{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "2Pmxv2ioyCRw"
   },
   "source": [
    "##### Copyright 2019 The TensorFlow Authors."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "cellView": "form",
    "execution": {
     "iopub.execute_input": "2022-12-14T22:54:48.269703Z",
     "iopub.status.busy": "2022-12-14T22:54:48.269239Z",
     "iopub.status.idle": "2022-12-14T22:54:48.273296Z",
     "shell.execute_reply": "2022-12-14T22:54:48.272774Z"
    },
    "id": "b-2ShX25yNWf"
   },
   "outputs": [],
   "source": [
    "#@title Licensed under the Apache License, Version 2.0 (the \"License\");\n",
    "# you may not use this file except in compliance with the License.\n",
    "# You may obtain a copy of the License at\n",
    "#\n",
    "# https://www.apache.org/licenses/LICENSE-2.0\n",
    "#\n",
    "# Unless required by applicable law or agreed to in writing, software\n",
    "# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
    "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
    "# See the License for the specific language governing permissions and\n",
    "# limitations under the License."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "pa49bUnKyRgF"
   },
   "source": [
    "# 시계열 예측"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "11Ilg92myRcw"
   },
   "source": [
    "<table class=\"tfo-notebook-buttons\" align=\"left\">\n",
    "  <td>     <a target=\"_blank\" href=\"https://www.tensorflow.org/tutorials/structured_data/time_series\"><img src=\"https://www.tensorflow.org/images/tf_logo_32px.png\"> TensorFlow.org에서 보기</a> </td>\n",
    "  <td>     <a target=\"_blank\" href=\"https://colab.research.google.com/github/tensorflow/docs-l10n/blob/master/site/ko/tutorials/structured_data/time_series.ipynb\"><img src=\"https://www.tensorflow.org/images/colab_logo_32px.png\">Google Colab에서 실행</a>   </td>\n",
    "  <td><a target=\"_blank\" href=\"https://github.com/tensorflow/docs-l10n/blob/master/site/ko/tutorials/structured_data/time_series.ipynb\"><img src=\"https://www.tensorflow.org/images/GitHub-Mark-32px.png\">GitHub에서소스 보기</a></td>\n",
    "  <td><a href=\"https://storage.googleapis.com/tensorflow_docs/docs-l10n/site/ko/tutorials/structured_data/time_series.ipynb\"><img src=\"https://www.tensorflow.org/images/download_logo_32px.png\">노트북 다운로드</a></td>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "GU8C5qm_4vZb"
   },
   "source": [
    "이 튜토리얼에서는 TensorFlow를 사용한 시계열 예측을 소개합니다. Convolutional/Recurrent Neural Network(CNN 및 RNN)를 포함하여 몇 가지 다른 스타일의 모델을 빌드합니다.\n",
    "\n",
    "이 내용은 각각 하위 항목이 있는 두 부분으로 나누어 생각합니다.\n",
    "\n",
    "- 단일 타임스텝 예측:\n",
    "    - 단일 특성\n",
    "    - 모든 특성\n",
    "- 다중 스텝 예측:\n",
    "    - 싱글샷: 모두 한 번에 예측합니다.\n",
    "    - 자가 회귀: 한 번에 하나의 예측을 수행하고 결과를 모델로 피드백합니다."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "XVhK72Pu1cJL"
   },
   "source": [
    "## 설정"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:54:48.277002Z",
     "iopub.status.busy": "2022-12-14T22:54:48.276533Z",
     "iopub.status.idle": "2022-12-14T22:54:50.999351Z",
     "shell.execute_reply": "2022-12-14T22:54:50.998613Z"
    },
    "id": "7rZnJaGTWQw0"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-12-14 22:54:50.306096: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory\n",
      "2022-12-14 22:54:50.306217: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory\n",
      "2022-12-14 22:54:50.306228: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "import datetime\n",
    "\n",
    "import IPython\n",
    "import IPython.display\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import tensorflow as tf\n",
    "\n",
    "mpl.rcParams['figure.figsize'] = (8, 6)\n",
    "mpl.rcParams['axes.grid'] = False"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "TokBlnUhWFw9"
   },
   "source": [
    "## 날씨 데이터세트\n",
    "\n",
    "이 튜토리얼은 <a class=\"external\" href=\"https://www.bgc-jena.mpg.de/wetter/\">막스 플랑크 생물 지구화학 연구소</a>에서 기록한 <a class=\"external\" href=\"https://www.bgc-jena.mpg.de\">날씨 시계열 데이터세트</a>를 사용합니다.\n",
    "\n",
    "이 데이터세트에는 온도, 대기압 및 습도와 같은 14가지 특성이 있습니다. 이러한 데이터는 2003년부터 시작해 10분 간격으로 수집되었습니다. 효율성을 위해 2009년과 2016년 사이에 수집된 데이터만 사용하겠습니다. 이 데이터세트 부분은 François Chollet이 자신이 저술한 책 [Deep Learning with Python](https://www.manning.com/books/deep-learning-with-python)을 위해 준비했습니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:54:51.003596Z",
     "iopub.status.busy": "2022-12-14T22:54:51.003141Z",
     "iopub.status.idle": "2022-12-14T22:54:51.456358Z",
     "shell.execute_reply": "2022-12-14T22:54:51.455504Z"
    },
    "id": "xyv_i85IWInT"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/jena_climate_2009_2016.csv.zip\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "    8192/13568290 [..............................] - ETA: 0s"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 4202496/13568290 [========>.....................] - ETA: 0s"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "13279232/13568290 [============================>.] - ETA: 0s"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "13568290/13568290 [==============================] - 0s 0us/step\n"
     ]
    }
   ],
   "source": [
    "zip_path = tf.keras.utils.get_file(\n",
    "    origin='https://storage.googleapis.com/tensorflow/tf-keras-datasets/jena_climate_2009_2016.csv.zip',\n",
    "    fname='jena_climate_2009_2016.csv.zip',\n",
    "    extract=True)\n",
    "csv_path, _ = os.path.splitext(zip_path)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "R81Wx8WP4c3G"
   },
   "source": [
    "이 튜토리얼은 **시간별 예측**만 다루므로 10분 간격부터 1시간까지 데이터를 서브 샘플링하는 것으로 시작합니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:54:51.461297Z",
     "iopub.status.busy": "2022-12-14T22:54:51.460568Z",
     "iopub.status.idle": "2022-12-14T22:54:52.257496Z",
     "shell.execute_reply": "2022-12-14T22:54:52.256731Z"
    },
    "id": "TX6uGeeeWIkG"
   },
   "outputs": [],
   "source": [
    "df = pd.read_csv(csv_path)\n",
    "# Slice [start:stop:step], starting from index 5 take every 6th record.\n",
    "df = df[5::6]\n",
    "\n",
    "date_time = pd.to_datetime(df.pop('Date Time'), format='%d.%m.%Y %H:%M:%S')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "VdbOWXiTWM2T"
   },
   "source": [
    "데이터를 살펴보겠습니다. 다음은 처음 몇 개의 행입니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:54:52.261837Z",
     "iopub.status.busy": "2022-12-14T22:54:52.261513Z",
     "iopub.status.idle": "2022-12-14T22:54:52.280344Z",
     "shell.execute_reply": "2022-12-14T22:54:52.279766Z"
    },
    "id": "ojHE-iCCWIhz"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>p (mbar)</th>\n",
       "      <th>T (degC)</th>\n",
       "      <th>Tpot (K)</th>\n",
       "      <th>Tdew (degC)</th>\n",
       "      <th>rh (%)</th>\n",
       "      <th>VPmax (mbar)</th>\n",
       "      <th>VPact (mbar)</th>\n",
       "      <th>VPdef (mbar)</th>\n",
       "      <th>sh (g/kg)</th>\n",
       "      <th>H2OC (mmol/mol)</th>\n",
       "      <th>rho (g/m**3)</th>\n",
       "      <th>wv (m/s)</th>\n",
       "      <th>max. wv (m/s)</th>\n",
       "      <th>wd (deg)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>996.50</td>\n",
       "      <td>-8.05</td>\n",
       "      <td>265.38</td>\n",
       "      <td>-8.78</td>\n",
       "      <td>94.4</td>\n",
       "      <td>3.33</td>\n",
       "      <td>3.14</td>\n",
       "      <td>0.19</td>\n",
       "      <td>1.96</td>\n",
       "      <td>3.15</td>\n",
       "      <td>1307.86</td>\n",
       "      <td>0.21</td>\n",
       "      <td>0.63</td>\n",
       "      <td>192.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>996.62</td>\n",
       "      <td>-8.88</td>\n",
       "      <td>264.54</td>\n",
       "      <td>-9.77</td>\n",
       "      <td>93.2</td>\n",
       "      <td>3.12</td>\n",
       "      <td>2.90</td>\n",
       "      <td>0.21</td>\n",
       "      <td>1.81</td>\n",
       "      <td>2.91</td>\n",
       "      <td>1312.25</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.63</td>\n",
       "      <td>190.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>996.84</td>\n",
       "      <td>-8.81</td>\n",
       "      <td>264.59</td>\n",
       "      <td>-9.66</td>\n",
       "      <td>93.5</td>\n",
       "      <td>3.13</td>\n",
       "      <td>2.93</td>\n",
       "      <td>0.20</td>\n",
       "      <td>1.83</td>\n",
       "      <td>2.94</td>\n",
       "      <td>1312.18</td>\n",
       "      <td>0.18</td>\n",
       "      <td>0.63</td>\n",
       "      <td>167.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>996.99</td>\n",
       "      <td>-9.05</td>\n",
       "      <td>264.34</td>\n",
       "      <td>-10.02</td>\n",
       "      <td>92.6</td>\n",
       "      <td>3.07</td>\n",
       "      <td>2.85</td>\n",
       "      <td>0.23</td>\n",
       "      <td>1.78</td>\n",
       "      <td>2.85</td>\n",
       "      <td>1313.61</td>\n",
       "      <td>0.10</td>\n",
       "      <td>0.38</td>\n",
       "      <td>240.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>997.46</td>\n",
       "      <td>-9.63</td>\n",
       "      <td>263.72</td>\n",
       "      <td>-10.65</td>\n",
       "      <td>92.2</td>\n",
       "      <td>2.94</td>\n",
       "      <td>2.71</td>\n",
       "      <td>0.23</td>\n",
       "      <td>1.69</td>\n",
       "      <td>2.71</td>\n",
       "      <td>1317.19</td>\n",
       "      <td>0.40</td>\n",
       "      <td>0.88</td>\n",
       "      <td>157.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    p (mbar)  T (degC)  Tpot (K)  Tdew (degC)  rh (%)  VPmax (mbar)  \\\n",
       "5     996.50     -8.05    265.38        -8.78    94.4          3.33   \n",
       "11    996.62     -8.88    264.54        -9.77    93.2          3.12   \n",
       "17    996.84     -8.81    264.59        -9.66    93.5          3.13   \n",
       "23    996.99     -9.05    264.34       -10.02    92.6          3.07   \n",
       "29    997.46     -9.63    263.72       -10.65    92.2          2.94   \n",
       "\n",
       "    VPact (mbar)  VPdef (mbar)  sh (g/kg)  H2OC (mmol/mol)  rho (g/m**3)  \\\n",
       "5           3.14          0.19       1.96             3.15       1307.86   \n",
       "11          2.90          0.21       1.81             2.91       1312.25   \n",
       "17          2.93          0.20       1.83             2.94       1312.18   \n",
       "23          2.85          0.23       1.78             2.85       1313.61   \n",
       "29          2.71          0.23       1.69             2.71       1317.19   \n",
       "\n",
       "    wv (m/s)  max. wv (m/s)  wd (deg)  \n",
       "5       0.21           0.63     192.7  \n",
       "11      0.25           0.63     190.3  \n",
       "17      0.18           0.63     167.2  \n",
       "23      0.10           0.38     240.0  \n",
       "29      0.40           0.88     157.0  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "WRzj1inMfgcO"
   },
   "source": [
    "시간이 지남에 따른 몇 가지 특성의 전개 양상은 다음과 같습니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:54:52.283931Z",
     "iopub.status.busy": "2022-12-14T22:54:52.283406Z",
     "iopub.status.idle": "2022-12-14T22:54:54.364912Z",
     "shell.execute_reply": "2022-12-14T22:54:54.364198Z"
    },
    "id": "Vg5XIc5tfNlG"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmpfs/tmp/ipykernel_750642/637349053.py:7: FutureWarning: The behavior of `series[i:j]` with an integer-dtype index is deprecated. In a future version, this will be treated as *label-based* indexing, consistent with e.g. `series[i]` lookups. To retain the old behavior, use `series.iloc[i:j]`. To get the future behavior, use `series.loc[i:j]`.\n",
      "  plot_features.index = date_time[:480]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x600 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x600 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_cols = ['T (degC)', 'p (mbar)', 'rho (g/m**3)']\n",
    "plot_features = df[plot_cols]\n",
    "plot_features.index = date_time\n",
    "_ = plot_features.plot(subplots=True)\n",
    "\n",
    "plot_features = df[plot_cols][:480]\n",
    "plot_features.index = date_time[:480]\n",
    "_ = plot_features.plot(subplots=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "wXWLG0_WBhZS"
   },
   "source": [
    "### 검사 및 정리하기"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "yhmZXJew6GlS"
   },
   "source": [
    "다음으로 데이터세트의 통계를 살펴봅니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:54:54.369250Z",
     "iopub.status.busy": "2022-12-14T22:54:54.368977Z",
     "iopub.status.idle": "2022-12-14T22:54:54.445048Z",
     "shell.execute_reply": "2022-12-14T22:54:54.444345Z"
    },
    "id": "h510pgKVrrai"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>p (mbar)</th>\n",
       "      <td>70091.0</td>\n",
       "      <td>989.212842</td>\n",
       "      <td>8.358886</td>\n",
       "      <td>913.60</td>\n",
       "      <td>984.20</td>\n",
       "      <td>989.57</td>\n",
       "      <td>994.720</td>\n",
       "      <td>1015.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>T (degC)</th>\n",
       "      <td>70091.0</td>\n",
       "      <td>9.450482</td>\n",
       "      <td>8.423384</td>\n",
       "      <td>-22.76</td>\n",
       "      <td>3.35</td>\n",
       "      <td>9.41</td>\n",
       "      <td>15.480</td>\n",
       "      <td>37.28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tpot (K)</th>\n",
       "      <td>70091.0</td>\n",
       "      <td>283.493086</td>\n",
       "      <td>8.504424</td>\n",
       "      <td>250.85</td>\n",
       "      <td>277.44</td>\n",
       "      <td>283.46</td>\n",
       "      <td>289.530</td>\n",
       "      <td>311.21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tdew (degC)</th>\n",
       "      <td>70091.0</td>\n",
       "      <td>4.956471</td>\n",
       "      <td>6.730081</td>\n",
       "      <td>-24.80</td>\n",
       "      <td>0.24</td>\n",
       "      <td>5.21</td>\n",
       "      <td>10.080</td>\n",
       "      <td>23.06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rh (%)</th>\n",
       "      <td>70091.0</td>\n",
       "      <td>76.009788</td>\n",
       "      <td>16.474920</td>\n",
       "      <td>13.88</td>\n",
       "      <td>65.21</td>\n",
       "      <td>79.30</td>\n",
       "      <td>89.400</td>\n",
       "      <td>100.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VPmax (mbar)</th>\n",
       "      <td>70091.0</td>\n",
       "      <td>13.576576</td>\n",
       "      <td>7.739883</td>\n",
       "      <td>0.97</td>\n",
       "      <td>7.77</td>\n",
       "      <td>11.82</td>\n",
       "      <td>17.610</td>\n",
       "      <td>63.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VPact (mbar)</th>\n",
       "      <td>70091.0</td>\n",
       "      <td>9.533968</td>\n",
       "      <td>4.183658</td>\n",
       "      <td>0.81</td>\n",
       "      <td>6.22</td>\n",
       "      <td>8.86</td>\n",
       "      <td>12.360</td>\n",
       "      <td>28.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VPdef (mbar)</th>\n",
       "      <td>70091.0</td>\n",
       "      <td>4.042536</td>\n",
       "      <td>4.898549</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.87</td>\n",
       "      <td>2.19</td>\n",
       "      <td>5.300</td>\n",
       "      <td>46.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sh (g/kg)</th>\n",
       "      <td>70091.0</td>\n",
       "      <td>6.022560</td>\n",
       "      <td>2.655812</td>\n",
       "      <td>0.51</td>\n",
       "      <td>3.92</td>\n",
       "      <td>5.59</td>\n",
       "      <td>7.800</td>\n",
       "      <td>18.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>H2OC (mmol/mol)</th>\n",
       "      <td>70091.0</td>\n",
       "      <td>9.640437</td>\n",
       "      <td>4.234862</td>\n",
       "      <td>0.81</td>\n",
       "      <td>6.29</td>\n",
       "      <td>8.96</td>\n",
       "      <td>12.490</td>\n",
       "      <td>28.74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rho (g/m**3)</th>\n",
       "      <td>70091.0</td>\n",
       "      <td>1216.061232</td>\n",
       "      <td>39.974263</td>\n",
       "      <td>1059.45</td>\n",
       "      <td>1187.47</td>\n",
       "      <td>1213.80</td>\n",
       "      <td>1242.765</td>\n",
       "      <td>1393.54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>wv (m/s)</th>\n",
       "      <td>70091.0</td>\n",
       "      <td>1.702567</td>\n",
       "      <td>65.447512</td>\n",
       "      <td>-9999.00</td>\n",
       "      <td>0.99</td>\n",
       "      <td>1.76</td>\n",
       "      <td>2.860</td>\n",
       "      <td>14.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max. wv (m/s)</th>\n",
       "      <td>70091.0</td>\n",
       "      <td>2.963041</td>\n",
       "      <td>75.597657</td>\n",
       "      <td>-9999.00</td>\n",
       "      <td>1.76</td>\n",
       "      <td>2.98</td>\n",
       "      <td>4.740</td>\n",
       "      <td>23.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>wd (deg)</th>\n",
       "      <td>70091.0</td>\n",
       "      <td>174.789095</td>\n",
       "      <td>86.619431</td>\n",
       "      <td>0.00</td>\n",
       "      <td>125.30</td>\n",
       "      <td>198.10</td>\n",
       "      <td>234.000</td>\n",
       "      <td>360.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   count         mean        std      min      25%      50%  \\\n",
       "p (mbar)         70091.0   989.212842   8.358886   913.60   984.20   989.57   \n",
       "T (degC)         70091.0     9.450482   8.423384   -22.76     3.35     9.41   \n",
       "Tpot (K)         70091.0   283.493086   8.504424   250.85   277.44   283.46   \n",
       "Tdew (degC)      70091.0     4.956471   6.730081   -24.80     0.24     5.21   \n",
       "rh (%)           70091.0    76.009788  16.474920    13.88    65.21    79.30   \n",
       "VPmax (mbar)     70091.0    13.576576   7.739883     0.97     7.77    11.82   \n",
       "VPact (mbar)     70091.0     9.533968   4.183658     0.81     6.22     8.86   \n",
       "VPdef (mbar)     70091.0     4.042536   4.898549     0.00     0.87     2.19   \n",
       "sh (g/kg)        70091.0     6.022560   2.655812     0.51     3.92     5.59   \n",
       "H2OC (mmol/mol)  70091.0     9.640437   4.234862     0.81     6.29     8.96   \n",
       "rho (g/m**3)     70091.0  1216.061232  39.974263  1059.45  1187.47  1213.80   \n",
       "wv (m/s)         70091.0     1.702567  65.447512 -9999.00     0.99     1.76   \n",
       "max. wv (m/s)    70091.0     2.963041  75.597657 -9999.00     1.76     2.98   \n",
       "wd (deg)         70091.0   174.789095  86.619431     0.00   125.30   198.10   \n",
       "\n",
       "                      75%      max  \n",
       "p (mbar)          994.720  1015.29  \n",
       "T (degC)           15.480    37.28  \n",
       "Tpot (K)          289.530   311.21  \n",
       "Tdew (degC)        10.080    23.06  \n",
       "rh (%)             89.400   100.00  \n",
       "VPmax (mbar)       17.610    63.77  \n",
       "VPact (mbar)       12.360    28.25  \n",
       "VPdef (mbar)        5.300    46.01  \n",
       "sh (g/kg)           7.800    18.07  \n",
       "H2OC (mmol/mol)    12.490    28.74  \n",
       "rho (g/m**3)     1242.765  1393.54  \n",
       "wv (m/s)            2.860    14.01  \n",
       "max. wv (m/s)       4.740    23.50  \n",
       "wd (deg)          234.000   360.00  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe().transpose()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "TzOTnWOoWMGK"
   },
   "source": [
    "#### 풍속"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "i47LiW5DCVsP"
   },
   "source": [
    "한 가지 눈에 띄는 점은 풍속(`wv (m/s)`)의 `min` 값과 최댓값(`max. wv (m/s)`) 열입니다. `-9999`는 오류일 수 있습니다.\n",
    "\n",
    "별도의 풍향 열이 있으므로 속도는 0보다 커야 합니다({code 0}&gt;=0{/code 0}). 0으로 교체합니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:54:54.449024Z",
     "iopub.status.busy": "2022-12-14T22:54:54.448352Z",
     "iopub.status.idle": "2022-12-14T22:54:54.458386Z",
     "shell.execute_reply": "2022-12-14T22:54:54.457690Z"
    },
    "id": "qFOq0_80vF4d"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wv = df['wv (m/s)']\n",
    "bad_wv = wv == -9999.0\n",
    "wv[bad_wv] = 0.0\n",
    "\n",
    "max_wv = df['max. wv (m/s)']\n",
    "bad_max_wv = max_wv == -9999.0\n",
    "max_wv[bad_max_wv] = 0.0\n",
    "\n",
    "# The above inplace edits are reflected in the DataFrame.\n",
    "df['wv (m/s)'].min()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "vtmu2IBPgPG8"
   },
   "source": [
    "### 특성 엔지니어링\n",
    "\n",
    "모델을 구축하기 전에 데이터를 이해하고 모델에 적절한 형식의 데이터를 전달하고 있는지 확인하는 것이 중요합니다."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "FYyEaqiD6j4s"
   },
   "source": [
    "#### 바람\n",
    "\n",
    "데이터의 마지막 열인 `wd (deg)` - 바람의 방향을 도 단위로 제공합니다. 각도는 좋은 모델 입력을 만들지 않습니다. 360°와 0°는 서로 가깝고 부드럽게 둘러싸야 합니다. 바람이 불지 않으면 방향은 중요하지 않습니다.\n",
    "\n",
    "현재, 바람 데이터의 분포는 다음과 같습니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:54:54.462440Z",
     "iopub.status.busy": "2022-12-14T22:54:54.461711Z",
     "iopub.status.idle": "2022-12-14T22:54:54.705652Z",
     "shell.execute_reply": "2022-12-14T22:54:54.704952Z"
    },
    "id": "YO7JGTcWQG2z"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Wind Velocity [m/s]')"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist2d(df['wd (deg)'], df['wv (m/s)'], bins=(50, 50), vmax=400)\n",
    "plt.colorbar()\n",
    "plt.xlabel('Wind Direction [deg]')\n",
    "plt.ylabel('Wind Velocity [m/s]')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "yWnf5dwMU1_g"
   },
   "source": [
    "그러나 풍향과 속도 열을 바람 **벡터**로 변환하면 모델이 해석하기가 더 쉽습니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:54:54.709607Z",
     "iopub.status.busy": "2022-12-14T22:54:54.709345Z",
     "iopub.status.idle": "2022-12-14T22:54:54.726103Z",
     "shell.execute_reply": "2022-12-14T22:54:54.725369Z"
    },
    "id": "6GmSTHXw6lI1"
   },
   "outputs": [],
   "source": [
    "wv = df.pop('wv (m/s)')\n",
    "max_wv = df.pop('max. wv (m/s)')\n",
    "\n",
    "# Convert to radians.\n",
    "wd_rad = df.pop('wd (deg)')*np.pi / 180\n",
    "\n",
    "# Calculate the wind x and y components.\n",
    "df['Wx'] = wv*np.cos(wd_rad)\n",
    "df['Wy'] = wv*np.sin(wd_rad)\n",
    "\n",
    "# Calculate the max wind x and y components.\n",
    "df['max Wx'] = max_wv*np.cos(wd_rad)\n",
    "df['max Wy'] = max_wv*np.sin(wd_rad)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "7iI0zDoxWDyB"
   },
   "source": [
    "바람 벡터의 분포는 모델이 올바르게 해석하는 데 훨씬 간단합니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:54:54.729666Z",
     "iopub.status.busy": "2022-12-14T22:54:54.729420Z",
     "iopub.status.idle": "2022-12-14T22:54:54.980276Z",
     "shell.execute_reply": "2022-12-14T22:54:54.979583Z"
    },
    "id": "bMgCG5o2SYKD"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-11.305513973134667, 8.24469928549079, -8.27438540335515, 7.7338312955467785)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist2d(df['Wx'], df['Wy'], bins=(50, 50), vmax=400)\n",
    "plt.colorbar()\n",
    "plt.xlabel('Wind X [m/s]')\n",
    "plt.ylabel('Wind Y [m/s]')\n",
    "ax = plt.gca()\n",
    "ax.axis('tight')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "_8im1ttOWlRB"
   },
   "source": [
    "#### 시간"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "7YE21HKK40zQ"
   },
   "source": [
    "마찬가지로 `Date Time` 열은 매우 유용하지만 이 문자열 형식은 아닙니다. 초로 변환하여 시작하십시오."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:54:54.984145Z",
     "iopub.status.busy": "2022-12-14T22:54:54.983867Z",
     "iopub.status.idle": "2022-12-14T22:54:55.275667Z",
     "shell.execute_reply": "2022-12-14T22:54:55.274631Z"
    },
    "id": "LIFf-VjMfnh3"
   },
   "outputs": [],
   "source": [
    "timestamp_s = date_time.map(pd.Timestamp.timestamp)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "EC_pnM1D5Sgc"
   },
   "source": [
    "풍향과 유사하게 초 단위의 시간은 유용한 모델 입력이 아닙니다. 날씨 데이터이기 때문에 일별 및 연간 주기가 명확합니다. 주기성을 다룰 수 있는 방법은 여러 가지가 있습니다.\n",
    "\n",
    "사인 및 코사인 변환을 사용하여 \"시간\" 및 \"시간\" 신호를 지우면 사용 가능한 신호를 얻을 수 있습니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:54:55.279503Z",
     "iopub.status.busy": "2022-12-14T22:54:55.279207Z",
     "iopub.status.idle": "2022-12-14T22:54:55.292162Z",
     "shell.execute_reply": "2022-12-14T22:54:55.291429Z"
    },
    "id": "MBfX6CDwax73"
   },
   "outputs": [],
   "source": [
    "day = 24*60*60\n",
    "year = (365.2425)*day\n",
    "\n",
    "df['Day sin'] = np.sin(timestamp_s * (2 * np.pi / day))\n",
    "df['Day cos'] = np.cos(timestamp_s * (2 * np.pi / day))\n",
    "df['Year sin'] = np.sin(timestamp_s * (2 * np.pi / year))\n",
    "df['Year cos'] = np.cos(timestamp_s * (2 * np.pi / year))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:54:55.295820Z",
     "iopub.status.busy": "2022-12-14T22:54:55.295552Z",
     "iopub.status.idle": "2022-12-14T22:54:55.481941Z",
     "shell.execute_reply": "2022-12-14T22:54:55.481134Z"
    },
    "id": "mXBbTJZfuuTC"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Time of day signal')"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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h6gSrFZKPwLFf4dhvkLBTu9/oAE16QqvbodVtUC9UaUwVbKrATUxMJDAwsNx9gYGBZGRkkJuby+XLlzGbzVc95ujRo9c87xtvvMGrr75aI5mF/bJarRxPymLtkSTWHE5ib3xaucf9PZ25lJXP0cRMjiZm8vEfJ/H3dCaqTQBRbQLp1dwPF0eTmvBCCCHsk7kQzm7VCtpjv0La2fKPewZD5nk4s0m7rXoBAtpqhW6r2yG4Mxjtv8eATRW4NWXmzJnMmDGj9NcZGRmEhIQoTCRsVaHZQsyZVNYcTmLd0STiU3PLPd4xxIdBbQKIahtIq0BP0nIK2XA8mbWHk9l4PIWUzHyWxsSzNCYeF0cjfVr4M6hNILe2DsDf01nRuxJCCKFruWlwcq1W1J5YA/npZY+ZnCGsv1bAthwKXg3g0ik4vko7/uxWSD6s3Ta/C+4B0GqoVuw27QdO9jnNzqYK3KCgIJKSksrdl5SUhJeXF66urphMJkwm01WPCQoKuuZ5nZ2dcXaW4kJcXXpuIRuOJbP2SDIbjiWTmVdU+pizg5Hezf2IahvIwNYBBHi5lHtuPXcn7uzUiDs7NSK/yEz06VTWHkli7eEkzqfnseawdvXXYIBOIT5EtQ1kUJtAmgd4YDDIVAYhhBDXcDkWjq3SrtKe3QKWsu9NuPlpxWyr26DZreDkXv659ZtB5GPaLSe1uDj+FU6shexk2P2FdnNw1Z5fUhx7BNTqW6xJNlXgRkZG8uuvv5a7b82aNURGRgLg5OREly5dWLduXeliNYvFwrp163j88cdrO67QsfjUHNYcTmLtkSRizqRSZClba1nf3YmBxdMMerfww82pav9MnB1M9G3pT9+W/rw6/BYOX8hg7WFtzu6BhHR2x6WxOy6Nt1cdo0l9N23ebptAuoXWw8Fk/x8XCSGEqIDFAuf3lM2nTT5U/nG/VmXTDBp1BWMVp8C5+UKHe7VbUQGc/bN4esNvkB5f/Hq/AgbtvCWv4d8adHwhpka7KGRlZXHy5EkAOnXqxHvvvcett96Kr68vjRs3ZubMmSQkJPDFF18AWpuwdu3a8dhjj/HQQw+xfv16nnzySX755ReGDBkCaG3Cxo8fz6effkr37t354IMP+Prrrzl69OgVc3OvRboo1D0Wi5X9CemsLS5qjyZmlnu8RYAHUW21gjM8xAdTNS8Uu5Cey7riBWpbT16iwGwpfczb1ZFbW/kT1TaQfi398XRxrNbXFkIIYaMKc+H0Rq3APL4Ksv7yCbXBCI17Fhect2lXZauT1QpJB8vm8p7fU/7xeqFli9QaR4Kp9r833Uy9VqMF7oYNG7j11luvuH/8+PEsXLiQCRMmEBsby4YNG8o95+9//zuHDx+mUaNG/POf/2TChAnlnv/xxx/zn//8h8TERMLDw/nwww+JiIiocq5aL3BzL0N8DLQcUvOvJUrlF5n588RFbcrAkWRSMss6aZiMBrqF1iu9ihrq517BmapXdn4Rm0+ksOZwMuuPJnE5p7D0MUeTgR5h9YlqE8jgWwJp4O1aa7mEEELUguxLZVdpT62Hor+s9XDyhOYDtcKyxSDt6mttyThfNm/39EYwl33PxMUbWgzWit3mUdqvayOSrRa4tqpWC9zCPFh8lzbJe+ib0GNqzb6eACAxPY8JC2LKXan1cHagXytt0Vf/Vv74uDkpTKgxW6zsjrvM2sNJrDmSxOmU7NLHHE0G/nN3R0Z2aqgwoRBCiGpzeiMsfwDy/9Ku1KtR2VXa0N7gYANrhvKz4PQfWrF7fBXkXCp7zOgIM46Ah3+Nx5AC9zrVaoFrMcNvz8GOedqvez0FA1+pEy06VDmelMmE+TGcT8+jnpsjwzsGE9U2kIim9XFysO3f91MpWaw7ksQv+y+w75y2Snbmba2Z0jdMFqUJIYSeHVgB308FS6E2n7bdKK2oDWpv23NdLWY4t6PsqrPJGab9WSsvLQXudar1KQpWK/z5Hqx7Tft1+3thxCxwUH8F0d7siE1l0sIdZOQVEebvzqKJ3XW505jFYuVfvxxh/pYzAEzsFco/h7WVTSSEEEKPtn4Eq1/Uxm1Hwp2fgqNLhU+xWXnpupiiYNuXs+yFwQB9noaRs8FgggNfw1f3Qn5m5c8VVbbq4AXGzosmI6+Izo19+HZqT10WtwBGo4GX7mjLP25vA8CCLbE8sWwPeYVmxcmEEEJUmcUCq/6vrLiNmAp3L9BvcQu1VtzeLClwa1P4/XD/1+Dors1tWXC7tm+0uGlfbItl2pLdFBRZiGoTyJKHe1DPXf9XyCf3DeO/Y8JxNBn4Zf8Fxs+PIT23sPInCiGEUKsoH757GLbP0n496DVtLY5MUawV8rtc21pEwYSV4O4Pifvh8yi4eFJ1Kt2yWq28veooL/14CKsV7uvemDkPdMbVyX62yB0R3pCFE7vj4exA9JlURn+6jcT0PNWxhBBCXEteOiweBQe/BaMD3PmZtgbHlufa2hkpcFVo2BkmrYZ6TSEtDj4fBPE7VKfSnUKzhae/2ccnG04BMGNQS/59Zzu73DShV3M/lj/SA39PZ44mZnLXJ1s4niRTXIQQwuZkXNA+oY3dDE4eMPYb6Dhadao6x/4qAb3wDYNJayC4E+SmwqI7tC35RJVk5xcxadFOvtudgMlo4K1R7XlyYAu77jRwS7A3303rSZi/O+fT87h79lZ2xKaqjiWEEKJEyjHtolXSQXAPgIm/QrMBqlPVSVLgquThD+NXQvNBWqPnZffBrkWqU9m8lMx8xny2nU3HU3B1NDF3XBdGd2usOlatCPF149upPenc2IeMvCLGzotm1cELqmMJIYSI2w6fD9a2v63fHB5eAw06qk5VZ0mBq5qzB9y3FMIfAKsFfn4SNryptRYTV4i9mM2o2Vs5kJCOr7sTS6f0YEDrqm3RbC/quTux5OEeRLUJpKDIwrQlu/liW6zqWEIIUXcdWQlfjIC8NGjYFR5arW11K5SRAtcWmBxhxMfQ5xnt1xvegJ+fAnOR2lw2Zm98GqNmbyUuNYcQX1dWTI0kPMRHdSwlXJ1MzHmgM/d1b4zVCi/9eIi3Vx2lDra1FkIItXZ8Dl8/CEV50HIojP8Z3OurTlXnSYFrKwwGGPhPGPYuGIywe5G2nV9BjupkNuGPo8nc99l2LmUX0K6hF99N60WYv4fqWEo5mIz8+852zBjUEoBPNpzi6W/2UWi2KE4mhBB1gNUK616HX2Zon8B2Hgejl4CTPvuv2xspcG1Nt4fh3i/BwQWO/wZfDIfsS5U/z459vTOeh7/YSW6hmT4t/Fg2JRJ/TxvYq9sGGAwGnhzYgrdGtcdkNPDd7gQmLdpJdr5c/RdCiBpjLoQfH4fN72i/7j8T7vgQTA5qc4lSUuDaojZ/g3E/gouPtv/z/MFwOVZ1qlpntVr5aN0JnluxH7PFyl2dGvL5+G54OMt/IP9rdLfGzB3XBVdHE5uOpzDms+2kZOarjiWEEPYnPwuW3gd7F2ufuN7xX+j/gvS4tTFS4Nqqxj20XrneIXDppLYy88I+1alqjdli5cUfDvLumuMATOvfjHfv7YiTg/yVvZYBrQNZOqUHvu5OHEhIZ9TsrcRezFYdSwgh7EdWCiz6G5xcAw6uMOYr6DJBdSpxFVIt2DL/Vlqv3MB2kJWkNY4+tV51qhqXV2hm2uJdLImOw2CAV4ffwvNDW9t1j9vqEh7iw4qpkYT4uhKXmsOo2VvZG5+mOpYQQuhf6mntE9Xze8DVV1tM1uo21anENUiBa+u8GmiNokP7QEEWLLkH9n+tOlWNuZxdwNh50aw+nISTg5FZ93dmfM9Q1bF0Jczfg++m9aJdQy8uZRdw32fb+eNosupYQgihXwm7Yd4grcj1aax9whrSTXUqUQEpcPXAxRse+BZuuQssRfDdZNjyX7vrlXvucg53z9nKrrOX8XJx4MuHunN7+waqY+mSv6czy6ZE0qeFH7mFZh7+Yidf74xXHUsIIfTnxFpY+DfIuQhB7bVPVv1aqE4lKiEFrl44OMOoz6HHY9qv17wEq2aCxT5aQh0+n8Fdn2zlVEo2DbxdWDGtJxFh0kfwZng4O/D5+G7c1akhZouV51bs56N1J6RXrhBCVNXer2DpaCjMhrD+MOFX8AxSnUpUgRS4emI0wtB/w+B/ab+Ong0rJkJhntpcN2nryYvc++k2kjPzaRXoyXeP9qRloKfqWHbBycHIu/d2ZFr/ZgC8u+Y4L/5wELNFilwhhLgmqxU2vQM/TNM+OW1/L9z/Dbh4qU4mqkgKXD3q+YR2NdfoCId/gMWjIDdNdaob8tO+84xfEENWfhHdm/ry9dRIGni7qo5lVwwGA88Pbc2rw2/BYIAl0XFMXbyLvEKz6mhCCGF7LGb49RlY/7r2615PwZ2fgoOT2lziukiBq1ft79bm5Tp5wtk/4at7dbe17/qjSTy5dA+FZivD2jfgi4e64+3qqDqW3RrfM5RP7u+Mk4ORNYeTeGLpHpmuIIQQ/2v1i7BjHmCAoW/BoNe0T1CFrsifmJ6F9YOHfgNnL4iPhj/fU52oyi5m5fPciv0AjO4awkf3dcLF0aQ4lf27rX0DvnyoO04mrchdtkMWngkhRKmT62D7J9p41DzoMVVtHnHDpMDVu6D2MOxdbbzhTTi3U22eKrBarTy/Yj8XswpoHeTJqyNuwWiUHre1JSKsPs8NbQXAaz8f5nRKluJEQghhA7IvwQ+PauPuU7RPSoVuSYFrD9rfA+1GgdWstRDLt+2C5auYONYdTcbJZOSDMeFy5VaBh3o1pWez+uQWmvn78r0Umu2jG4cQQtwQqxVWPgVZieDXCqJeVZ1I3CQpcO2BwaBdxfVqqDWh/v3/VCe6plMpWby+8jAAzw1tResgWZGqgtFo4N17O+Ll4sC+c+l8tO6E6khCCKHO3iVw5Gdt8fZdn4GTm+pE4iZJgWsvXOvBnXMAA+xeBEd/UZ3oCoVmC39fvpe8Qgu9mtfnoV5NVUeq0xp4u/Lvu9oD8PEfJ9l1NlVxIiGEUCD1NPz2vDYe8A8IDlcaR1QPKXDtSdO+0PNxbfzTE5CZpDbP//hw3Qn2n0vH29WRd+7pKPNubcDfOgRzV6eGWKwwfflesvL11YlDCCFuirkIvnsECrKgSS/o+aTqRKKaSIFrbwb8EwLbQ84l+PExm9nOd2dsKrP+OAnAv+9sL71ubcgrI26hoY8r8am5vPrTIdVxhBCi9vz5HpyLAWdv7VNQo6wJsRdS4NobB2cYNRdMznByTXEvP7Uy8wr5+9d7sVhhVOdGDOvQQHUk8RdeLo68PzocowG+2XWO3w5cUB1JCCFq3rldWvch0Nax+DRWm0dUKylw7VFAG60xNWgNq1OOKY3zyk+HiU/NpVE9V14Z3lZpFnF13Zv6lm7nO/P7AySm63v7ZyGEqFB+Fnz3sNZ9qN3d0OEe1YlENZMC1151nwLNBkBRHnz7MBQVKInxy/4LfLv7HEYDvD86HE8X2anMVj01sCXtG3qTllPIsyv2YbHYxvQWIYSodr//n7a4zKsRDHtHdRpRA6TAtVdGI4z4BFx9IXE/bPh3rUdITM/j/74/AMCj/ZvTLdS31jOIqnNyMPL+6HBcHI1sPnGRhVtjVUcSQojqd/QXrdsQBrhzttaFSNgdKXDtmVcDuOO/2vjPDyB2S629tMVi5Zlv9pGeW0iHRt48FdWi1l5b3LjmAR78Y5g2jeTNVUc5lpipOJEQQlSjzCStyxBAzye07kPCLkmBa+/aDodODwBW+P4RyEuvlZddsDWWP09exMVRuyroaJK/anrxQERjBrQOoKDIwlPL9pBfZFYdSQghbp7VqnUXyrmkdRsa8KLqRKIGSdVRFwx9E+qFQno8/Ppsjb/c0cQM3lp1FIAXh7Wlmb9Hjb+mqD4Gg4G3RnWgvrsTRxMzeXf1cdWRhBDi5u2Yp3UXcnDRug05OKtOJGqQFLh1gbMn3DUXDEbYvxwOrKixl8orNDN92V4KiiwMbB3A2Ahpu6JH/p7OvDWqAwBzN59m68mLihMJIcRNSDmmdRUCrctQQBu1eUSNkwK3rgjpDn2Lr96unAFp8TXyMu/8foyjiZn4eTjx1t0dMBhktzK9imobyP0RjbFaYcbX+0jPKVQdSQghrl9RQXE3oTxoNhC6TVadSNQCKXDrkr7PQsMukJ8OP0wDi6VaT7/l5EXm/XkGgLdGdcDPQz7+0bsXh7WhqZ87iRl5/N8PB7DayM54QghRZRv+rXUTcvWFEbO0LkPC7smfcl1ictSmKji6Q+xm2PZxtZ06LaeAp7/eB8DYiMYMbBNYbecW6rg5OfDB6HBMRgO/7L/AD3sTVEcSQoiqi92idRECrauQl+ykWVdIgVvX1G8GQ9/Qxuteg8QDN31Kq9XKP74/SGJGHmF+7vxjmMxtsicdQ3yYPlBr8/bSD4eIT81RnEgIIaogL13rHoRV6ybUdrjqRKIWSYFbF3UeB62GgaUQvp0Mhbk3dbrv9yTwy4ELOBgNfDAmHDcnh2oKKmzFtP7N6NKkHpn5RTz99T7MssuZEMLW/fqs1j2oXlOtm5CoU2qlwJ01axahoaG4uLgQERFBTEzMNY/t378/BoPhituwYcNKj5kwYcIVjw8dOrQ23op9MBhg+IfgHgApR2Dtqzd8qvjUHF768RAAfx/Ukg6NfKoppLAlDiYjH4wOx8PZgZjYVD7ddEp1JCGEuLYDK7SuQQaTNjXP2VN1IlHLarzAXb58OTNmzODll19m9+7ddOzYkSFDhpCcnHzV47/77jsuXLhQejt48CAmk4l77rmn3HFDhw4td9zSpUtr+q3YF3c/GPmJNo6eDSfXXfcpzBYrM77eS1Z+EV2b1GNqv2bVHFLYkhBfN14ZfgsA760+zoFztbNpiBBCXJf0c/DLDG3c91kI6aY2j1Cixgvc9957j8mTJzNx4kTatm3LnDlzcHNzY/78+Vc93tfXl6CgoNLbmjVrcHNzu6LAdXZ2LndcvXqyl/R1azGorF3KD9Mg+9J1PX3OxlPsiL2Mh7MD7xcvRBL2bVTnhtzePogii5Wnlu8ht0B2ORNC2BCLBb6fqs2/bdgV+j6jOpFQpEYL3IKCAnbt2kVUVFTZCxqNREVFsW3btiqd4/PPP2fMmDG4u7uXu3/Dhg0EBATQqlUrpk2bxqVL1y7O8vPzycjIKHcTxQa9Bn6tICsJVj6lbWVYBfvPpfH+Gm2Hq1eH30KIr1tNphQ2wmAw8P9GtifQy5nTKdn8+9cjqiMJIUSZbR9rXYIc3eGuz7TuQaJOqtEC9+LFi5jNZgIDy7eMCgwMJDExsdLnx8TEcPDgQR5++OFy9w8dOpQvvviCdevW8dZbb7Fx40Zuu+02zOarX01644038Pb2Lr2FhITc+JuyN05u2n8CRkc48jPsXVLpU3IKipi+bC9FFivD2jfgrs4NayGosBX13J14556OAHy5/Sx/HL36dCMhhKhViQe07kCgdQuqL9Pm6jKb7qLw+eef0759e7p3717u/jFjxjB8+HDat2/PyJEjWblyJTt27GDDhg1XPc/MmTNJT08vvcXH18wuXroVHA4D/qGNf3seUk9XePi/fz3C6YvZBHo58//ubCe7ldVBfVr481CvpgA8u2IfF7PyFScSQtRphblaVyBLodYlqPM41YmEYjVa4Pr5+WEymUhKSip3f1JSEkFBQRU+Nzs7m2XLljFp0qRKXycsLAw/Pz9Onjx51cednZ3x8vIqdxP/o+eT0KQXFGTBd4+Aueiqh60/msTi7XEAvHtPOD5uTrWZUtiQ54a2olWgJxezCnjhW9nlTAih0NpXta5AHoFalyC58FLn1WiB6+TkRJcuXVi3rmyFvsViYd26dURGRlb43G+++Yb8/HweeOCBSl/n3LlzXLp0iQYNZIeSG2Y0wZ1zwNkbzsXA5nevOORiVj7PrdgPwMO9m9K7hV9tpxQ2xMXRxAdjwnEyGVl7JImlMfLJiBBCgZPrtG5AACM+0boEiTqvxqcozJgxg7lz57Jo0SKOHDnCtGnTyM7OZuLEiQCMGzeOmTNnXvG8zz//nJEjR1K/fv1y92dlZfHss8+yfft2YmNjWbduHSNGjKB58+YMGTKkpt+OffNpDMOKC9uNb8G5naUPWa1Wnl+xn4tZBbQO8uSZIa0UhRS2pE0DL54bqv1deH3lYU6nZClOJISoU7IvaV2AALpPgRZRFR8v6owaL3BHjx7NO++8w0svvUR4eDh79+5l1apVpQvP4uLiuHDhQrnnHDt2jD///POq0xNMJhP79+9n+PDhtGzZkkmTJtGlSxc2b96Ms7NzTb8d+9fhHmh3N1jN8N1kyNcKlq9i4lh3NBknk5EPxoTj4mhSHFTYiod6NaVns/rkFpr5+/K9FJotqiMJIeoCq1Xr/pOVpHUDirrxTYuE/TFY6+DEuYyMDLy9vUlPT5f5uFeTexlm94aMc9B5PKci/82wDzeTV2jhxWFteLhPmOqEwsZcSM9lyPubyMgr4skBzZkxWK7wCyFq2J7F8ONjWhegh9dqC6aFXbmZes2muygIRVzrwZ2zAQPsXsSyL2aTV2ihV/P6pSvnhfirBt6u/Puu9gB8/MdJdp1NVZxICGHXUk9rXX9A6wIkxa34H1Lgiqtr2hd6PgHA1Iz/0tQlh3fu6YhRdisT1/C3DsHc1akhFitMX76XnIKrd+IQQoibYrFo3X4KsrTuPz2fVJ1I2CApcMU1JXR+miPWJtQ3ZDI/7A8aeLuqjiRs3CsjbqGhjyvxqbl8vvmM6jhCCHt0cIXW7cfJU+v+Y5Q1IeJKUuCKa3pv/VleLXwQgNDY5XDplOJEwtZ5uTjy/G2tAfh002kuyQYQQojqVJQP61/Xxn3+rnX/EeIqpMAVV3U0MYPv9pxju6UtGY36Y7AUwfp/qY4ldOBv7RvQvqE3WflFfLT+6puvCCHEDdnxOaTFgWcDiJimOo2wYVLgiqt6e9UxrFYY1r4BXn/7f4ABDn0HCbtVRxM2zmg08ELxVdwl0WeJu5SjOJEQwi7kpcOm/2jj/jPByU1tHmHTpMAVV9h++hLrjyZjMhq0DR2C2kHHMdqDa1/Weg8KUYFezf3o08KPQrOVd9ccUx1HCGEPtnwIuang1xLCx6pOI2ycFLiiHKvVypu/HQXgvu4hNPVz1x649f/A5ARnNsGpdRWcQQjN80O1q7g/7j3PwYR0xWmEELqWcQG2zdLGA18Gk4PaPMLmSYEryll1MJG98Wm4OZl4cmCLsgd8GmvbIAKseUVr0yJEBdo19GZEeDAAb606qjiNEELXNr4JRbkQEgGth6lOI3RAClxRqtBs4T+/ax8nP9wnjABPl/IH9HkanL0h6YDWpkWISjwzuBWOJgObT1xk84kU1XGEEHqUchx2f6mNo14Fg/RjF5WTAleU+npnPKcvZlPf3YnJfa6yY5mbL/Sero3Xv661axGiAiG+bjzQowmgXcW1WGT+thDiOq1/DaxmaHU7NIlUnUbohBS4AoCcgiI+WHsCgCcGNMfTxfHqB0ZM1dqzpMVp7VqEqMTjtzbHw9mBgwkZ/Lz/vOo4Qgg9iY+BIz+DwQgDX1KdRuiIFLgCgM83nyElM5/Gvm7cH9Hk2gc6uWntWUBr15Ini4dExep7OPNI3zAA3ll9jIIimb8thKgCqxXWvKyNw++HgDZq8whdkQJXcCkrn083nQbgmSGtcHKo5K9F+FitTUtuqta2RYhKTOrTFH9PZ+JTc/kq+qzqOEIIPTj+O8RtBQcX6P9/qtMInZECV/DxHyfJyi+iXUMv/ta+QeVPMDlA1CvaeNssyEys0XxC/9ycHJgepXXl+HD9STLzChUnEkLYNIsZ1r6ijSOmgndDpXGE/kiBW8fFXcph8XbtitoLQ9tgNFZxdWqr27V2LUW5sOGNGkwo7MW9XUMI83MnNbuAucWfGAghxFXtWwopR8DFp2xxsxDXQQrcOu7dNccoNFvp08KP3i38qv5Eg0Fr1wJa+5aU4zUTUNgNR5ORZ4e0AmDu5jMkZ+YpTiSEsEmFufDHv7Vxn6fBtZ7aPEKXpMCtww4mpPPjXm1Ve8muU9elSaR2Jddq1tq4CFGJoe2CCA/xIbfQzIfrTqiOI4SwRTGfQUYCeDUq22BIiOskBW4dVrK71IjwYNo19L6xkwx8WWvfcuRniN9RjemEPTIYDLxwm/bD1NKYeE6nZClOJISwKbmXYfO72njAP8DRpeLjhbgGKXDrqD9PXGTziYs4mgw8PajVjZ8ooLXWVQFgzUtaWxchKtAjrD4DWgdgtlh5d7VMbRFC/MWf72vtJwPaQofRqtMIHZMCtw6yWKy8ueoIAGMjmtC4vtvNnbD/TK2NS9xWra2LEJV4bmgrDAb45cAF9sanqY4jhLAF6edg+xxtHPUKGE1K4wh9kwK3Dlp54AIHEzLwcHbgiQHNb/6E3g21Ni6gtXWxmG/+nMKutQ7yYlTnRgC88esRrHLlXwjxxxtgzocmvaHFYNVphM5JgVvHFBRZeOf3YwA80jeM+h7O1XPi3tO1di4pR2Dfsuo5p7Brfx/UEicHI9FnUtlwPEV1HCGESkmHYd9X2njQq1qnHiFughS4dczSmDjiUnPw83BmUp+m1Xdi13rQ9xlt/Mf/09q8CFGBhj6uTOgZCsBbvx3FbJGruELUWeteA6sF2gyHRl1VpxF2QArcOiQzr7C0NdP0qBa4OTlU7wt0m6y1dclI0Nq8CFGJR/s3w8vFgaOJmfywJ0F1HCGECme3wvHfwGCCgS+pTiPshBS4dcjczWe4lF1AmJ87o7uFVP8LOLpobV1Aa/OSe7n6X0PYFR83Jx69VZsH/t6a4+QVyvxtIeoUq1XrwAPQZTz4tVCbR9gNKXDriOTMPOZt1rZHfXZIKxxNNfRH32G01t4lL11r9yJEJSb0DCXIy4WEtNzSbaOFEHXE0ZVwbgc4ukG/51WnEXZECtw64qN1J8kpMNMxxIeh7YJq7oWMJq29C2jtXtLP1dxrCbvg4mhixqCWAHz8x0nScwsVJxJC1ApzEawt3vI98jHwrMHvTaLOkQK3DjhzMZulMXEAzLytNYaaXp3aYrDW5sWcr7V9EaISd3VuSIsAD9JyCpmz8ZTqOEKI2rDnS7h0AtzqQ88nVacRdkYK3Drgnd+PUWSxMqB1AD3C6tf8CxoMWpsX0Nq+JB2u+dcUuuZgMvL8UG0L3/l/niExPU9xIiFEjSrIhg1vauO+z4GLl9o8wu5IgWvn9san8cuBCxgM2u5RtaZRV63di9WitX8RohID2wTQLbQe+UUWPlgrW/gKYde2z4asRPBpAl0nqk4j7JAUuHbMarXy5m/alrx3dWpE66Ba/gl54Eta25fjv2ltYISogMFg4IXbtKu4X++M52RypuJEQogakX0JtvxXGw/4JzhU04ZDQvyFFLh2bMPxFLafTsXJwciMwS1rP4BfC63tC2htYGQ7VlGJLk18Gdw2EIsV3lp1THUcIURN2PwO5GdAUHtoN0p1GmGnpMC1U2aLlbd+OwrA+MgmNPRxVROk3/Na+5dzO7R2MEJU4rmhrTAaYM3hJHbGpqqOI4SoTpdjIWauNo56FYxShoiaIX+z7NSPexM4mpiJp4sDjxU30lfCM0hr/wJaOxhzkbosQheaB3iWbkTy5m9HscqVfyHsxx//BkshhPWH5gNVpxF2TApcO5RXaObd1doinUf7N8fHzUltoJ5Pgquv1g5m72K1WYQuPDWwJS6ORnaevczaI8mq4wghqsOF/bD/a21c0i9diBoiBa4dWrz9LAlpuQR5uTCxV6jqOFr7l37PaeM/3tDawwhRgSBvFx7q1RSAt1YdpchsUZxICHHT1r4CWLV5t8GdVKcRdk4KXDuTnlvIx3+cBODvg1rg4mhSnKhY14e0djBZiVp7GCEq8Ui/Zvi4OXIyOYtvd8uOeELo2ukNcGodGB1hwIuq04g6QApcO/PpxlOk5RTSIsCDUZ0bqY5TxsFZawcDWnuY7Etq8wib5+3qyOPF88ffX3OC3AKz4kRCiBtiscCal7Vx14fAN0xtHlEnSIFrRxLT85i/5QwAzw1tjYPJxv54243S2sLkZ8Dmd1WnETrwYHEHkMSMPBZujVUdRwhxIw7/ABf2gpMH9H1WdRpRR9hYBSRuxn/XHSev0ELXJvWIahOgOs6VjEatLQzAjrlw+azaPMLmOTuYeLq4h/MnG06SllOgOJEQ4rqYC8t2s+z5JHj4q80j6gwpcO3EyeRMlu+IB2Dm7a0xGAyKE11D84FaexhzAfzx/1SnETowIrwhrYM8ycwrYlbx/HIhhE7sWgiXz4B7QFnLSCFqQa0UuLNmzSI0NBQXFxciIiKIiYm55rELFy7EYDCUu7m4uJQ7xmq18tJLL9GgQQNcXV2JiorixIkTNf02bNrbq45hscLgtoF0aeKrOk7FStrD7P9aaxsjRAVMxrItfBdtPcu5yzmKEwkhqiQ/Eza+pY37Pw/OHmrziDqlxgvc5cuXM2PGDF5++WV2795Nx44dGTJkCMnJ1+5t6eXlxYULF0pvZ8+W/yj77bff5sMPP2TOnDlER0fj7u7OkCFDyMvLq+m3Y5N2nU1l9eEkjAZtFyibF9ypeHtGK6x7VXUaoQP9WvoTGVafArOF99fU7R9mhdCNbbMgO0VbVNZ5vOo0oo6p8QL3vffeY/LkyUycOJG2bdsyZ84c3NzcmD9//jWfYzAYCAoKKr0FBgaWPma1Wvnggw948cUXGTFiBB06dOCLL77g/Pnz/PDDDzX9dmyO1WrlzeItee/tGkLzAE/FiapowItgdICTa+H0RtVphI0zGMqu4n635xxHEzMUJxJCVCgrGbZ+pI0HvgQmR7V5RJ1TowVuQUEBu3btIioqquwFjUaioqLYtm3bNZ+XlZVFkyZNCAkJYcSIERw6dKj0sTNnzpCYmFjunN7e3kRERFzznPn5+WRkZJS72YuNx1PYEXsZF0cj06Naqo5Tdb5hWrsYgPWvg2zHKirRMcSHYe0bYLVSulOfEMJG/fkBFGRBcGdoO1J1GlEH1WiBe/HiRcxmc7krsACBgYEkJiZe9TmtWrVi/vz5/PjjjyxevBiLxULPnj05d05r9F7yvOs55xtvvIG3t3fpLSQk5Gbfms2YveEUAA9ENCHI26WSo21M32fB5AzndsDZrarTCB34+6CWGAyw5nASJ5MzVccRQlxNTqq2uAxgwD/AVhc9C7tmc10UIiMjGTduHOHh4fTr14/vvvsOf39/Pv300xs+58yZM0lPTy+9xcfHV2NidfbEXSb6TCqOJgOT+jRVHef6eQRA+P3aeMt/1WYRutA8wINBbbQfbj/bdFpxGiHEVe34HAqztb7nzQaqTiPqqBotcP38/DCZTCQlJZW7PykpiaCgoCqdw9HRkU6dOnHypNYeqOR513NOZ2dnvLy8yt3swacbtW/wI8Ib0sDbVXGaG9TzCcAAJ36HpMOq0wgdmNq/GQDf70kgMb1uLiwVwmYV5kL0HG3ca7pcvRXK1GiB6+TkRJcuXVi3bl3pfRaLhXXr1hEZGVmlc5jNZg4cOECDBg0AaNq0KUFBQeXOmZGRQXR0dJXPaQ9OpWTx+2FtSsYjfXW87WH9ZtB2uDaWq7iiCjo3rkf3UF8KzdbSnfuEEDZiz2LIuQg+jWXurVCqxqcozJgxg7lz57Jo0SKOHDnCtGnTyM7OZuLEiQCMGzeOmTNnlh7/2muvsXr1ak6fPs3u3bt54IEHOHv2LA8//DCgraaePn06//rXv/jpp584cOAA48aNIzg4mJEjR9b027EZczedxmqFqDYBtAjUSeeEa+k1Xft6cAWk2cf0EVGzpvbXfqj7KjqO9NxCxWmEEACYi8o6J0Q+ASYHtXlEnVbjf/tGjx5NSkoKL730EomJiYSHh7Nq1arSRWJxcXEYjWV19uXLl5k8eTKJiYnUq1ePLl26sHXrVtq2bVt6zHPPPUd2djZTpkwhLS2N3r17s2rVqis2hLBXyRl5fLc7AYCp/ZopTlMNGnaGpn3hzCbY/gkMfUN1ImHjbm0VQKtAT44lZbIk+iyP9m+uOpIQ4siPkHYWXH2h0wOq04g6zmC11r3+TBkZGXh7e5Oenq7L+bhv/naUORtP0aVJPb6d1lN1nOpxch0svgsc3eHvB8HNxndjE8p9u+scT3+zDz8PZ/58/lZcHE2qIwlRd1mt8GlfSNwP/WdC/xdUJxJ24GbqNZvroiAqlpFXyJLt2s5udnH1tkSzAdqK28Js2DFPdRqhA8PDgwn2duFiVn7pJxpCCEVO/6EVt45u0H2K6jRCSIGrN0uj48jML6JFgAcDWweojlN9DIayubjRc7SVuEJUwNFkZFIfbS7u3M2nMVvq3IdRQtiOkkXCncfJJ3DCJkiBqyP5RWY+/1NbNT6lbxhGo521X2k7Ult5m3NJW4krRCXGdAvB29WRMxezWX3o6hu9CCFq2Pk9cHoDGEzQ41HVaYQApMDVlR/2JJCcmU+QlwsjwhuqjlP9TA7aylvQVuKai9TmETbP3dmBcZFNAJiz8RR1cEmBEOqVXL1tNwrqNVGbRYhiUuDqhMVi5dPinZsm9W6Kk4Od/tF1egDc6msrcY/8qDqN0IHxPUNxdjCy71w620+nqo4jRN2SehoOF/9f3esptVmE+As7rZLsz5ojSZxOycbTxYH7IhqrjlNznNyg+yPa+M8PtJW5QlTAz8OZe7uGANpVXCFELdr6MVgt0HwQBLVTnUaIUlLg6oDVai39xv1gjyZ4ONt58+zuk7WVuIn7tZW5QlRicp8wjAbYeDyFw+czVMcRom7ISoG9S7SxXL0VNkYKXB2IOZPKnrg0nByMTOzVVHWcmufmq63EBe0qrhCVaFzfjdvba9t5f7pJruIKUSui50BRHjTsAqG9VacRohwpcHWgZO7t3V0a4e/prDhNLYl8TFuRe2ajtkJXiEqU9IVeuf8C8ak5itMIYefys2DHXG3ca7rW6lEIGyIFro07lpjJ+qPJGAzax7B1hk9jaH+3Ni5ZoStEBdo19KZ3cz/MFmtpOz0hRA3ZvQjy0sG3GbQepjqNEFeQAtfGfVo89/a2dkE09XNXnKaW9XxS+3r4R22lrhCVKLmKu2xHHKnZBYrTCGGnigpg2yxt3OtJMMo22cL2SIFrwxLScvlp33nAzrblraqgdtrKXKtFW6krRCV6Na9Pu4Ze5BVa+GJbrOo4Qting99CRgJ4BEKHMarTCHFVUuDasM83n6HIYqVns/p0aOSjOo4avadrX/cu0VbsClEBg8HAI321HwYXbY0lp0A2CxGiWlksZdPGIqaCo4vaPEJcgxS4Niotp4BlO+IAeKQuXr0t0aQXNOyqrdSNnqM6jdCB29oF0djXjcs5hXy9I151HCHsy4nVkHIEnDyh60Oq0whxTVLg2qgvtp0lp8BM2wZe9G3hpzqOOgZDWX/FHXO1lbtCVMDBZGRyX21B5tzNZygyWxQnEsKOlFy97ToRXH2URhGiIlLg2qC8QjMLt8YC8Ei/MAx1vf1K62FQv7m2Ynf3ItVphA7c06UR9d2dSEjL5ZcDF1THEcI+xMdA3FYwOkKPR1WnEaJCUuDaoG92xpOaXUCjeq4MK25eX6cZTWUdFbbN0lbwClEBF0cTE3qGAjBn42mssuWzEDevZOOdjqPBS743CdsmBa6NKTJb+Gyz1hJrcp8wHEzyRwRAh9Hait2MBDi4QnUaoQMPRjbBzcnEkQsZbDwuCxSFuCkpx+DYL4ABesq2vML2SfVkY347mEh8ai713By5t2uI6ji2w9EFekzTxls+1FbyClEBHzcn7uveGIBPN0ofZSFuytYPta+th4F/S7VZhKgCKXBtiNVqZU7xxg7je4bi6iTNs8vp+pC2cjfliLaSV4hKTOrdFAejgW2nL7EvPk11HCH0KeM87FuujXvJ1VuhD1Lg2pA/T17k0PkMXB1NjI8MVR3H9rh4ayt3AbZ8oDSK0IdgH1eGhwcDlP7wKIS4Tts/AUshNO4JId1VpxGiSqTAtSElH6OO7hZCPXcnxWlsVI9HweQEcdsgLlp1GqEDJRs/rDqUyJmL2YrTCKEzuWmwc6E2Ltl4RwgdkALXRhw4l86fJy9iMhp4uE9T1XFsl1cDbcEZlPVjFKICrYI8GdA6AKsVPtskc3GFuC4750NBJvi30bZOF0InpMC1EXM2aR+f3tGhAY3quSlOY+N6PQUYtBW9KcdUpxE6MLV4N8Bvd58jOTNPcRohdKIwD7bP1sa9ngKjlAxCP+Rvqw04eymb34qb0dfpbXmryq+FtpIXylb2ClGBbqH16NzYh4IiCwu3xKqOI4Q+7F8G2cng1Qja3606jRDXRQpcGzB382ksVujfyp82DbxUx9GHXtO1r/uWayt8haiAwWAo/eHxy+1nycwrVJxICBtnMWstGQEiHwWTo9o8QlwnKXAVu5iVzzc7zwFli2FEFYR0gya9tJW92z9RnUbowKA2gTTzdyczr4ilMXGq4whh246uhNRT4OIDncerTiPEdZMCV7GFW2LJL7LQMcSHHmG+quPoS0k/xp0LtZW+QlTAaDSU/hD5+Z9nyC8yK04khI2yWsu25e0+GZw9lMYR4kZIgatQdn4RX2yLBWBavzAMBoPaQHrTYjAEtNVW+O6crzqN0IERnYIJ9HImKSOfH/fK1BYhrir2Tzi/GxxcoPsjqtMIcUOkwFVoaUwcGXlFNPVzZ1DbINVx9MdgKLuKu322tuJXiAo4O5h4qJfWhu/TjaewWKyKEwlhg0o20gkfCx7+SqMIcaOkwFWkoMjC53+eAWBK3zBMRrl6e0PajdJW+GYnw76lqtMIHbg/ojGeLg6cSslm7ZEk1XGEsC2JB+DkWjAYoecTqtMIccOkwFXk533nuZCeh7+nM3d2aqg6jn6ZHCHyMW289SNt5a8QFfB0ceSBHk0A+FQ2fhCivJLOCW1Hgq9sOiT0SwpcBSwWK58Wb+zwUK+muDiaFCfSuc7jtJW+qae0lb9CVGJiz1CcTEZ2nb3MjthU1XGEsA2Xz8LBb7VxyfQvIXRKClwF/jiWzPGkLDycHbg/orHqOPrn7AHdp2jjPz/QVgALUYEALxdGddE+OZmz4ZTiNELYiG2zwGqGsP4QHK46jRA3RQpcBeZs1L6hjo1ojLerNM+uFt2naCt+z+/WVgALUYnJfcIwGGDd0WSOJ2WqjiOEWtmXYPcX2rhkIx0hdEwK3Fq262wqO2Iv42gy8FBvmd9UbTz8odMD2rhkBbAQFQjz92BIcfeSTzfKXFxRx+2YC0W5ENRBu4IrhM5JgVvL5hR/I72zU0MCvVwUp7EzkY9rK39PrtVWAgtRian9tY0fftybwPm0XMVphFCkIBuiP9XGvadrLRiF0DkpcGvRyeRM1hxOwmCAKbItb/XzbQq33KmNS1YCC1GB8OIdBIssVuYXt+0Tos7ZswRyU6FeKLQZoTqNENVCCtxa9FlxS6JBbQJpHiBbH9aIkpW/B7/VVgQLUYlH+mk/bC6NiSM9p1BxGiFqmbkItn2kjSMfB5OD2jxCVBMpcGtJYnoe3+9JAMo+FhU1oEFHCLtVWwm8bZbqNEIH+rf0p3WQJ9kFZr7cHqs6jhC169D3kBYHbn5l6xiEsANS4NaS+VvOUGi20j3Ul86N66mOY996T9e+7v5CWxksRAUMBgNTi6/iLtgSS16hbBYi6girFbb8VxtHTAVHV7V5hKhGtVLgzpo1i9DQUFxcXIiIiCAmJuaax86dO5c+ffpQr1496tWrR1RU1BXHT5gwAYPBUO42dOjQmn4bNyw9t5CvouMAmNo/THGaOqBpP+1KblGutjJYiEoM69CAhj6uXMouYMWuc6rjCFE7Tq2DpAPg6A7dJqlOI0S1qvECd/ny5cyYMYOXX36Z3bt307FjR4YMGUJycvJVj9+wYQP33Xcff/zxB9u2bSMkJITBgweTkJBQ7rihQ4dy4cKF0tvSpUtr+q3csCXRZ8nKL6JVoCe3tgpQHcf+GQxlfRyjP9VWCAtRAUeTkYf7aG375m4+jdkim4WIOuDPD7SvXcaDm6/SKML2WSxW7p2zjXd+P0Z6ru2vV6jxAve9995j8uTJTJw4kbZt2zJnzhzc3NyYP3/+VY9fsmQJjz76KOHh4bRu3Zp58+ZhsVhYt25dueOcnZ0JCgoqvdWrZ5sf+xeZLSzcEgvAlL5hGKT9Su1oOwLqNdVWBu9bpjqN0IHR3ULwcXPk7KUc1hxOUh1HiJp1YR/EbgajA/R4VHUaoQObTqQQE5vKwq2xmIy2X8vUaIFbUFDArl27iIqKKntBo5GoqCi2bdtWpXPk5ORQWFiIr2/5ny43bNhAQEAArVq1Ytq0aVy6dO25lvn5+WRkZJS71RYHk5HFD0cwsVcow8ODa+116zyjSZtTBtpVXNm+V1TCzcmB+7trW2cv2CItw4SdK+l723YE+ISozSJ0YeHWWADu6doID2fb77ZRowXuxYsXMZvNBAYGlrs/MDCQxMTEKp3j+eefJzg4uFyRPHToUL744gvWrVvHW2+9xcaNG7ntttswm6++OOSNN97A29u79BYSUrv/mFsGevLyHbfgaJI1fbUq/H5w8oSLx+D0H6rTCB14MLIJJqOB6DOpHD5fez8IC1GrslLgwDfaOGKa2ixCF06lZLHhWAoGA4yPDFUdp0psuuJ68803WbZsGd9//z0uLmW7fo0ZM4bhw4fTvn17Ro4cycqVK9mxYwcbNmy46nlmzpxJenp66S0+Pr6W3oFQysULOo3VxtvnqM0idKGBtytD22nb9y7cKldxhZ3atRDMBRDcGRp1VZ1G6MCi4qu3A1oFEOrnrjZMFdVogevn54fJZCIpqfx8tqSkJIKCgip87jvvvMObb77J6tWr6dChQ4XHhoWF4efnx8mTJ6/6uLOzM15eXuVuoo7oPgUwwInf4dIp1WmEDjzUKxSAH/ae51JWvtowQlS3ogLYMU8b95gm2/KKSmXkFZZ2l5nYq6niNFVXowWuk5MTXbp0KbdArGTBWGRk5DWf9/bbb/P666+zatUqunat/KfLc+fOcenSJRo0aFAtuYUdqd8MWgzWxjGfqc0idKFz43q0b+hNQZGFZTvk0x5hZ478BFmJ4BEIbUeqTiN04Osd8eQUmGkR4EGv5vVVx6myGp+iMGPGDObOncuiRYs4cuQI06ZNIzs7m4kTJwIwbtw4Zs6cWXr8W2+9xT//+U/mz59PaGgoiYmJJCYmkpWVBUBWVhbPPvss27dvJzY2lnXr1jFixAiaN2/OkCFDavrtCD3qUbzYbM8SyJN5laJiBoOBicVXcb/cdpZCs0VtICGq0/bZ2teuk8DBSW0WYfPMFitfbNO2vZ/QK1RXnaBqvMAdPXo077zzDi+99BLh4eHs3buXVatWlS48i4uL48KFC6XHz549m4KCAu6++24aNGhQenvnnXcAMJlM7N+/n+HDh9OyZUsmTZpEly5d2Lx5M87OzjX9doQehd0Kfq2gIBP2LlGdRujAsA4N8PNwJjEjj98OVm1BrBA279xOSNgJJifoOlF1GqED648mE5eag7erI3d2aqg6znUxWK11r39SRkYG3t7epKeny3zcumLH5/DLDK037hO7wWjT6yuFDXh/zXH+u+4EnRv78N2jvVTHEeLmffuw1j2h431wpyy8FZW7f+52tp66xCN9w5h5e5taf/2bqdfku7yoGzqOARdvuHwGTqxWnUbowNgejXE0Gdgdl8a++DTVcYS4ORkX4ND32rikR7gQFTiWmMnWU5cwGrQWinojBa6oG5zcofM4bRwtVy5E5QI8Xbijg7Y5S0mDcyF0a+d8sBRB40gIDledRuhASavEIbcE0aiem+I0108KXFF3dJ8CBqO26UPyUdVphA5MKF5stnL/eZIz8tSGEeJGFeZpBS5AxCNqswhduJxdwHe7EwCY0DNUbZgbJAWuqDt8GkPrYdpYruKKKujQyIcuTepRaLayODpOdRwhbsyh7yDnIng1hNZ3qE4jdGDZjnjyiyy0beBF96a+quPcEClwRd1SMvds3zLIvaw2i9CFkqsXX0WfJb/o6tuBC2GzrNay1mDdHgaTg9o8wuYVmS18uS0WgIk6aw32V1LgirqlSS8IbA9FubD7C9VphA4MbRdEkJcLF7MKWLnvQuVPEMKWxG2DxP3g4ApdJqhOI3Rg9eEkzqfnUd/diTs6BquOc8OkwBV1i8FQNgctZi6Yi9TmETbP0WQsXUG8YOsZ6mBnRaFnJdOxOtwLbvr8qFnUrgVbtMVl90c0xsXRpDjNjZMCV9Q97e8Bt/qQHg/HflWdRujAfd0b4+xg5GBCBrvOytQWoRNp8XBkpTaWxWWiCg4mpLMj9jIORgMP9NBfa7C/kgJX1D2OLtCleBcfWWwmqsDX3YmR4douPgu2xKoNI0RV7ZgHVjM07QuBt6hOI3Sg5P+329s3INDLRW2YmyQFrqibuk0CowOc3QIX9qtOI3SgpGXYqkOJnE/LVRtGiMoU5MCuhdo4YprSKEIfUjLz+XnfeUBbXKZ3UuCKuskrGNqO0MbRn6rNInShTQMveoT5YrZY+XL7WdVxhKjY/uWQlwY+TaDlENVphA4sjYmjwGyhY4gPnRrXUx3npkmBK+qukpZhB76B7ItqswhdmNirKaB9I8gtkJZhwkZZrWU/uEc8Akb9LhQStaOgyFL6g/tDdnD1FqTAFXVZo24Q3BnM+bBrgeo0Qgei2gTSqJ4raTmF/Lg3QXUcIa7uzEZIOQKO7tDpAdVphA78euACKZn5BHg6c1u7BqrjVAspcEXdZTBAj+K5aTs+B3Oh2jzC5pmMBsZHhgLaYgxpGSZs0vbixbPh94OLt9osQhcWbI0F4IEeTXBysI/S0D7ehRA3qu1I8AiEzAtw+EfVaYQO3NstBFdHE8eSMtl26pLqOEKUl3oajq/SxtIaTFTB7rjL7ItPw8lk5P6IxqrjVBspcEXd5uAEXSdpY2kZJqrA29WRUV2KW4YVX/UQwmbEzAWs0DwK/FqoTiN0oKQ12B0dg/HzcFYbphpJgStE14lgcoJzO+DcLtVphA5M6KktNlt7JIm4SzmK0whRLD8T9izWxtIaTFRBYnoevx3QtiC3h9ZgfyUFrhAeAdBulDaWq7iiCpoHeNC3pT9WK3yxLVZ1HCE0e5dCfgbUbwHNBqhOI3Rg8fazFFmsdA/1pV1D+5qvLQWuEFA2V+3Q95CZqDaL0IWJPUMBWL4znuz8IrVhhLBYyn5Aj3gEjPLtXVQsr9DMVzFxQNlGNvZE/gUIARDcCUJ6gKVQ66ggRCX6tfQnzM+dzLwivt19TnUcUdedWgepp8DZGzrepzqN0IGf9p0nNbuAYG8XBrcNVB2n2kmBK0SJHsUbP+ycD0X5arMIm2c0GhhffBV34dZYLBZpGSYU2j5b+9r5QXD2UJtF2Dyr1Vq6uOzByFAcTPZXDtrfOxLiRrX+G3g1hJyLcPBb1WmEDozq0ghPZwdOp2Sz6USK6jiirko5rl3BxQDdHladRuhAzJlUjlzIwMXRyH3dQ1THqRFS4ApRwuRY9s1h+2xtu0shKuDh7MA9XbVvDiVXQ4SodTHF2/K2uh18m6rNInSh5P+rOzs1wsfNSW2YGiIFrhB/1WUCOLhA4n6I2646jdCB8T2bYDDAxuMpnErJUh1H1DW5aVr3BJCNHUSVnLucw+rD2mLqCcXTrOyRFLhC/JWbL3S4VxtHz1abRehCk/ruDGwdAMAi2fhB1LY9i6EwGwLaQtO+qtMIHfhy21ksVujVvD6tgjxVx6kxUuAK8b8iihebHVkJafFqswhdmNhL+1h4xa5zZOQVKk4j6gyLuWx6QsRUMBjU5hE2L6egiKUlrcF62vd0FilwhfhfgbdAaB+wmmHHPNVphA70bFafloEe5BSY+XqH/FAkasnxVZAWB671oP09qtMIHfh+TwIZeUU09nVjQPEnT/ZKClwhrqZH8TaXuxZCgWzFKipmMBhKr4Ys2haLWVqGidpQ0hqsywRwclMaRdg+q9XKwuLFZeN7hmIy2vcVfylwhbialkPBpwnkpcGBr1WnETpwZ6eGeLs6Ep+ay/qjyarjCHuXeBBiN4PBJK3BRJX8efIiJ5KzcHcycU/XRqrj1DgpcIW4GqMJuk/RxtvnSMswUSlXJxNjupe0DDujOI2weyVzb9vcAd72X6yIm1dy9fbuLo3wcnFUG6YWSIErxLV0egAc3SHlCJzZpDqN0IFxkaEYDbD11CWOJmaojiPsVfYl2F/8yVLJdCohKhB7MZv1x7RPlsbbcWuwv5ICV4hrcfWB8OI93aPnKI0i9KGhjytDbgkCpGWYqEG7F0FRHjToCCERqtMIHVi0LRarFfq38ifMv25s5SwFrhAVKWkZduw3SD2tNovQhZKWYd/tTuBydoHiNMLumAvLurtETJPWYKJSmXmFfLPzHFD2/1NdIAWuEBXxawHNowArxEjLMFG5bqH1uCXYi/wiC8ukZZiobkd+howEcPeHdnepTiN0YMWuc2TlFxHm706f5n6q49QaKXCFqEzJVdw9X0J+ptoswuZpLcNCAfhyWyxFZovaQMK+RBcvLuv6EDg4q80ibJ7FYi2dLjWxZyhGO28N9ldS4ApRmWYDoX5zyM8o2/NdiArc0TGY+u5OnE/P4/dDSarjCHtxfg/EbwejI3SdpDqN0IENx5OJvZSDp4sDd3WuW902pMAVojJGI3R/RBvHfAoWuSInKubiaGJsRGMAFm6VlmGimmwvXuza7i7wDFSbRejCguLWYKO7huDu7KA2TC2TAleIqgi/D5y94NJJOLVOdRqhA2N7NMHBaGBH7GUOJqSrjiP0LjMJDn6rjSMeUZtF6MLJ5Ew2n7iIwVB3WoP9lRS4QlSFsyd0elAbS8swUQWBXi4M69AAgPmy8YO4WbsWgKUQGnWHhl1UpxE6UHL1NqpNICG+dW8rZylwhaiq7pMBA5xcCynHVacROlCy2GzlvgukZOarDSP0q6gAdnyujeXqraiC9JxCvtudAMDEXqFqwygiBa4QVeXbFFrdpo1LtskUogKdGtcjPMSHArOFr6LjVMcRenXoe8hOBs9gaDtCdRqhA8t3xpFbaKZ1kCeRYfVVx1FCClwhrkfJ1ZO9SyE3TWkUoQ8lV08WR5+loEgWKIrrZLVC9Gxt3G0SmBzV5hE2r8hsYdHWs4D2KZKhjm4GUisF7qxZswgNDcXFxYWIiAhiYmIqPP6bb76hdevWuLi40L59e3799ddyj1utVl566SUaNGiAq6srUVFRnDhxoibfghCapv0goC0UZsOexarTCB24rV0DAjydScnM59cDF1THEXpzbofWHszkDF0mqE4jdGDtkWQS0nKp5+bIyE4NVcdRpsYL3OXLlzNjxgxefvlldu/eTceOHRkyZAjJyclXPX7r1q3cd999TJo0iT179jBy5EhGjhzJwYMHS495++23+fDDD5kzZw7R0dG4u7szZMgQ8vLyavrtiLrOYCi7ihvzKVjMavMIm+fkYOTBHk0AWLDlDFarVXEioSvbi6/edrgH3OvOLlTixi0oXtR6X/fGuDiaFKdRx2Ct4f9tIyIi6NatGx9//DEAFouFkJAQnnjiCV544YUrjh89ejTZ2dmsXLmy9L4ePXoQHh7OnDlzsFqtBAcH8/TTT/PMM88AkJ6eTmBgIAsXLmTMmDGVZsrIyMDb25v09HS8vLyq6Z2KOqMgB95vC7mXYcxX0HqY6kTCxl3KyifyzfUUFFn47tGedG5cT3UkoQfpCfBBe7CaYeqfENRedSJh4w6fz+D2DzdjMhrY/NytBPu4qo50U26mXqvRK7gFBQXs2rWLqKioshc0GomKimLbtm1Xfc62bdvKHQ8wZMiQ0uPPnDlDYmJiuWO8vb2JiIi45jnz8/PJyMgodxPihjm5Qefx2rjk6ooQFajv4czwjsFAWeseISq183OtuG3SW4pbUSUlG8sMbRek++L2ZtVogXvx4kXMZjOBgeV3XAkMDCQxMfGqz0lMTKzw+JKv13PON954A29v79JbSEjIDb0fIUp1exgMJojdDEmHVKcROlCy2Oy3AxdITJfpVKIShbmwc4E2ltZgogouZeXzw97zAEysgxs7/K860UVh5syZpKenl97i4+NVRxJ65xMCbf6mjWXjB1EFtwR70z3UlyKLlcXbz6qOI2zdgRWQmwrejWUalKiSZTviKSiy0L6hN12ayDSoGi1w/fz8MJlMJCUllbs/KSmJoKCgqz4nKCiowuNLvl7POZ2dnfHy8ip3E+KmRUzTvu7/GrIvqc0idKHkKu5XMXHkFcoCRXENVmvZD87dJ4Ox7i4UElVTaLbw5TbtB+eJvepua7C/qtEC18nJiS5durBu3brS+ywWC+vWrSMyMvKqz4mMjCx3PMCaNWtKj2/atClBQUHljsnIyCA6Ovqa5xSiRjTuAUEdoCgPdi9SnUbowKC2gTT0cSU1u4Cf9p1XHUfYqrNbIOkgOLpB5wdVpxE6sOpgIokZefh5OJduEV7X1fgUhRkzZjB37lwWLVrEkSNHmDZtGtnZ2UycOBGAcePGMXPmzNLjn3rqKVatWsW7777L0aNHeeWVV9i5cyePP/44AAaDgenTp/Ovf/2Ln376iQMHDjBu3DiCg4MZOXJkTb8dIcoYDNCj+CrujnlgLlSbR9g8B5ORByNLWobFSsswcXUli1c7jgFX+ahZVK6kNdjYiMY4O8gVf6iFAnf06NG88847vPTSS4SHh7N3715WrVpVukgsLi6OCxfKmp/37NmTr776is8++4yOHTuyYsUKfvjhB9q1a1d6zHPPPccTTzzBlClT6NatG1lZWaxatQoXF5eafjtClNduFLj7Q0YCHPlZdRqhA2O6heDiaOTIhQyiz6SqjiNszeWzcKx4c6PusrhMVG5ffBq749JwNBkY26Ox6jg2o8b74Noi6YMrqtX6/web3oaQHjDpd9VphA7M/O4AS2PiGHpLEHMe7KI6jrAlq1+ErR9B2K0w7gfVaYQO/H35Xr7fk8CdnRry/uhw1XGqlc32wRWiTug2CYwOEL9d21JTiEqULDZbfTiR+NQctWGE7SjIht1faOOS6U9CVCA5I4+V+7X5/BOkNVg5UuAKcbM8g+CWO7Vx9KdqswhdaBnoSe/mflisSMswUWbfUshLB98waD5IdRqhA0ui4yg0W+nc2IeOIT6q49gUKXCFqA4lLcMOfgtZyWqzCF0oudqyNCaOnIIitWGEelZr2Q/I3R8Bo3x7FhXLLzKzJLqkNVhTxWlsj/wLEqI6NOoCjbqBuQB2zledRujAgNYBNKnvRkZeEd/tTlAdR6h2aj1cPA5OnhB+v+o0QgdW7rvAxawCgrxcGNru6vsA1GVS4ApRXSKmal93fA5FBWqzCJtnNBoYFxkKwMKt0jKsziu5ettpLLjI4mdRMavVysKtsQA8GNkER5OUc/9LfkeEqC5tR4BnA8hOhkPfq04jdOCero1wdzJxMjmLP09eVB1HqHLpFJz4HTBA9ymq0wgd2HX2MgcS0nFyMHJfd2kNdjVS4ApRXUyOWkcFgOjZ2pw6ISrg5eLIPV1DAFi4JVZtGKFOydXblkOgfjO1WYQuLCi+ejsyPBhfdye1YWyUFLhCVKcuE8HkrLULO7dDdRqhA+OKdzZbfyyZ2IvZitOIWpeXAXuXaOMI2dhBVO58Wi6rDiYCMKGnLC67FilwhahO7n7Q/h5tXLLdphAVCPP34NZW/litlM6pE3XI3iVQkAV+rbTNHYSoxJfbz2K2WIlo6kvbYJmvfS1S4ApR3Uquwhz+EdJldbyo3ITiFj8rdp0jM69QcRpRayyWsukJEY+AwaA2j7B5eYVmlsbEAdIarDJS4ApR3Rp0gCa9wGqGnZ+rTiN0oG8LP5r5u5OVX8SKXedUxxG15cRquHwGXLyh4xjVaYQO/LAngbScQhr6uDKobaDqODZNClwhakJJy7CdC6AwV20WYfMMBkPpVdxFW2OxWGSBYp0QXTyNqfN4cHJXm0XYvL+2Bhvfswkmo1zxr4gUuELUhFa3g3cI5KbCgRWq0wgduKtTQzxdHIi9lMOG47Ibnt1LPgqnN4DBCN0nq04jdGDb6UscTczE1dHE6K7SGqwyUuAKURNMDmXftKLnSMswUSl3ZwfGdNNahi2QlmH2L3qO9rX1MPCRYkVUruT/hVFdGuLt5qg2jA5IgStETek8DhzdIOkgxP6pOo3QgXGRoRgNsPnERU4kZaqOI2pKTirsW6aNS6YzCVGB+NQc1h5JAmBCz1C1YXRCClwhaoprPegwWhuXXK0RogIhvm5EtdEWjkjLMDu250soyoXA9tqCVCEqsWhrLFYr9GnhR/MAT9VxdEEKXCFqUsnVmWO/wuWzarMIXShp/fPd7gTSc6RlmN0xF0HMXG3cY6q0BhOVys4vYvnOeAAm9gpVG0ZHpMAVoiYFtIaw/mC1wI65qtMIHegR5kvrIE9yC80s3xmnOo6obsd+hfR4cKsP7e5WnUbowHe7z5GZV0RTP3f6twxQHUc3pMAVoqZFTNO+7v4CCmQrVlExg8FQepVm0dazFJktagOJ6lUyXanLRHB0UZtF2DyLxcqCktZgkU0wSmuwKpMCV4ia1mIw1GsKeemwb6nqNEIHRoQ3pJ6bIwlpuaw9Ii3D7MaF/XB2CxgdoNsk1WmEDmw+eZHTKdl4ODswqksj1XF0RQpcIWqa0Vi2fW/0p9IyTFTKxdHEfd211lELtpxRnEZUm5JteduOAK9gtVmELpT8+7+nayM8XaQ12PWQAleI2hA+Fpw84eJxOLVedRqhAw9GajsVRZ9J5fD5DNVxxM3KvggHvtHGJdOWhKjA6ZQsNhxLwWCA8ZGhquPojhS4QtQGFy/oNFYbl1zFEaICDbxdGdouCICFW+Uqru7tXADmfAjuDI26qk4jdGBR8dzbAa0CCPWTrZyvlxS4QtSW7lMAA5z4HS6dUp1G6MBDxYvNfth7nktZ+WrDiBtnLoQd87Rxj2nSGkxUKiOvkBW7zgFlrQPF9ZECV4jaUr+ZtuAM5CquqJLOjevRvqE3BUUWlu2IVx1H3KjDP0JWIngEQtuRqtMIHfhm5zmyC8y0CPCgV/P6quPokhS4QtSmksVme5dAnsyrFBX7a8uwL7edpVBahulTSWuwrpPAwUltFmHzzBZr6fSECb1CMcgV/xsiBa4QtanZAPBrBQVZWpErRCWGdWiAn4cziRl5rDqYqDqOuF7ndsG5HWBygq4TVacROvDH0WTiUnPwcnHgzk4NVcfRLSlwhahNBkP5lmEWs9o8wuY5O5gYGyEtw3Qrerb2td0o8JBdqETlFhQvKr2ve2PcnBwUp9EvKXCFqG0dx4CLN1w+AyfWqE4jdGBsj8Y4mgzsjktjX3ya6jiiqjIuwKHvtXHJD7ZCVOBYYiZbTl7CaNBaBYobJwWuELXNyR06j9PGJVd3hKhAgKcLf+ugbQywsHhuntCBnfPBUgQhPSC4k+o0QgdK/n0PbhtEo3puasPonBS4QqjQbTIYjHB6AyQfVZ1G6EDJYrOV+8+TnJGnNoyoXFG+VuAC9JiqNovQhbScAr7fU9IaLFRtGDsgBa4QKtRrAq1u18YlK6yFqECHRj50aVKPQrOVJdFxquOIyhz8FnIugldDaH2H6jRCB5btiCev0EKbBl50b+qrOo7uSYErhCo9irfr3LcMclLVZhG6MKFnKABLos+SXyQLFG2W1Qrbi6cfdXsYTLJQSFSsyGzhi+LpCROlNVi1kAJXCFWa9ILAdlCUC3u+VJ1G6MDQdkEEeblwMauAlfsuqI4jriVuOyTuBwcX6DJBdRqhA6sPJ3E+PQ9fdyeGdwxWHccuSIErhCoGA0QUz82LmQvmIrV5hM1zNBlLV1Yv3BqL1WpVnEhcVcni0Q73gpt81Cwqt3BLLAD3d2+Mi6NJbRg7IQWuECq1vwfc6kN6PBz7RXUaoQP3dW+Ms4ORAwnp7Dp7WXUc8b/S4uHISm0cIYvLROUOJqQTE5uKg9EgrcGqkRS4Qqjk+JePMKM/VRpF6IOvuxMjw7XdjRZIyzDbs2MeWM3QtC8E3qI6jdCBktZgt7dvQKCXi9owdkQKXCFU6/YwGB3g7Ba4sF91GqEDE4pbCK06mMj5tFy1YUSZghzYtVAby9VbUQUXs/L5ae95oOzftageUuAKoZpXMLQdoY3lKq6ogjYNvOgR5ovZYuXL7WdVxxElDnwNeWng0wRaDlWdRujAV9FxFJgtdAzxoXPjeqrj2BUpcIWwBSVXew58A9kX1WYRujChZ1MAlsbEkVcoLcOUs1phe3FP6+5TwCgLhUTFCoosLC7+AXVicQtAUX2kwBXCFjTqBsGdwZwPOxeoTiN0YFDbQBrVcyUtp5Af9iSojiPObISUI+DoDp0eUJ1G6MBvBy+QnJlPgKczt7dvoDqO3anRAjc1NZWxY8fi5eWFj48PkyZNIisrq8Ljn3jiCVq1aoWrqyuNGzfmySefJD09vdxxBoPhituyZctq8q0IUbP+2jJsxzwwF6rNI2yeyWhgfGQoIC3DbELJ9KLw+8HVR2kUoQ8LiluDPdCjCU4Ocr2xutXo7+jYsWM5dOgQa9asYeXKlWzatIkpU6Zc8/jz589z/vx53nnnHQ4ePMjChQtZtWoVkyZNuuLYBQsWcOHChdLbyJEja/CdCFELbrkTPAIhKxEO/6g6jdCBe7uG4Opo4mhiJttOX1Idp+5KPQ3HftPGEY+ozSJ0YU/cZfbGp+FkMnJf98aq49ilGitwjxw5wqpVq5g3bx4RERH07t2bjz76iGXLlnH+/PmrPqddu3Z8++233HHHHTRr1owBAwbw//7f/+Pnn3+mqKh8E3wfHx+CgoJKby4u0lpD6JyDE3Qt/mGuZJtPISrg7ebIqC7FLcOKrwYJBWLmAlZoHgV+LVSnETpQ8u/1jo7B+Hs6qw1jp2qswN22bRs+Pj507dq19L6oqCiMRiPR0dFVPk96ejpeXl44OJTfy/uxxx7Dz8+P7t27M3/+/Ao/nsvPzycjI6PcTQib1HUimJwgYSec26k6jdCBCcWLU9YeSSI+NUdtmLooPxP2LNbG0hpMVEFSRh6/HtC22p4orcFqTI0VuImJiQQEBJS7z8HBAV9fXxITE6t0josXL/L6669fMa3htdde4+uvv2bNmjWMGjWKRx99lI8++uia53njjTfw9vYuvYWEhFz/GxKiNngEQLtR2jh6jtosQheaB3jSp4UfVissko0fat/epZCfAfWbQ7OBqtMIHVi8/SxFFivdQuvRrqG36jh267oL3BdeeOGqi7z+ejt69OhNB8vIyGDYsGG0bduWV155pdxj//znP+nVqxedOnXi+eef57nnnuM///nPNc81c+ZM0tPTS2/x8fE3nU+IGlMyh+/Q95BxQW0WoQsP9dJahi3fGU9WflElR4tqY7FATPHisoipYJSFQqJieYVmvoqOA2Bi8b9bUTMcKj+kvKeffpoJEyZUeExYWBhBQUEkJyeXu7+oqIjU1FSCgoIqfH5mZiZDhw7F09OT77//HkdHxwqPj4iI4PXXXyc/Px9n5yvnsjg7O1/1fiFsUnAnaBwJcdsgejYMek11ImHj+rX0J8zPndMXs1kWE8fDfcJUR6objv0Kl06Cszd0HKM6jdCBb3ef41J2AQ19XBncNlB1HLt23QWuv78//v7+lR4XGRlJWloau3btokuXLgCsX78ei8VCRETENZ+XkZHBkCFDcHZ25qeffqrS4rG9e/dSr149KWKF/ej1lFbg7lwAfZ4GF/kYS1yb0Whgct8wZn53gM//PMO4yFBpO1TTrFbY8oE27jYJnD2VxhG2z2yxMnfTaQAm9W6Kg0n+jdakGvvdbdOmDUOHDmXy5MnExMSwZcsWHn/8ccaMGUNwcDAACQkJtG7dmpiYGEArbgcPHkx2djaff/45GRkZJCYmkpiYiNms7dTz888/M2/ePA4ePMjJkyeZPXs2//73v3niiSdq6q0IUftaDAH/1trcPtn4QVTBnZ0a4u/pzIX0PH7ed/VONaIaxW2DczvA5CyLy0SV/H4okdhLOfi4OTKmu6wFqmk1+uPDkiVLaN26NQMHDuT222+nd+/efPbZZ6WPFxYWcuzYMXJytJW/u3fvJjo6mgMHDtC8eXMaNGhQeiuZN+vo6MisWbOIjIwkPDycTz/9lPfee4+XX365Jt+KELXLaISeT2rj7bOhKF9tHmHzXBxNpSuyP910CotFNn6oUX9+oH0Nvw885aNmUTGr1cqcjacAGNejCW5O1/0BurhOBmsd3P4mIyMDb2/v0hZkQtikogL4MBwyEuCOD6HLeNWJhI1Lzy2k15vrycov4vPxXRnYRgqvGpF0GGZHAgZ4YhfUb6Y6kbBxW09e5P550bg4Gtny/ADqe8iUyqq4mXpNJoAIYascnKDHo9p464faim0hKuDt6sjYCG1XpJKrRaIGbP1Q+9p2uBS3okpmF/97vLdriBS3tUQKXCFsWZfx2gKzSyfh2C+q0wgdeKh3UxxNBnbEXmbX2VTVcexPWjwc+EYb93pKbRahC4fOp7P5xEWMBpgsHU5qjRS4QtgyZ0/o9rA2/vMDbeW2EBUI9HLhzk7a9r1zNp5WnMYObf8ELEUQ2gcadlGdRujAp8X/Dod1CCbE101xmrpDClwhbF3EVG2ldsJOOLtFdRqhA1P6NsNggDWHkziZnKk6jv3ISYVdi7Rx7+lKowh9iE/NYeV+ravJI33l6m1tkgJXCFvnEQCdxmrjLf9Vm0XoQvMADwYVLzD7bJNcxa02Oz6HwmwIbC/b8ooqmbf5NBYr9GnhJ9vy1jIpcIXQg8jHwWCEE6sh6ZDqNEIHHumnLX76fk8Ciel5itPYgcJciJ6jjXs9BQaD2jzC5l3Kymf5Tq3F6dR+shixtkmBK4Qe1G8GbYZrY7mKK6qgS5N6dA/1pdBsZf6WM6rj6N+exZBzEXwawy13qk4jdGDRtrPkFVpo39Cbns3qq45T50iBK4RelKzYPrAC0uLUZhG6MLW/Nufvq+g40nMLFafRMXMRbPtYG0c+ASZp0i8qllNQxBfbYgHt6q1BrvjXOilwhdCLhp2haV+wmmHbJ6rTCB24tVUArQI9ycovYkn0WdVx9OvIj3A5Flx9y+bDC1GB5TviScsppEl9N4a2C1Idp06SAlcIPek1Xfu6e5G2oluIChgMBqYUr9ye/2cseYVmxYl0yGot25Y34hFwclcaR9i+QrOFeZu1aUGT+4RhMsrVWxWkwBVCT5oNgKD2UJgDO+apTiN0YHh4MMHeLlzMyue73Qmq4+jP6Q2QuB8c3aD7FNVphA6s3H+ehLRc/DycuLtLI9Vx6iwpcIXQE4Oh7Cpu9BwoyFEaR9g+R5ORScW7J3226RRmi2wWcl22fKB97fQguPkqjSJsn9VqLd3YYWKvprg4mhQnqrukwBVCb9qOBJ8mkHMJ9i5RnUbowJhuIXi7OhJ7KYfVhxJVx9GP83u0K7gGE0Q+pjqN0IENx1M4mpiJu5OJByKaqI5Tp0mBK4TemByg5xPaeOuH2gpvISrg7uzAuEjtm+2cjaewypbPVVPSkq/dKKgnxYqo3JwNpwC4r3tjvN0cFaep26TAFUKPwseCW32tXdjhH1SnETowvmcozg5G9p1LZ9vpS6rj2L7U03D4R21c0qJPiArsibtM9JlUHE0GJvVpqjpOnScFrhB65OQG3R/Rxls+0FZ6C1EBPw9n7u0aAlA6R1BUYOvHYLVA8ygIaqc6jdCBkn9XI8Ib0sDbVXEaIQWuEHrVfbK2sjvxAJxarzqN0IHJfcIwGmDj8RQOn89QHcd2ZaWUzW8vWdQpRAVOpWTx+2Ftfvsjxa35hFpS4AqhV26+0Hm8Npbte0UVNK7vxu3tGwDw6aZTitPYsJhPoSgPGnaB0N6q0wgdmLvpNFYrRLUJoEWgp+o4AilwhdC3yEe1Fd5nNmorvoWoxNR+zQBYuf8C8anSZu4K+VkQM1cb93pKa80nRAWSM/JKe0yX/PsS6kmBK4Se+TSG9ndr45LdloSoQLuG3vRp4YfZYuXzP8+ojmN7di+CvDTwbQat/6Y6jdCB+VtiKTBb6NqkHl1DpVeyrZACVwi9K1nhfeQnuCQfO4vKPdJXu8q0bEccqdkFitPYEHMhbJuljXs9CUZp0i8qlpFXyJLtZwF4RK7e2hQpcIXQu8BboMVgbcX3to9VpxE60Kt5fdo19CKv0MKirbGq49iOAysgIwE8AqHDGNVphA58FR1HZn4RLQI8GNg6QHUc8RdS4AphD0qu4u5ZAlnJarMIm2cwGErnCn6xLZacAtksBIulbLFmxFRwdFGbR9i8/CIz84un+UzpG4bRKPO1bYkUuELYgya9oGFXMOdD9BzVaYQO3NauAY193bicU8jXO+JVx1HvxGpIOQJOntD1IdVphA78sCeB5Mx8grxcGBHeUHUc8T+kwBXCHhgM0Hu6Nt4xD/IzlcYRts9kNDC5uF/n3M1nKDRbFCdSrOTqbdeJ4OqjNIqwfRaLlU83aRs7TOrdFCcHKadsjfyJCGEvWt0O9ZtDXjrsWqQ6jdCBe7o0ws/DiYS0XH7Zf0F1HHXiYyBuKxgdocc01WmEDqw+nMTplGy8XBy4L6Kx6jjiKqTAFcJeGE3Q80ltvG0WFMnqeFExF0cTE3qGAjBn4ymsdXXL55IWex1Hg1ew0ijC9lmtVuZs1DrWPBjZBA9nB8WJxNVIgSuEPek4BjyCIPM8HFyhOo3QgQd6NMHNycTRxEw2Hk9RHaf2pRyHY78ABuj5lOo0QgdizqSyNz4NJwcjE3o2VR1HXIMUuELYEwfnso9Yt/xXWxkuRAV83Jy4r7v2EWvJVak6ZWvx3NvWw8C/pdosQhdK/p3c3aUR/p7OitOIa5ECVwh703UiOHtBylE48bvqNEIHJvVuioPRwPbT2pWpOiPjPOxbro17ydVbUbmjiRn8cSwFowGm9AlTHUdUQApcIeyNi7dW5IJs3yuqJNjHtbTN0ad16Sru9k/AUgiNe0JId9VphA58tlHrnHBbuwaE+rkrTiMqIgWuEPYoYhqYnCB+O8RtV51G6MAj/bSrUasOJXI6JUtxmlqQmwY7F2rjkhZ7QlQgIS2Xn/adB8r+vQjbJQWuEPbIqwF0GK2NS/p7ClGBloGeDGwdgNUKczefVh2n5u2cDwWZ4N8Gmg9SnUbowLzNpymyWOnZrD4dGvmojiMqIQWuEPaq11OAAY79CslHVacROjC1v7Z977e7EkjOzFOcpgYV5sH22dq411NglG+FomKXswtYFqPt+FeyzbWwbfKvWgh75ddCWxkOsPUjtVmELnQL9aVLk3oUmC0s2BKrOk7N2b8MspPBqxG0v1t1GqEDX24/S26hmbYNvOjTwk91HFEFUuAKYc96Tde+7l8O6QlKowh9eKR4+97F28+SmVeoOE0NsJhhy4faOPJRMDmqzSNsXm6BmYVbYwFt7q3BYFAbSFSJFLhC2LOQbtCkl7ZSfPsnqtMIHYhqE0jzAA8y84r4KjpOdZzqd3QlpJ4CFx/oPF51GqED3+yKJzW7gBBfV4a1b6A6jqgiKXCFsHclV3F3LdRWjgtRAaPRwJTiq7jzt5whv8isOFE1slrLWud1nwzOHkrjCNtXZLaULrqc3CcMB5OUTXohf1JC2LsWgyCgLRRkwc7PVacROjAiPJhAL2eSMvL5cc951XGqT+yfcH43OLhA90dUpxE68OvBROJTc/F1d+KeLiGq44jrIAWuEPbOYCjbpWn7HG0FuRAVcHYwMal3UwDmbDqFxWJVnKiabPlA+xo+Fjz8lUYRts9qtTJng7bxyfjIUFydTIoTieshBa4QdUG7UeAdoq0c3/eV6jRCB+7r3hhPFwdOp2Sz9kiS6jg3L/EAnFwLBiP0fEJ1GqEDf568yOELGbg6mhgX2UR1HHGdpMAVoi4wOULkY9p460faSnIhKuDp4siDPbRv6nM2nsJq1flV3JLOCW1Hgm9TpVGEPswp3rZ6TPcQ6rk7KU4jrleNFripqamMHTsWLy8vfHx8mDRpEllZFW8B2b9/fwwGQ7nb1KlTyx0TFxfHsGHDcHNzIyAggGeffZaioqKafCtC6F+nB7WV46mn4cjPqtMIHZjQKxQnByO749LYEXtZdZwbd/ksHPxWG5dM1xGiAgfOpbPl5CVMRkPpdB2hLzVa4I4dO5ZDhw6xZs0aVq5cyaZNm5gyZUqlz5s8eTIXLlwovb399tulj5nNZoYNG0ZBQQFbt25l0aJFLFy4kJdeeqkm34oQ+ufsAd2L//1t+UBbUS5EBQI8XRjVuRFQdjVLl7bNAqsZwvpDcLjqNEIHSv6+D+8YTKN6borTiBtRYwXukSNHWLVqFfPmzSMiIoLevXvz0UcfsWzZMs6fr3hVrpubG0FBQaU3Ly+v0sdWr17N4cOHWbx4MeHh4dx22228/vrrzJo1i4KCgpp6O0LYh4hHwMEVzu+B2M2q0wgdmNI3DIMB1h9N5lhipuo41y/7Euz+QhuXtMwTogKxF7P57eAFQNvYQehTjRW427Ztw8fHh65du5beFxUVhdFoJDo6usLnLlmyBD8/P9q1a8fMmTPJyckpd9727dsTGBhYet+QIUPIyMjg0KFDVz1ffn4+GRkZ5W5C1EnuftDpAW288W25iisq1dTPndvaBQHw8R8nFae5Ads/gaJcaNBRu4IrRCVmbziFxQq3tvKndZBX5U8QNqnGCtzExEQCAgLK3efg4ICvry+JiYnXfN7999/P4sWL+eOPP5g5cyZffvklDzzwQLnz/rW4BUp/fa3zvvHGG3h7e5feQkKkl52ow3o9CSYn7QruqXWq0wgdeOzW5gD8vO88BxPSFae5DpmJ2vQEgL7Pai3zhKjAiaRMvtkVD8DjA1ooTiNuxnUXuC+88MIVi8D+93b06NEbDjRlyhSGDBlC+/btGTt2LF988QXff/89p07d+PyvmTNnkp6eXnqLj4+/4XMJoXs+jcvm4q55BSwWpXGE7bsl2JuR4cEAvLXqxv9/r3Ub3tSu3jbqDq3/pjqN0IG3fz+GxQpDbgmkS5N6quOIm+BwvU94+umnmTBhQoXHhIWFERQURHJycrn7i4qKSE1NJSgoqMqvFxERAcDJkydp1qwZQUFBxMTElDsmKUnr0Xit8zo7O+Ps7Fzl1xTC7vV5WpuXmHQADq6ADveqTiRs3NODW/HLgQtsPnGRzSdS6NPCxjdKuHiibO7toFfl6q2o1M7YVNYcTsJogGeHtFYdR9yk676C6+/vT+vWrSu8OTk5ERkZSVpaGrt27Sp97vr167FYLKVFa1Xs3bsXgAYNGgAQGRnJgQMHyhXPa9aswcvLi7Zt217v2xGibnLzhd7TtfH616EoX2kcYftCfN14oLgv7lurjtr+7mbrXtU6J7S8DZr0VJ1G2Dir1cqbv2mfTozuFkLzAA/FicTNqrE5uG3atGHo0KFMnjyZmJgYtmzZwuOPP86YMWMIDtY+6kpISKB169alV2RPnTrF66+/zq5du4iNjeWnn35i3Lhx9O3blw4dOgAwePBg2rZty4MPPsi+ffv4/fffefHFF3nsscfkKq0Q1yNiGng2gLQ42PG56jRCBx6/tTkezg4cTMjg5/0Vd8NRKn6H1uvZYISol1WnETqw5nASO89exsXRyPSolqrjiGpQo31wlyxZQuvWrRk4cCC33347vXv35rPPPit9vLCwkGPHjpV2SXBycmLt2rUMHjyY1q1b8/TTTzNq1Ch+/rmsKb3JZGLlypWYTCYiIyN54IEHGDduHK+99lpNvhUh7I+TG/SfqY03/QfydLR4SChR38OZqcVtk95ZfYyCIhucv221wprivujh90NAG7V5hM0rMlt4+/djAEzq3ZRALxfFiUR1MFh1v//i9cvIyMDb25v09PRyPXaFqHPMRTA7Ei4ehz7PwMB/qk4kbFxOQRH9/rOBlMx8XrmjLRN62dguT8d/h6/uBQcXeGIXeDdSnUjYuOU74nj+2wP4uDmy6blb8XJxVB1JFLuZeq1Gr+AKIWycyQEGFn+Eu20WZFxQm0fYPDcnB6ZHae2TPlx/ksy8QsWJ/sJihrWvaOOIR6S4FZXKLTDz/poTgDYFR4pb+yEFrhB1XethEBKhtVPa+KbqNEIH7u0aQpifO6nZBczddFp1nDL7lkHyYXDxgd5/V51G6MCCrWdIzMijoY8rD0Y2UR1HVCMpcIWo6wwGiHpVG+/+ElKOq80jbJ6jycizQ1oBMHfzGZIz8xQnAgpz4Y//p437PA2u0sNUVOxydgGzN2g99p8e3BJnB5PiRKI6SYErhIAmkdDqdq2t0npZsCkqN7RdEOEhPuQWmvlw3QnVcSBmLmQkgFejso1MhKjAJxtOkplXRJsGXowMb6g6jqhmUuAKITQDX9LaKh35GeJjKj9e1GkGg4EXbtOa4S+Nied0Spa6MLmXYfO72vjW/wNHWQUvKnbucg6Ltp4F4PmhrTAaZSMQeyMFrhBCE9BGa6sEsOZlrd2SEBXoEVafAa0DMFusvLta4dSWP9+HvDTwbwMdx6jLIXTj/TUnKDBbiAyrT7+WNr4rn7ghUuAKIcr0/z+tvVLcVq3dkhCVeG5oKwwG+OXABfbGp9V+gPRzsH2ONo56BYwyj1JU7MiFDL7bcw6AF25rjUG2cbZLUuAKIcp4N4SIqdp47Sta2yUhKtA6yIu7OmntuN749Qi13lp9wxtgzocmvaDlkNp9baFLb686itUKw9o3oGOIj+o4ooZIgSuEKK/3dK3NUsoRre2SEJWYMbglTg5Gos+ksuF4Su29cPIR2PuVNo56VesIIkQFtp26xB/HUnAwGnimuBOIsE9S4AohynOtp7VZAq3tUmGu2jzC5jX0cWVCz1AA3vrtKGZLLV3FXfsqWC3Q5g4I6VY7ryl0y2q18uaqowDc170xTf3cFScSNUkKXCHElbpP0dotZSRAzGeq0wgdeLR/MzxdHDiamMkPexJq/gXPboXjv4HBVLYbnxAV+O1gIvvi03BzMvHEwOaq44gaJgWuEOJKji4w4B/aePO7WhsmISrg4+bEo/21ouG9NcfJK6zB+dtWq9bpA6DzOPBrUXOvJexCodnCf34/BsDDfcII8JRWcvZOClwhxNV1GA0BbSEvXWvDJEQlJvYKJcjLhYS0XBZvP1tzL3T0FzgXA45u0P+FmnsdYTeW74jnzMVs6rs7MaVvmOo4ohZIgSuEuDqjSWu7BFobpvRzSuMI2+fiaGLGoJYAfPzHSdJzC6v/RcxFsK54a+kej4JnUPW/hrAr2flFfLBW223vyYEt8HB2UJxI1AYpcIUQ19ZisNZ+yZwPf7yhOo3Qgbs6N6RFgAdpOYV8uvFU9b/A3sVw8Ti4+kKvJ6v//MLuzP/zDBez8mns68Z93RurjiNqiRS4QohrMxhg0GvaeN9XkHRYbR5h8xxMRp4bqm3hO3/LGRLT86rv5AU5ZT9o9XsOXLyr79zCLl3KyufTTacBeGZIK5wcpOypK+RPWghRsUZdoc1wrR3TutdUpxE6ENUmgK5N6pFXaOGDtdW4hW/0bMhKBJ/G0PWh6juvsFsfrT9JVn4R7Rp68bf2DVTHEbVIClwhROUGvqS1Yzr+m9aeSYgKGAwGZt6uXcX9emc8J5Mzb/6k2Zfgzw+08YB/goPzzZ9T2LW4SzksidYWO74wtA1Go2wEUpdIgSuEqJxfC60dE8Cal7Q2TUJUoEsTXwa3DcRihbdXHbv5E25+F/IzILA9tLv75s8n7N67a45RaLbSp4UfvVv4qY4japkUuEKIqun/gtaW6dwOOLpSdRqhA88NbYXRAKsPJ7HrbOqNn+jyWdgxVxsPegWM8q1LVOxgQjo/7j0PwPPFc8JF3SL/SwghqsYzCCIf08ZrX9XaNQlRgeYBntzbNQSAN349ivVGr/z/8W8wF0DTftBsYDUmFPbqreIteUeEB9OuoSxGrIukwBVCVF3PJ7X2TJdOwJ4vVacROjA9qiXODkZ2nr3M2iPJ13+CxAOwf7k2jnpF6+whRAU2n0hh84mLOJoMPD2oleo4QhEpcIUQVefipbVnAtjwJhRkq80jbF6QtwsP9W4KwNurjlJktlzfCda+AljhlrugYedqzyfsi8ViLb16OzaiCY3ruylOJFSRAlcIcX26PqS1acpKhO2zVacROjC1XzN83Bw5kZzFd7sTqv7E0xvh5FowOsCAF2suoLAbKw9c4GBCBh7ODjwxoLnqOEIhKXCFENfHwRkGvKSNt/xXa98kRAW8XR15/Fat2HhvzXFyC8yVP8lqhbUva+OuD0H9ZjWYUNiDgiIL7/yudex4pG8Y9T2klVxdJgWuEOL6tRsFQe21tk2b31GdRujAAz2a0NDHlcSMPBZuja38CYe+h/N7wMkD+j5X4/mE/n0VfZa41Bz8PJyZ1Kep6jhCMSlwhRDXz2iEqFe1ccxcuByrNI6wfS6OJmYMagnAJxtOkpZTcO2DzYVlu+b1fAI8/GshodCzzLxCPlx/EoDpUS1wc3JQnEioJgWuEOLGNBugtW2yFGptnISoxMhODWkd5ElmXhGfbDh17QN3LYTLZ8Ddv6w1nRAVmLv5DKnZBYT5uTO6W4jqOMIGSIErhLgxBgMMKr6Ku/9ruLBfbR5h80xGA8/fpjXdX7g1loS03CsPys+CjW9p437Pg7NnLSYUepScmce8zacBeHZIKxxNUtoIKXCFEDcjuJM2HxdrcTsnISrWv6U/PcJ8KSiy8N7q41cesO1jyE4B3zDoMqHW8wn9+XDdCXIKzHQM8WFouyDVcYSNkAJXCHFzBryotXE6tQ5Ob1CdRtg4g8HAC7e1AeC7Pec4mphR9mBWMmz9SBsP+CeYHBUkFHpyOiWLpTHxAMy8rTUG2QhEFJMCVwhxc3zDtDZOAGteBst1NvIXdU54iA+3tw/CaoW3Vx0re2DTf6AgS/tkoO1IZfmEfry7+jhmi5VbW/nTI6y+6jjChkiBK4S4eX2f09o5XdgLh39QnUbowDODW2EyGlh/NJntpy9B6mnYOV97MOpVrVOHEBXYG5/GLwcuYDDAc0Nbq44jbIz8DyKEuHke/tDzSW287jWtzZMQFQjz9+C+7tpq9zd/O4p1/b/AUgTNoyCsn+J0wtZZrVbe/O0IAHd1akSbBl6KEwlbIwWuEKJ6RD6mtXW6fEZr8yREJZ4c2AJXRxPmc7sxHPwWMEDUK6pjCR3YcDyF7adTcXIwMmNwS9VxhA2SAlcIUT2cPbS2TgAb3oS8dLV5hM0L8HRhcu9QZjp8BYC53T3aDnlCVKDQbOGt344CMD5S2yFPiP8lBa4Qovp0mQC+zSDnIvwq26uKyj3quZGepsPkWx351DRGdRyhAx+vP8nRxEy8XBx4tH9z1XGEjZICVwhRfUyOMPITMBhh/zI4+K3qRMKWpRzHZf3LALxZNIb/xOSx9dRFxaGELdt19jIf/6FtyfuvO9tTz91JcSJhq6TAFUJUr8Y9oM/T2njl3yE9QW0eYZuKCuC7h6EoF8JuJb/zw1it8PTX+0jPkUWK4kpZ+UXM+HovZouVkeHBDO8YrDqSsGFS4Aohql+/5yG4szYP94ep0htXXGnDG3BhH7jWg5GzefGOdjT1c+dCeh4v/ngQq9WqOqGwMa/9fIizl3Jo6OPKayPbqY4jbJwUuEKI6mdyhLvmgqMbnNkE22epTiRsydmt8Of72viOD8GrAW5ODrw/OhyT0cDP+87z497zajMKm7Lq4AW+3nkOgwHeu7cjXi6yy52oWI0WuKmpqYwdOxYvLy98fHyYNGkSWVlZ1zw+NjYWg8Fw1ds333xTetzVHl+2bFlNvhUhxPXyaw5D/q2N170GiQfU5hG2IS8dvnsEsEL4A9B2eOlD4SE+PDWwBQD//OEg5y7nKAopbElSRh4vfKf9/zG1XzMiZMcyUQU1WuCOHTuWQ4cOsWbNGlauXMmmTZuYMmXKNY8PCQnhwoUL5W6vvvoqHh4e3HbbbeWOXbBgQbnjRo4cWZNvRQhxI7pMgJa3gbkAvp0MhXmqEwnVfn0O0uOgXijc9uYVDz/avxmdG/uQmV/EjK/3YbbIVIW6zGKx8sw3+0jLKeSWYC/+HiU9b0XV1FiBe+TIEVatWsW8efOIiIigd+/efPTRRyxbtozz56/+0ZPJZCIoKKjc7fvvv+fee+/Fw8Oj3LE+Pj7ljnNxcamptyKEuFEGAwz/SNsAIuUIrHtVdSKh0sFvte4aBiPc+Rk4e15xiIPJyPujw3F3MhFzJpXPNp1WEFTYii+2xbL5xEWcHYz8d0w4Tg4ys1JUTY39Tdm2bRs+Pj507dq19L6oqCiMRiPR0dFVOseuXbvYu3cvkyZNuuKxxx57DD8/P7p37878+fMrXJCQn59PRkZGuZsQopZ4+MOI4jm42z+BU+vV5hFqpCdoXTUA+jwDjSOueWiT+u68PPwWAN5bc4yDCbJpSF10PCmTN4o3dPjHsDY0D7jyByIhrqXGCtzExEQCAgLK3efg4ICvry+JiYlVOsfnn39OmzZt6NmzZ7n7X3vtNb7++mvWrFnDqFGjePTRR/noo4+ueZ433ngDb2/v0ltISMj1vyEhxI1rOQS6Fv+g+sOjkJOqNo+oXRaL1k0jL13rrtGv8k1A7unSiKG3BFFotvLUsj3kFphrIaiwFflFZp5atpf8Igv9WvrzYI8mqiMJnbnuAveFF1645kKwktvRo0dvOlhubi5fffXVVa/e/vOf/6RXr1506tSJ559/nueee47//Oc/1zzXzJkzSU9PL73Fx8ffdD4hxHUa/C+o3wIyL8DPT4G0gao7tn+iddNwdNO6a5gqXwFvMBh44672BHg6cyolmzd+O1ILQYWteG/1cY5cyMDX3Yn/3NMBg8GgOpLQmesucJ9++mmOHDlS4S0sLIygoCCSk5PLPbeoqIjU1FSCgoIqfZ0VK1aQk5PDuHHjKj02IiKCc+fOkZ+ff9XHnZ2d8fLyKncTQtQyJzcYNReMDnDk/7d353FV1nn/x1+HXWWT7QCu4IYrmiai2SaujeVSLk2NWlquv9D2mZKxuzLrrttqHEvTdO5bTZu0slJzSxv3NFxSUclCE3FBQEBkOdfvj2vEmExBwQsO7+fjcR6Pc851znW96etFHy+/1+f7OSQutDqR3Awn916ee91rqtldo5Rq1/Lgvx+IBuAfW35m/cFT1/iGOIPNyWeY9a059/q1Aa0J8dE9NlJ2bmX9QnBwMMHBwdf8XGxsLBkZGezcuZP27dsDsG7dOhwOBzExvz/36pI5c+Zw7733lupYiYmJ1K5dG09Pz2v/ACJinfB2cNefzbZhK56BBp0hIMLqVFJRCvLM7hlF+dCsD9wyrMy7uL1pMCO6NOTDTT/x9D/3sCq+K4He+l3vrDJzC3hyyW4MA4Z2rEePlte+ICZyJRU2B7d58+b06tWLUaNGsX37djZt2sT48eMZMmQI4eHm8nq//PILUVFRbN++vcR3jxw5wsaNGxk5cuRv9rt8+XI++OAD9u3bx5EjR5g5cyavvvoqEyZMqKgfRUTKU5d4qB8L+dmw7HEoKrQ6kVSUtVPM7hm1QsxuGtf5z8zP9oqiqd2bM9kXeW7pXq1y5sRe/GwfqZl5NAysyQv3tLA6jlRhFdpvY8GCBURFRdGtWzf69OnDbbfdxqxZs4q3FxQUkJSURG5uyWbec+fOpW7duvTo0eM3+3R3d2fGjBnExsbStm1b3n//fd566y0SEhIq8kcRkfLi4gr93wcPHzi27fKKVuJckteZc2/B7KJRK+i6d+Xl7sr0we3wcHVh9f40Fu/QfRTO6LPEX/h89wlcXWxmqzjPMv8js0gxm1EN/yqclZWFn58fmZmZmo8rYpXdH5lXcG2u8OhqqNve6kRSXnLTYWZn84bCW0fCPW+Wy25nbUzm1a8OUsPdla+e6EpEUK1y2a9Y7/i5XHpP/5bzFwuZGNeUJ+KaWB1JKoEbqdfUMVlErNFmMLTsD0YRLB0F+TlWJ5LyYBhml4zzqWbXjO7/VW67HnlbJLGRgVwoKCJ+cSIFRY5y27dYp8hhMGnJbs5fLKRdfX/G3dXI6kjiBFTgiog1bDa45y3wCYf0ZFj1F6sTSXnYvcjskuHiZnbN8KhZbrt2cbHx5qBofL3c2H0sg3fXHSm3fYt1Zm38ke1H06nl4cr0wW1xc1VpIjdOf4pExDo1A6D/e+bznR9C0gpr88iNST8KXz1tPr/rL2bXjHIW7l+DV/q3BuBv6w6z8+dz5X4MuXn2/ZLJW6uTAEi4tyUNAjXtRMqHClwRsVbkHRA73nz+2XjIVq/TKqmo0JxTnZ8N9TtDlycq7FB9o8Pp364ODgMmLk4k+6I6cVRFF/KLeOKj7ykoMujVMpQH2te1OpI4ERW4ImK9bpMhpCXknoHPxmmVs6roX/9jdsXw9DWvyru4VujhptzXkjr+NUhJz+Wl5T9U6LGkYry24gDJp3MI8fHk1QGttVqZlCsVuCJiPTdPc76mqycc/hq+m2N1IimL4zvhm6nm8z7/DbUbVPghfb3ceWtQNDYbLPnuOCv3pVb4MaX8rE86xfwtPwPwxgPRBNTysDiROBsVuCJSOdhbQtxfzeerXoDThyyNI6WUn2N2wTCKoOUAaDPoph06JjKQ0XeYd9w/t3QvaVl5N+3Ycv3OZl/k6Y/3ADC8c0PuaHrtFUtFykoFrohUHjGjIfJOKLwAS0dCYb7VieRaVv3F7ILhWwf+8NZ1r1Z2vSbGNaVluC8ZuQU89fFuHA5Nb6nMDMPguaV7OZN9kSYh3jzXO8rqSOKkVOCKSOXh4gL9ZkKN2pC6Gza8ZnUiuZqkFWb3C2yXx+0m83Bz4e0hbfF0c+Hbw2eYv+Wnm55BSm/xjmOs3p+Gu6uN6UPa4uVesXO1pfpSgSsilYtvOPxhuvn827fg582WxpHfkX3K7HoB0Hm82Q3DIo1DfHjhnuYATF1xkENp5y3LIr/v6JkcpizfD8DTPZvRMtzP4kTizFTgikjl07IftP0jYMDSxyEv0+pE8muGYRa3uWfA3gruftHqRDzUqQF3Ngsmv9DBEx8lcrGwyOpI8isFRQ7iFydyoaCI2MhARt4WaXUkcXIqcEWkcur1Gvg3gMwU+OoZq9PIr303Bw6vMrteDJhtdsGwmM1m4/X72xBQy4MDqVm89bVuUqxM/rbuCLuPZeDj5cabg6JxcVFLMKlYKnBFpHLy8oUBs8DmAns+gn2fWJ1IwOxuseoF83n3KWBvYW2eXwnx8eK1AeYqZ7O+/ZHNyWcsTiQAO38+x7vrDgPwSv/WhPvXsDiRVAcqcEWk8qrfCbo+aT7/YiJk/mJtnuquMP/f3S0uQORd0PFxqxP9Ro+WoQztWA/DgCeX7CYzt8DqSNVa9sVCJi5OxGFAv7bh3BsdbnUkqSZU4IpI5XbHsxDezpyH++locDisTlR9bXjN7G5Ro7bZNcGlcv4v5IV7WtAwsCapmXn85dO9GFoZzzIvLf+BlPRc6vjXYMp9rayOI9VI5fztJCJyias7DPgA3GvC0Y2w9e9WJ6qeft5sdrUAs8uFb5ilca6mlqcb/zO4La4uNr7Yk8pniSesjlQtrdyXypLvjmOzwZuDovGr4W51JKlGVOCKSOUX1Bh6vmI+XzsFTu61Nk91k5dpdrPAMLtbtOxndaJrale/Nv/v7iYAvPjpPo6l51qcqHpJy8rj+aXmefr47Y3oFBlocSKpblTgikjV0H4ENO0NRfnwv/3hxPdWJ6oesk/B/HvNbha1G0LvaVYnKrVxdzXilvr+nL9YyNDZW/nxdLbVkaqFY+m5DJm1lXO5BbQM92VS96ZWR5JqSAWuiFQNNhvcNwNC20DOafjwHjiyxupUzu1sMszpDqmJUDMQBv0DPH2sTlVqbq4uvPvgLTQMrMnxcxcYOHMzu1LOWR3Lqe37JZP+f9/M0TM51PGvwYwHb8HDTaWG3Hz6UyciVUetQBj+JUTeCQU5sHAwJC6yOpVzOr7TLG7P/WReuX10NYRFW52qzOr41+CfYzoTXdePc7kFPDh7K2v2p1kdyyltPHSawe9v4Uz2RZqH+bJ0bGcaBtWyOpZUUypwRaRq8fKFBz+G1oPAUWh2Vvj2TXN1LSkfh76G+X+A3LMQ1tYsbgMbWZ3qugV5e7LosU7c1SyYvAIHj/3vd3y0PcXqWE5l2ffHeWTeDnLyi+jSOJAlj3fC7utldSypxlTgikjV4+YB/d+HLk+Yr9e+BF89DQ4tz3rDdv0vLBoCBbnQqJt5xdw7xOpUN6ymhxuz/tSBQR3q4jDguaV7mb7mkFqI3SDDMHhvQzITF++m0GFwb3Q4Hw7viI+XOiaItVTgikjV5OIC3V+CXtMAG+yYDR8Pg4I8q5NVTYYBG96Az8eDUQTRQ+HBxeDpbXWycuPu6sK0gW2YcHdjAKavOcyfl+2lsEi9la9HkcNgyvL9vLbiIACjukYwfXBbzbmVSkF/CkWkaus0Gu6fC64ecGC52WHhgm4kKhNHEXw5Cda/bL7u+qS5kIOr812Fs9lsPNmjGS/3a4WLDRZtP8bo/9vJhXxd/S+LvIIiJizaxbzNPwHwwj3N+cs9LXBxsVkbTOTfVOCKSNXXagA8tBQ8/SBlM8ztBRnHrE5VNeTnwuKH4bu5gA36/Dd0m2x2rXBiD3VqwMyH2uPp5sKaA6d48IOtpOfkWx2rSsi8UMCf5m7nq70n8XB14d2h7RjZNdLqWCIlqMAVEecQ0RUeWQE+4XD6IMzpAWk/WJ2qcstNh3/cB0lfgqun2Qas4yirU900PVuGsmBkDH413Pk+JYP7Z27WghDXkJp5gQfe28z2o+n4eLox75Fb6RsdbnUskd9QgSsizsPeEkauhuAoOH8C5vaGo99anapyykiBuT3h+Hbw8oM/fQot7rU61U3XoWEAn4yJpY5/DX48k8OAmZvZ90um1bEqpUNp5xnw980cSssmxMeTJaNj6dwoyOpYIlekAldEnItfXRixAurHwsVM+L8BsG+p1akql9Q98EF3OHMIfOvAI6ugQWerU1mmcYgPS8d2JirUh9PnLzJk1lb+dfiM1bEqle1H07l/5mZSM/NoHOLN0rGdaR7ma3Uskd+lAldEnE/NAHj4U2je11za95+PwNaZVqeqHH7cAB/2geyTENLC7HEb0tzqVJaz+3qxZHQssZGBZF8sZPiH2/n0+1+sjlUpfLU3lYfmbCMrr5D2DWrzz9Gx1K1d0+pYIlelAldEnJO7FzwwH24dBRiw8jn4+kVwVOOWUHv/Cf83EPLPQ4PbzCvdfnWsTlVp+Hq5F88pLXQYxC9O5P0NydW6V+78zT8xbuEu8gsd9GhhZ8HIGPxrelgdS+SaVOCKiPNycYU+b0C3BPP15ndg2eNQWA3vlt/8LnzyKDgKoEU/eOgTqOFvdapKx9PNlbcHt2XkbREATF1xkJe+2I/DUb2KXMMwmLbyIAmf/4BhwEOd6jPzofZ4ubtaHU2kVFTgiohzs9mg6yTo9x64uMHeJbDwAcjLsjrZzeFwwMo/w9cvmK9jxsD9H5pXuOWKXFxsvPCHFrxwjzl148NNPzFh0ffkFVSPXrkFRQ6eXLKbmd8kA/BUj6b8132tcFWPW6lCVOCKSPXQdigMXQzuteDHb2BeHzh/0upUFavwonnVdusM83X3l6DXVHMVOLmmkV0jeWdoO9xdbXy5N5Vhc7eTeaHA6lgVKvtiIY/M28HS73/B1cXGG/e3YfzdTbA5eV9kcT76LSci1UeTOBj+BdQKhpN7YU53OHPY6lQVIy/TnG/7w1LzyvWA2dDlCadfwKG83RsdzvwRHfH2dGPb0XQGvbeFk5nOuRy02UFiC98ePkMNd1c+GNaBBzrUszqWyHVRgSsi1UudW+DRryEg0uwFO6cHHNthdarylZVqdkr46Vvw8IY/fgxtBlmdqsrq3DiIJY/HEuLjSVLaeQb8fROH0s5bHatcHT2Tw4CZm9j3SxaBtTz46LFO3NUsxOpYItdNBa6IVD8BkfDI1xB+C1xIh/l9IWmF1anKx+kk88p02j6oFQIjvoJGd1udqsprEe7L0rGdiQyuxYnMPO6fuZkdP6VbHatcJB7LYODMzRxLv0D9gJp8MqYz0fX8rY4lckNU4IpI9eQdDMOWQ+PuUHgBPnoQds6zOtWNSdlqXpHOPAaBjc1V3cKirU7lNOrWrsknozvTvkFtsvIK+eMH21i5L9XqWDdk3cE0hs7aSnpOPm3q+vHJmM40DKpldSyRG6YCV0SqL09vGLoI2j4EhgOWPwGrJ0NmFWvwfyEDvvsQ/nEf5GVAnQ7mFeraDS0O5nxq1/JgwcgYurewk1/oYMyCXcxYf4TT5y9aHa1M0nPymb3xR0b9YycXCoq4vWkwi0Z1ItjH0+poIuXCZlTDDtZZWVn4+fmRmZmJr6+WGhSp9gwD1r8CG9+4/F5YNDTrA816Q2ibyndz1rmfIGklJH0FP28CR6H5ftNeZhswD600VZEKixxM/vwHFm5LAcw/Hu3q+RPXwk735nYah3hXus4DyaezWbM/jTUH0tj58zkutfYdeEtdXhvYGndXXfOSyuVG6jUVuCpwReSSvf+E7bPh2DbgV78afeuYhW6z3tCwK7hZcJXL4YAT35sFbdIKOPVDye1BzaDNA9BlIri63fx81ZBhGCzcnsLiHcfYczyzxLYGgTWJa24nrrmdWxvWxs2C4rGwyMGulAzWHEhjzf40fjyTU2J7izBfHuhQl+GdG1a6YlwEVOCWmQpcEbmq7NNw+GuzmExeBwW5l7d5eEPjbubV3SY9oGZAxeUouAA/bjBzHFoJ2WmXt9lcoH7ny4V3YKOKyyHXdDIzj7UHzUJyU/JZ8gsvLwntV8Odu5oFE9fCzh1Ng/Hxcq+wHNkXC/n20GlWH0hj/cFTnMu93LfX3dVGp8hAerSwc3dzO3X8a1RYDpHyoAK3jFTgikipFVyAo99C0pfmlIDsXy0OYXOB+rH/LjL7lE+RmX0KDq0yr9ImrzNvgLvEw+dXxXX3ii2u5brlXCzk28NnWL0/jXUH065YZMY1t9OteQh1a9/4VJLUzAusOXCKNfvT2JJ8lvyiksX13VEhxDW3c3vToAotrkXKW6UscF955RW+/PJLEhMT8fDwICMj45rfMQyDhIQEZs+eTUZGBl26dGHmzJk0adKk+DPp6elMmDCB5cuX4+LiwsCBA3n77bfx9vYudTYVuCJyXRwOSP3eLD6TVpituH4tqOnlYrfureDieu19GobZ2uvS1IPjOyg5PaLur6ZH3GbN9Ai5bkUOg10p51izP43VB9L48XTJaQLNw3zp3jyEuBZ2WoX74VKK5XANw+CHE1nm1IMDaez7peSy0w0Ca9K9uZ24FnY6NLBmeoRIeaiUBW5CQgL+/v4cP36cOXPmlKrAnTZtGlOnTmX+/PlERETw4osvsnfvXvbv34+Xl7lueu/evUlNTeX999+noKCAESNGcOutt7Jw4cJSZ1OBKyLl4tzP5tSBpK/gp39dvtELoGagecNXs94QeZfZseGSokJI2fLvQvkrOHe05H7D2v7qBrfWle8GN7luyaezWXsgjTX7T/Hdz+nFN3oB2H096dbcvEkttlEgXu6X/4J0sbCIrT+mF98klvqr1dRsNrilfm3imtvp3iKERsGV7wY3ketRKQvcS+bNm0d8fPw1C1zDMAgPD+fJJ5/kqaeeAiAzMxO73c68efMYMmQIBw4coEWLFuzYsYMOHToAsHLlSvr06cPx48cJDw8vVSYVuCJS7vIy4cgas2g9/LX5+hJXT4i8AyJuh9Q9/96e8avtHhBxh1nQNu0FfnVueny5+dJz8ll/8BRrDqSx8dBpcvKLirfV9HCla5Mgbm0YwK6Uc2xIKrm9hru5Pa6FnbujQgjy1pV9cT43Uq9Vmlttjx49ysmTJ4mLiyt+z8/Pj5iYGLZs2cKQIUPYsmUL/v7+xcUtQFxcHC4uLmzbto3+/ftfcd8XL17k4sXLPQqzsrKu+DkRkevm5QetBpqPogJz0YWkFebc3XM/mUXt4a8vf75GwOUrvI3uLnmFV6qFgFoeDGxfl4Ht617xCu2qH9JY9cPlGwtDfMwrvD1a/PYKr4iUVGkK3JMnzRs37HZ7ifftdnvxtpMnTxISUnJtbDc3NwICAoo/cyVTp05lypQp5ZxYROR3uLpDRFfz0fOVy3NsU7ZCcDNz+kG9jqWboyvVgqebK3c0DeaOpsG8dF/L4jm2u49l0KqOH3HN7bSuU7o5uiJSxgL3ueeeY9q0aVf9zIEDB4iKirqhUOXt+eefZ9KkScWvs7KyqFevnoWJRKTasNkgJMp8iJSCzWajVR0/WtXxszqKSJVVpgL3ySefZPjw4Vf9TGRk5HUFCQ0NBSAtLY2wsLDi99PS0mjbtm3xZ06dOlXie4WFhaSnpxd//0o8PT3x9NT8JBEREZHqoEwFbnBwMMHBwRUSJCIigtDQUNauXVtc0GZlZbFt2zbGjBkDQGxsLBkZGezcuZP27dsDsG7dOhwOBzExMRWSS0RERESqlgprjpeSkkJiYiIpKSkUFRWRmJhIYmIi2dnZxZ+Jiopi2bJlgPlPMvHx8bz88st8/vnn7N27lz/96U+Eh4fTr18/AJo3b06vXr0YNWoU27dvZ9OmTYwfP54hQ4aUuoOCiIiIiDi3CrvJbPLkycyfP7/4dbt27QBYv349d955JwBJSUlkZl5upfPMM8+Qk5PDY489RkZGBrfddhsrV64s7oELsGDBAsaPH0+3bt2KF3p45513KurHEBEREZEqRkv1qg+uiIiISKVzI/Wa1u8TEREREaeiAldEREREnIoKXBERERFxKipwRURERMSpqMAVEREREaeiAldEREREnIoKXBERERFxKipwRURERMSpqMAVEREREaeiAldEREREnIoKXBERERFxKipwRURERMSpqMAVEREREafiZnUAKxiGAUBWVpbFSURERETkSi7VaZfqtrKolgXu+fPnAahXr57FSURERETkas6fP4+fn1+ZvmMzrqcsruIcDgcnTpzAx8cHm81W4cfLysqiXr16HDt2DF9f3wo/ntwcGlfnozF1ThpX56MxdT5XGlPDMDh//jzh4eG4uJRtVm21vILr4uJC3bp1b/pxfX19dSI6IY2r89GYOieNq/PRmDqf/xzTsl65vUQ3mYmIiIiIU1GBKyIiIiJORQXuTeDp6UlCQgKenp5WR5FypHF1PhpT56RxdT4aU+dT3mNaLW8yExERERHnpSu4IiIiIuJUVOCKiIiIiFNRgSsiIiIiTkUFroiIiIg4FRW4N8GMGTNo2LAhXl5exMTEsH37dqsjyXX661//is1mK/GIioqyOpaU0caNG+nbty/h4eHYbDY+/fTTEtsNw2Dy5MmEhYVRo0YN4uLiOHz4sDVhpVSuNabDhw//zbnbq1cva8JKqUydOpVbb70VHx8fQkJC6NevH0lJSSU+k5eXx7hx4wgMDMTb25uBAweSlpZmUWIpjdKM65133vmb83X06NFlOo4K3Aq2ePFiJk2aREJCArt27SI6OpqePXty6tQpq6PJdWrZsiWpqanFj3/9619WR5IyysnJITo6mhkzZlxx++uvv84777zDe++9x7Zt26hVqxY9e/YkLy/vJieV0rrWmAL06tWrxLm7aNGim5hQymrDhg2MGzeOrVu3snr1agoKCujRowc5OTnFn5k4cSLLly/n448/ZsOGDZw4cYIBAwZYmFqupTTjCjBq1KgS5+vrr79etgMZUqE6duxojBs3rvh1UVGRER4ebkydOtXCVHK9EhISjOjoaKtjSDkCjGXLlhW/djgcRmhoqPHGG28Uv5eRkWF4enoaixYtsiChlNV/jqlhGMawYcOM++67z5I8Uj5OnTplAMaGDRsMwzDPS3d3d+Pjjz8u/syBAwcMwNiyZYtVMaWM/nNcDcMw7rjjDuOJJ564of3qCm4Fys/PZ+fOncTFxRW/5+LiQlxcHFu2bLEwmdyIw4cPEx4eTmRkJH/84x9JSUmxOpKUo6NHj3Ly5MkS562fnx8xMTE6b6u4b775hpCQEJo1a8aYMWM4e/as1ZGkDDIzMwEICAgAYOfOnRQUFJQ4V6Oioqhfv77O1SrkP8f1kgULFhAUFESrVq14/vnnyc3NLdN+3cotofzGmTNnKCoqwm63l3jfbrdz8OBBi1LJjYiJiWHevHk0a9aM1NRUpkyZQteuXdm3bx8+Pj5Wx5NycPLkSYArnreXtknV06tXLwYMGEBERATJycn8+c9/pnfv3mzZsgVXV1er48k1OBwO4uPj6dKlC61atQLMc9XDwwN/f/8Sn9W5WnVcaVwBHnzwQRo0aEB4eDh79uzh2WefJSkpiaVLl5Z63ypwRcqgd+/exc/btGlDTEwMDRo0YMmSJTz66KMWJhORqxkyZEjx89atW9OmTRsaNWrEN998Q7du3SxMJqUxbtw49u3bp3senMzvjetjjz1W/Lx169aEhYXRrVs3kpOTadSoUan2rSkKFSgoKAhXV9ff3NGZlpZGaGioRamkPPn7+9O0aVOOHDlidRQpJ5fOTZ23zi0yMpKgoCCdu1XA+PHj+eKLL1i/fj1169Ytfj80NJT8/HwyMjJKfF7natXwe+N6JTExMQBlOl9V4FYgDw8P2rdvz9q1a4vfczgcrF27ltjYWAuTSXnJzs4mOTmZsLAwq6NIOYmIiCA0NLTEeZuVlcW2bdt03jqR48ePc/bsWZ27lZhhGIwfP55ly5axbt06IiIiSmxv37497u7uJc7VpKQkUlJSdK5WYtca1ytJTEwEKNP5qikKFWzSpEkMGzaMDh060LFjR6ZPn05OTg4jRoywOppch6eeeoq+ffvSoEEDTpw4QUJCAq6urgwdOtTqaFIG2dnZJa4EHD16lMTERAICAqhfvz7x8fG8/PLLNGnShIiICF588UXCw8Pp16+fdaHlqq42pgEBAUyZMoWBAwcSGhpKcnIyzzzzDI0bN6Znz54WpparGTduHAsXLuSzzz7Dx8eneF6tn58fNWrUwM/Pj0cffZRJkyYREBCAr68vEyZMIDY2lk6dOlmcXn7PtcY1OTmZhQsX0qdPHwIDA9mzZw8TJ07k9ttvp02bNqU/0A31YJBSeffdd4369esbHh4eRseOHY2tW7daHUmu0+DBg42wsDDDw8PDqFOnjjF48GDjyJEjVseSMlq/fr0B/OYxbNgwwzDMVmEvvviiYbfbDU9PT6Nbt25GUlKStaHlqq42prm5uUaPHj2M4OBgw93d3WjQoIExatQo4+TJk1bHlqu40ngCxocfflj8mQsXLhhjx441ateubdSsWdPo37+/kZqaal1ouaZrjWtKSopx++23GwEBAYanp6fRuHFj4+mnnzYyMzPLdBzbvw8mIiIiIuIUNAdXRERERJyKClwRERERcSoqcEVERETEqajAFRERERGnogJXRERERJyKClwRERERcSoqcEVERETEqajAFRERERGnogJXRMQiw4cPt2T533nz5mGz2bDZbMTHxxe/37BhQ6ZPn37V7176nr+/f4VmFBG5EW5WBxARcUY2m+2q2xMSEnj77bexajFJX19fkpKSqFWrVpm+l5qayuLFi0lISKigZCIiN04FrohIBUhNTS1+vnjxYiZPnkxSUlLxe97e3nh7e1sRDTAL8NDQ0DJ/LzQ0FD8/vwpIJCJSfjRFQUSkAoSGhhY//Pz8igvKSw9vb+/fTFG48847mTBhAvHx8dSuXRu73c7s2bPJyclhxIgR+Pj40LhxY1asWFHiWPv27aN37954e3tjt9t5+OGHOXPmzHXlzs3N5ZFHHsHHx4f69esza9asG/nPICJiCRW4IiKVyPz58wkKCmL79u1MmDCBMWPG8MADD9C5c2d27dpFjx49ePjhh8nNzQUgIyODu+++m3bt2vHdd9+xcuVK0tLSGDRo0HUd/80336RDhw58//33jB07ljFjxpS48iwiUhWowBURqUSio6N54YUXaNKkCc8//zxeXl4EBQUxatQomjRpwuTJkzl79ix79uwB4G9/+xvt2rXj1VdfJSoqinbt2jF37lzWr1/PoUOHynz8Pn36MHbsWBo3bsyzzz5LUFAQ69evL+8fU0SkQmkOrohIJdKmTZvi566urgQGBtK6devi9+x2OwCnTp0CYPfu3axfv/6K83mTk5Np2rTpdR//0rSKS8cSEakqVOCKiFQi7u7uJV7bbLYS713qzuBwOADIzs6mb9++TJs27Tf7CgsLK5fjXzqWiEhVoQJXRKQKu+WWW/jkk09o2LAhbm76lS4iApqDKyJSpY0bN4709HSGDh3Kjh07SE5OZtWqVYwYMYKioiKr44mIWEIFrohIFRYeHs6mTZsoKiqiR48etG7dmvj4ePz9/XFx0a94EamebIZVy+iIiIgl5s2bR3x8PBkZGZZ8X0Skoumv9yIi1VBmZibe3t48++yzZfqet7c3o0ePrqBUIiLlQ1dwRUSqmfPnz5OWlgaAv78/QUFBpf7ukSNHALOFWURERIXkExG5USpwRURERMSpaIqCiIiIiDgVFbgiIiIi4lRU4IqIiIiIU1GBKyIiIiJORQWuiIiIiDgVFbgiIiIi4lRU4IqIiIiIU1GBKyIiIiJO5f8D4OdFl5WjY6UAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(np.array(df['Day sin'])[:25])\n",
    "plt.plot(np.array(df['Day cos'])[:25])\n",
    "plt.xlabel('Time [h]')\n",
    "plt.title('Time of day signal')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "HiurzTGQgf_D"
   },
   "source": [
    "그러면 모델이 가장 중요한 빈도 특성에 액세스할 수 있습니다. 이 경우 어떤 빈도가 중요한지 미리 알고 있었습니다.\n",
    "\n",
    "해당 정보가 없는 경우 <a href=\"https://en.wikipedia.org/wiki/Fast_Fourier_transform\" class=\"external\">고속 푸리에 변환</a>을 사용하여 특성을 추출하여 중요한 빈도를 결정할 수 있습니다. 가정을 확인하기 위해 시간 경과에 따른 온도의 `tf.signal.rfft`가 있습니다. `1/year` 및 `1/day`에 가까운 빈도에서 명백한 피크가 있다는 점에 주목하세요.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:54:55.485934Z",
     "iopub.status.busy": "2022-12-14T22:54:55.485613Z",
     "iopub.status.idle": "2022-12-14T22:54:59.438099Z",
     "shell.execute_reply": "2022-12-14T22:54:59.437360Z"
    },
    "id": "EN4U1fcMiTYs"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fft = tf.signal.rfft(df['T (degC)'])\n",
    "f_per_dataset = np.arange(0, len(fft))\n",
    "\n",
    "n_samples_h = len(df['T (degC)'])\n",
    "hours_per_year = 24*365.2524\n",
    "years_per_dataset = n_samples_h/(hours_per_year)\n",
    "\n",
    "f_per_year = f_per_dataset/years_per_dataset\n",
    "plt.step(f_per_year, np.abs(fft))\n",
    "plt.xscale('log')\n",
    "plt.ylim(0, 400000)\n",
    "plt.xlim([0.1, max(plt.xlim())])\n",
    "plt.xticks([1, 365.2524], labels=['1/Year', '1/day'])\n",
    "_ = plt.xlabel('Frequency (log scale)')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "2rbL8bSGDHy3"
   },
   "source": [
    "### 데이터 분할"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "qoFJZmXBaxCc"
   },
   "source": [
    "훈련, 검증 및 테스트 세트에 `(70%, 20%, 10%)` 분할을 사용합니다. 분할하기 전에 데이터가 임의로 셔플되지 **않습니다**. 이것은 두 가지 이유 때문입니다.\n",
    "\n",
    "1. 데이터를 연속된 샘플의 창으로 자르는 것이 여전히 가능합니다.\n",
    "2. 모델을 훈련한 후 수집된 데이터를 바탕으로 평가하므로 검증/테스트 결과가 보다 현실적입니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:54:59.441721Z",
     "iopub.status.busy": "2022-12-14T22:54:59.441397Z",
     "iopub.status.idle": "2022-12-14T22:54:59.446555Z",
     "shell.execute_reply": "2022-12-14T22:54:59.445805Z"
    },
    "id": "ia-MPAHxbInX"
   },
   "outputs": [],
   "source": [
    "column_indices = {name: i for i, name in enumerate(df.columns)}\n",
    "\n",
    "n = len(df)\n",
    "train_df = df[0:int(n*0.7)]\n",
    "val_df = df[int(n*0.7):int(n*0.9)]\n",
    "test_df = df[int(n*0.9):]\n",
    "\n",
    "num_features = df.shape[1]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "-eFckdUUHWmT"
   },
   "source": [
    "### 데이터 정규화\n",
    "\n",
    "신경망을 훈련하기 전에 특성의 크기를 정하는 것이 중요합니다. 정규화는 평균을 빼고 각 특성의 표준 편차로 나누어 크기 조정을 수행하는 일반적인 방법입니다."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "mxbIic5TMlxx"
   },
   "source": [
    "모델이 검증 및 테스트 세트의 값에 액세스할 수 없도록 훈련 데이터를 사용해서만 평균 및 표준 편차를 계산해야 합니다.\n",
    "\n",
    "또한 모델이 훈련할 때 훈련 세트의 미래 값에 액세스할 수 없어야 하고 이 정규화가 이동 평균을 사용하여 수행되어야 한다고 말할 수도 있습니다. 이 내용은 본 튜토리얼의 중점 사항이 아니며, 검증 및 테스트 세트가 있기 때문에 (다소) 정직한 메트릭을 얻을 수 있습니다. 따라서 단순화를 위해 이 튜토리얼에서는 단순 평균을 사용합니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:54:59.450257Z",
     "iopub.status.busy": "2022-12-14T22:54:59.449656Z",
     "iopub.status.idle": "2022-12-14T22:54:59.491115Z",
     "shell.execute_reply": "2022-12-14T22:54:59.490215Z"
    },
    "id": "Eji6njXvHusN"
   },
   "outputs": [],
   "source": [
    "train_mean = train_df.mean()\n",
    "train_std = train_df.std()\n",
    "\n",
    "train_df = (train_df - train_mean) / train_std\n",
    "val_df = (val_df - train_mean) / train_std\n",
    "test_df = (test_df - train_mean) / train_std"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "G6ufs8kk9JQw"
   },
   "source": [
    "이제 특성의 분포를 살펴봅니다. 일부 특성은 꼬리가 길지만 `-9999` 풍속 값과 같은 명백한 오류는 없습니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:54:59.495230Z",
     "iopub.status.busy": "2022-12-14T22:54:59.494957Z",
     "iopub.status.idle": "2022-12-14T22:55:04.077693Z",
     "shell.execute_reply": "2022-12-14T22:55:04.076744Z"
    },
    "id": "T0UYEnkwm8Fe"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_std = (df - train_mean) / train_std\n",
    "df_std = df_std.melt(var_name='Column', value_name='Normalized')\n",
    "plt.figure(figsize=(12, 6))\n",
    "ax = sns.violinplot(x='Column', y='Normalized', data=df_std)\n",
    "_ = ax.set_xticklabels(df.keys(), rotation=90)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "ZBBmdxZ2HgfJ"
   },
   "source": [
    "## 데이터 창 작업\n",
    "\n",
    "이 튜토리얼의 모델은 데이터의 연속된 샘플 창을 기반으로 일련의 예측을 수행합니다.\n",
    "\n",
    "입력 창의 주요 특성은 다음과 같습니다.\n",
    "\n",
    "- 입력 및 레이블 창의 너비(타임스텝 수)\n",
    "- 각 사이의 시간 오프셋\n",
    "- 입력, 레이블 또는 둘 모두로 사용되는 특성\n",
    "\n",
    "이 튜토리얼은 다양한 모델(선형, DNN, CNN 및 RNN 모델 포함)을 빌드하고 다음 두 가지 목적으로 이 모델을 사용합니다.\n",
    "\n",
    "- *단일 출력* 및 *다중 출력* 예측\n",
    "- *단일 타임스텝* 및 *다중 타임스텝* 예측\n",
    "\n",
    "이 섹션에서는 모든 모델에 재사용할 수 있도록 데이터 창 작업을 구현하는 부분에 중점을 둡니다.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "YAhGUVx1jtOy"
   },
   "source": [
    "작업 및 모델 유형에 따라 다양한 데이터 창을 생성할 수 있습니다. 다음은 몇 가지 예입니다.\n",
    "\n",
    "1. 예를 들어, 24시간의 기록이 주어졌을 때 앞으로 24시간의 미래를 단일 예측하기 위해 다음과 같은 창을 정의할 수 있습니다.\n",
    "\n",
    "![One prediction 24h into the future.](images/raw_window_24h.png)\n",
    "\n",
    "1. 6시간의 기록이 주어졌을 때 앞으로 1시간의 미래를 예측하는 모델에는 다음과 같은 창이 필요할 수 있습니다.\n",
    "\n",
    "![One prediction 1h into the future.](images/raw_window_1h.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "sa2BbfNZt8wy"
   },
   "source": [
    "이 섹션의 나머지 부분에서는 `WindowGenerator` 클래스를 정의합니다. 이 클래스는 다음을 수행할 수 있습니다.\n",
    "\n",
    "1. 위의 다이어그램과 같이 인덱스와 오프셋을 처리합니다.\n",
    "2. 특성 창을 `(features, labels)` 쌍으로 분할합니다.\n",
    "3. 결과 창의 내용을 플롯합니다.\n",
    "4. `tf.data.Dataset`를 사용하여 훈련, 평가 및 테스트 데이터로부터 이러한 창을 여러 배치로 효율적으로 생성합니다."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "rfx3jGjyziUF"
   },
   "source": [
    "### 1. 인덱스 및 오프셋\n",
    "\n",
    "우선 `WindowGenerator` 클래스를 만듭니다. `__init__` 메서드에는 입력 및 레이블 인덱스에 필요한 모든 논리가 포함됩니다.\n",
    "\n",
    "또한 훈련, 평가 및 테스트 DataFrame을 입력으로 사용합니다. 이러한 DataFrame은 나중에 창의 `tf.data.Dataset`로 변환됩니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:55:04.082637Z",
     "iopub.status.busy": "2022-12-14T22:55:04.082318Z",
     "iopub.status.idle": "2022-12-14T22:55:04.089378Z",
     "shell.execute_reply": "2022-12-14T22:55:04.088705Z"
    },
    "id": "Kem30j8QHxyW"
   },
   "outputs": [],
   "source": [
    "class WindowGenerator():\n",
    "  def __init__(self, input_width, label_width, shift,\n",
    "               train_df=train_df, val_df=val_df, test_df=test_df,\n",
    "               label_columns=None):\n",
    "    # Store the raw data.\n",
    "    self.train_df = train_df\n",
    "    self.val_df = val_df\n",
    "    self.test_df = test_df\n",
    "\n",
    "    # Work out the label column indices.\n",
    "    self.label_columns = label_columns\n",
    "    if label_columns is not None:\n",
    "      self.label_columns_indices = {name: i for i, name in\n",
    "                                    enumerate(label_columns)}\n",
    "    self.column_indices = {name: i for i, name in\n",
    "                           enumerate(train_df.columns)}\n",
    "\n",
    "    # Work out the window parameters.\n",
    "    self.input_width = input_width\n",
    "    self.label_width = label_width\n",
    "    self.shift = shift\n",
    "\n",
    "    self.total_window_size = input_width + shift\n",
    "\n",
    "    self.input_slice = slice(0, input_width)\n",
    "    self.input_indices = np.arange(self.total_window_size)[self.input_slice]\n",
    "\n",
    "    self.label_start = self.total_window_size - self.label_width\n",
    "    self.labels_slice = slice(self.label_start, None)\n",
    "    self.label_indices = np.arange(self.total_window_size)[self.labels_slice]\n",
    "\n",
    "  def __repr__(self):\n",
    "    return '\\n'.join([\n",
    "        f'Total window size: {self.total_window_size}',\n",
    "        f'Input indices: {self.input_indices}',\n",
    "        f'Label indices: {self.label_indices}',\n",
    "        f'Label column name(s): {self.label_columns}'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "yVJgblsYzL1g"
   },
   "source": [
    "이 섹션의 시작 부분에서 다이어그램에 나타낸 두 개의 창을 만드는 코드는 다음과 같습니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:55:04.093204Z",
     "iopub.status.busy": "2022-12-14T22:55:04.092664Z",
     "iopub.status.idle": "2022-12-14T22:55:04.098242Z",
     "shell.execute_reply": "2022-12-14T22:55:04.097518Z"
    },
    "id": "IsM5kRkz0UwK"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Total window size: 48\n",
       "Input indices: [ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23]\n",
       "Label indices: [47]\n",
       "Label column name(s): ['T (degC)']"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "w1 = WindowGenerator(input_width=24, label_width=1, shift=24,\n",
    "                     label_columns=['T (degC)'])\n",
    "w1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:55:04.101971Z",
     "iopub.status.busy": "2022-12-14T22:55:04.101348Z",
     "iopub.status.idle": "2022-12-14T22:55:04.106289Z",
     "shell.execute_reply": "2022-12-14T22:55:04.105650Z"
    },
    "id": "viwKsYeAKFUn"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Total window size: 7\n",
       "Input indices: [0 1 2 3 4 5]\n",
       "Label indices: [6]\n",
       "Label column name(s): ['T (degC)']"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "w2 = WindowGenerator(input_width=6, label_width=1, shift=1,\n",
    "                     label_columns=['T (degC)'])\n",
    "w2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "kJaUyTWQJd-L"
   },
   "source": [
    "### 2. 분할\n",
    "\n",
    "연속적인 입력 목록이 주어지면 `split_window` 메서드는 이 목록을 입력 창과 레이블 창으로 변환합니다.\n",
    "\n",
    "위에서 정의한 예제 `w2`는 다음과 같이 분할됩니다.\n",
    "\n",
    "![The initial window is all consecuitive samples, this splits it into an (inputs, labels) pairs](https://github.com/tensorflow/docs-l10n/blob/master/site/ko/tutorials/structured_data/images/split_window.png?raw=true)\n",
    "\n",
    "이 다이어그램에는 데이터의 `features` 축이 나와 있지 않지만 이 `split_window` 함수는 단일 출력과 다중 출력 예에서 모두 사용될 수 있도록 `label_columns`를 처리합니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:55:04.110101Z",
     "iopub.status.busy": "2022-12-14T22:55:04.109505Z",
     "iopub.status.idle": "2022-12-14T22:55:04.114674Z",
     "shell.execute_reply": "2022-12-14T22:55:04.113979Z"
    },
    "id": "W4KbxfzqkXPW"
   },
   "outputs": [],
   "source": [
    "def split_window(self, features):\n",
    "  inputs = features[:, self.input_slice, :]\n",
    "  labels = features[:, self.labels_slice, :]\n",
    "  if self.label_columns is not None:\n",
    "    labels = tf.stack(\n",
    "        [labels[:, :, self.column_indices[name]] for name in self.label_columns],\n",
    "        axis=-1)\n",
    "\n",
    "  # Slicing doesn't preserve static shape information, so set the shapes\n",
    "  # manually. This way the `tf.data.Datasets` are easier to inspect.\n",
    "  inputs.set_shape([None, self.input_width, None])\n",
    "  labels.set_shape([None, self.label_width, None])\n",
    "\n",
    "  return inputs, labels\n",
    "\n",
    "WindowGenerator.split_window = split_window"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "G6U6VtVuM15s"
   },
   "source": [
    "다음을 사용해 보세요."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:55:04.117905Z",
     "iopub.status.busy": "2022-12-14T22:55:04.117649Z",
     "iopub.status.idle": "2022-12-14T22:55:04.137345Z",
     "shell.execute_reply": "2022-12-14T22:55:04.136586Z"
    },
    "id": "YeCWbq6KLmL7"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "All shapes are: (batch, time, features)\n",
      "Window shape: (3, 7, 19)\n",
      "Inputs shape: (3, 6, 19)\n",
      "Labels shape: (3, 1, 1)\n"
     ]
    }
   ],
   "source": [
    "# Stack three slices, the length of the total window.\n",
    "example_window = tf.stack([np.array(train_df[:w2.total_window_size]),\n",
    "                           np.array(train_df[100:100+w2.total_window_size]),\n",
    "                           np.array(train_df[200:200+w2.total_window_size])])\n",
    "\n",
    "example_inputs, example_labels = w2.split_window(example_window)\n",
    "\n",
    "print('All shapes are: (batch, time, features)')\n",
    "print(f'Window shape: {example_window.shape}')\n",
    "print(f'Inputs shape: {example_inputs.shape}')\n",
    "print(f'Labels shape: {example_labels.shape}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "xtMk1ffk2Mmd"
   },
   "source": [
    "일반적으로 TensorFlow의 데이터는 가장 바깥 쪽 인덱스가 여러 예제(\"배치\" 차원)에 걸쳐 있는 배열로 구성됩니다. 중간 인덱스는 \"시간\" 또는 \"공간\"(너비, 높이) 차원입니다. 가장 안쪽 인덱스는 특성입니다.\n",
    "\n",
    "위의 코드는 3개의  7-타임스텝 창 배치를 사용하며 각 타임스텝에는 19개의 특성이 있습니다. 그러면 이것을 한 배치 당 6-타임스텝과 19개의 특성 입력 및 1-타임스텝 1-특성 레이블로 분할합니다. 레이블에는 하나의 특성만 있는데 이는 `WindowGenerator`가 `label_columns=['T (degC)']`로 초기화되었기 때문입니다. 우선 이 튜토리얼에서는 단일 출력 레이블을 예측하는 모델을 빌드합니다."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "tFZukGXrJoGo"
   },
   "source": [
    "### 3. 플롯하기\n",
    "\n",
    "다음은 분할 창을 간단하게 시각화할 수 있는 플롯 메서드입니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:55:04.141033Z",
     "iopub.status.busy": "2022-12-14T22:55:04.140735Z",
     "iopub.status.idle": "2022-12-14T22:55:04.144415Z",
     "shell.execute_reply": "2022-12-14T22:55:04.143659Z"
    },
    "id": "fmgd1qkYUWT7"
   },
   "outputs": [],
   "source": [
    "w2.example = example_inputs, example_labels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:55:04.147820Z",
     "iopub.status.busy": "2022-12-14T22:55:04.147267Z",
     "iopub.status.idle": "2022-12-14T22:55:04.154277Z",
     "shell.execute_reply": "2022-12-14T22:55:04.153631Z"
    },
    "id": "jIrYccI-Hm3B"
   },
   "outputs": [],
   "source": [
    "def plot(self, model=None, plot_col='T (degC)', max_subplots=3):\n",
    "  inputs, labels = self.example\n",
    "  plt.figure(figsize=(12, 8))\n",
    "  plot_col_index = self.column_indices[plot_col]\n",
    "  max_n = min(max_subplots, len(inputs))\n",
    "  for n in range(max_n):\n",
    "    plt.subplot(max_n, 1, n+1)\n",
    "    plt.ylabel(f'{plot_col} [normed]')\n",
    "    plt.plot(self.input_indices, inputs[n, :, plot_col_index],\n",
    "             label='Inputs', marker='.', zorder=-10)\n",
    "\n",
    "    if self.label_columns:\n",
    "      label_col_index = self.label_columns_indices.get(plot_col, None)\n",
    "    else:\n",
    "      label_col_index = plot_col_index\n",
    "\n",
    "    if label_col_index is None:\n",
    "      continue\n",
    "\n",
    "    plt.scatter(self.label_indices, labels[n, :, label_col_index],\n",
    "                edgecolors='k', label='Labels', c='#2ca02c', s=64)\n",
    "    if model is not None:\n",
    "      predictions = model(inputs)\n",
    "      plt.scatter(self.label_indices, predictions[n, :, label_col_index],\n",
    "                  marker='X', edgecolors='k', label='Predictions',\n",
    "                  c='#ff7f0e', s=64)\n",
    "\n",
    "    if n == 0:\n",
    "      plt.legend()\n",
    "\n",
    "  plt.xlabel('Time [h]')\n",
    "\n",
    "WindowGenerator.plot = plot"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "HXvctEuK68vX"
   },
   "source": [
    "이 플롯은 항목이 참조하는 시간을 기준으로 입력, 레이블 및 (나중에) 예측값을 정렬합니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:55:04.157865Z",
     "iopub.status.busy": "2022-12-14T22:55:04.157393Z",
     "iopub.status.idle": "2022-12-14T22:55:04.571681Z",
     "shell.execute_reply": "2022-12-14T22:55:04.570922Z"
    },
    "id": "XjTqUnglOOni"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x800 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "w2.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "UqiqcPOldPG6"
   },
   "source": [
    "다른 열을 플롯할 수 있지만 예제 창 `w2` 구성에는 `T (degC)` 열에 대한 레이블만 있습니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:55:04.575775Z",
     "iopub.status.busy": "2022-12-14T22:55:04.575475Z",
     "iopub.status.idle": "2022-12-14T22:55:04.915492Z",
     "shell.execute_reply": "2022-12-14T22:55:04.914753Z"
    },
    "id": "EBRe4wnlfCH8"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x800 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "w2.plot(plot_col='p (mbar)')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "xCvD-UaUzYMw"
   },
   "source": [
    "### 4. `tf.data.Dataset` 만들기"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "kLO3SFR9Osdf"
   },
   "source": [
    "마지막으로, 이 `make_dataset` 메서드는 시계열 DataFrame을 가져와 `tf.keras.utils.timeseries_dataset_from_array` 함수를 이용해 `(input_window, label_window)` 쌍의 `tf.data.Dataset`로 변환합니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:55:04.919807Z",
     "iopub.status.busy": "2022-12-14T22:55:04.919274Z",
     "iopub.status.idle": "2022-12-14T22:55:04.924000Z",
     "shell.execute_reply": "2022-12-14T22:55:04.923316Z"
    },
    "id": "35qoSQeRVfJg"
   },
   "outputs": [],
   "source": [
    "def make_dataset(self, data):\n",
    "  data = np.array(data, dtype=np.float32)\n",
    "  ds = tf.keras.utils.timeseries_dataset_from_array(\n",
    "      data=data,\n",
    "      targets=None,\n",
    "      sequence_length=self.total_window_size,\n",
    "      sequence_stride=1,\n",
    "      shuffle=True,\n",
    "      batch_size=32,)\n",
    "\n",
    "  ds = ds.map(self.split_window)\n",
    "\n",
    "  return ds\n",
    "\n",
    "WindowGenerator.make_dataset = make_dataset"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "LvsxQwJaCift"
   },
   "source": [
    "`WindowGenerator` 객체는 훈련, 검증, 테스트 데이터를 보존합니다.\n",
    "\n",
    "앞에서 정의한 `make_dataset` 메서드를 사용하여 `tf.data.Dataset`로 액세스하기 위한 속성을 추가합니다. 또한 쉽게 액세스하고 플로팅할 수 있도록 표준 예제 배치를 추가합니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:55:04.927583Z",
     "iopub.status.busy": "2022-12-14T22:55:04.927058Z",
     "iopub.status.idle": "2022-12-14T22:55:04.932595Z",
     "shell.execute_reply": "2022-12-14T22:55:04.931949Z"
    },
    "id": "2jZ2KkqGCfzu"
   },
   "outputs": [],
   "source": [
    "@property\n",
    "def train(self):\n",
    "  return self.make_dataset(self.train_df)\n",
    "\n",
    "@property\n",
    "def val(self):\n",
    "  return self.make_dataset(self.val_df)\n",
    "\n",
    "@property\n",
    "def test(self):\n",
    "  return self.make_dataset(self.test_df)\n",
    "\n",
    "@property\n",
    "def example(self):\n",
    "  \"\"\"Get and cache an example batch of `inputs, labels` for plotting.\"\"\"\n",
    "  result = getattr(self, '_example', None)\n",
    "  if result is None:\n",
    "    # No example batch was found, so get one from the `.train` dataset\n",
    "    result = next(iter(self.train))\n",
    "    # And cache it for next time\n",
    "    self._example = result\n",
    "  return result\n",
    "\n",
    "WindowGenerator.train = train\n",
    "WindowGenerator.val = val\n",
    "WindowGenerator.test = test\n",
    "WindowGenerator.example = example"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "fF_Vj6Iw3Y2w"
   },
   "source": [
    "이제 `WindowGenerator` 객체가 `tf.data.Dataset` 객체에 대한 액세스 권한을 부여하므로 데이터를 쉽게 반복할 수 있습니다.\n",
    "\n",
    "`Dataset.element_spec` 속성은 데이터세트 요소의 구조, 데이터 유형, 형상을 알려줍니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:55:04.935767Z",
     "iopub.status.busy": "2022-12-14T22:55:04.935496Z",
     "iopub.status.idle": "2022-12-14T22:55:05.077081Z",
     "shell.execute_reply": "2022-12-14T22:55:05.076285Z"
    },
    "id": "daJ0-U383YVs"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(TensorSpec(shape=(None, 6, 19), dtype=tf.float32, name=None),\n",
       " TensorSpec(shape=(None, 1, 1), dtype=tf.float32, name=None))"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Each element is an (inputs, label) pair.\n",
    "w2.train.element_spec"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "XKTx3_Z7ua-n"
   },
   "source": [
    "`Dataset`를 반복하면 구체적인 배치가 생성됩니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:55:05.080848Z",
     "iopub.status.busy": "2022-12-14T22:55:05.080547Z",
     "iopub.status.idle": "2022-12-14T22:55:05.207023Z",
     "shell.execute_reply": "2022-12-14T22:55:05.206099Z"
    },
    "id": "6gtKXEgf4Iml"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Inputs shape (batch, time, features): (32, 6, 19)\n",
      "Labels shape (batch, time, features): (32, 1, 1)\n"
     ]
    }
   ],
   "source": [
    "for example_inputs, example_labels in w2.train.take(1):\n",
    "  print(f'Inputs shape (batch, time, features): {example_inputs.shape}')\n",
    "  print(f'Labels shape (batch, time, features): {example_labels.shape}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "LyuGuJUgjUK3"
   },
   "source": [
    "## 단일 스텝 모델\n",
    "\n",
    "이러한 종류의 데이터를 기반으로 빌드할 수 있는 가장 간단한 모델은 현재 조건만을 기초로 1 타임스텝(1시간) 후의 단일 특성 값을 예측하는 모델입니다.\n",
    "\n",
    "따라서 1시간 미래의 `T (degC)` 값을 예측하는 모델을 빌드하는 것으로 시작하겠습니다.\n",
    "\n",
    "![Predict the next time step](images/narrow_window.png)\n",
    "\n",
    "다음과 같은 단일 스텝 `(input, label)` 쌍을 생성하도록 `WindowGenerator` 객체를 구성합니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:55:05.210621Z",
     "iopub.status.busy": "2022-12-14T22:55:05.210268Z",
     "iopub.status.idle": "2022-12-14T22:55:05.216330Z",
     "shell.execute_reply": "2022-12-14T22:55:05.215401Z"
    },
    "id": "G5QX1G1JTPCr"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Total window size: 2\n",
       "Input indices: [0]\n",
       "Label indices: [1]\n",
       "Label column name(s): ['T (degC)']"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "single_step_window = WindowGenerator(\n",
    "    input_width=1, label_width=1, shift=1,\n",
    "    label_columns=['T (degC)'])\n",
    "single_step_window"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "RKTm8ajVGw4N"
   },
   "source": [
    "`window` 객체는 훈련, 검증 및 테스트 세트로부터 `tf.data.Datasets`를 생성하므로 데이터 배치를 쉽게 반복할 수 있습니다.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:55:05.220019Z",
     "iopub.status.busy": "2022-12-14T22:55:05.219587Z",
     "iopub.status.idle": "2022-12-14T22:55:05.341581Z",
     "shell.execute_reply": "2022-12-14T22:55:05.340751Z"
    },
    "id": "Do4ILUaBF8oc"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Inputs shape (batch, time, features): (32, 1, 19)\n",
      "Labels shape (batch, time, features): (32, 1, 1)\n"
     ]
    }
   ],
   "source": [
    "for example_inputs, example_labels in single_step_window.train.take(1):\n",
    "  print(f'Inputs shape (batch, time, features): {example_inputs.shape}')\n",
    "  print(f'Labels shape (batch, time, features): {example_labels.shape}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "D1bbPiR3VAm_"
   },
   "source": [
    "### 기준\n",
    "\n",
    "훈련 가능한 모델을 빌드하기 전에 나중에 더 복잡한 모델과 비교하기 위한 포인트로 성능 기준을 갖는 것이 좋습니다.\n",
    "\n",
    "첫 번째 작업은 모든 특성의 현재 값을 고려하여 1시간 후의 온도를 예측하는 것입니다. 현재 값에는 현재 온도가 포함됩니다.\n",
    "\n",
    "따라서 예측으로 현재 온도를 반환하여 \"변화 없음\"을 예측하는 모델로 시작하겠습니다. 온도가 천천히 변하기 때문에 이것은 합리적인 기준입니다. 물론, 더 미래로 들어가면 이 기준의 예측 효과를 떨어질 것입니다.\n",
    "\n",
    "![Send the input to the output](images/baseline.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:55:05.345658Z",
     "iopub.status.busy": "2022-12-14T22:55:05.345029Z",
     "iopub.status.idle": "2022-12-14T22:55:05.350067Z",
     "shell.execute_reply": "2022-12-14T22:55:05.349389Z"
    },
    "id": "9TybQaIsi3yg"
   },
   "outputs": [],
   "source": [
    "class Baseline(tf.keras.Model):\n",
    "  def __init__(self, label_index=None):\n",
    "    super().__init__()\n",
    "    self.label_index = label_index\n",
    "\n",
    "  def call(self, inputs):\n",
    "    if self.label_index is None:\n",
    "      return inputs\n",
    "    result = inputs[:, :, self.label_index]\n",
    "    return result[:, :, tf.newaxis]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "0vb3f948i8p8"
   },
   "source": [
    "이 모델을 인스턴스화하고 평가합니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:55:05.354033Z",
     "iopub.status.busy": "2022-12-14T22:55:05.353313Z",
     "iopub.status.idle": "2022-12-14T22:55:06.908644Z",
     "shell.execute_reply": "2022-12-14T22:55:06.907572Z"
    },
    "id": "IS3-QKc4sX0D"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/439 [..............................] - ETA: 1:25 - loss: 0.0102 - mean_absolute_error: 0.0725"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 26/439 [>.............................] - ETA: 0s - loss: 0.0119 - mean_absolute_error: 0.0770  "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 53/439 [==>...........................] - ETA: 0s - loss: 0.0131 - mean_absolute_error: 0.0787"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 81/439 [====>.........................] - ETA: 0s - loss: 0.0125 - mean_absolute_error: 0.0779"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "110/439 [======>.......................] - ETA: 0s - loss: 0.0125 - mean_absolute_error: 0.0777"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "137/439 [========>.....................] - ETA: 0s - loss: 0.0126 - mean_absolute_error: 0.0781"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "164/439 [==========>...................] - ETA: 0s - loss: 0.0123 - mean_absolute_error: 0.0773"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "191/439 [============>.................] - ETA: 0s - loss: 0.0124 - mean_absolute_error: 0.0774"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "218/439 [=============>................] - ETA: 0s - loss: 0.0126 - mean_absolute_error: 0.0777"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "245/439 [===============>..............] - ETA: 0s - loss: 0.0126 - mean_absolute_error: 0.0781"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "273/439 [=================>............] - ETA: 0s - loss: 0.0126 - mean_absolute_error: 0.0782"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "301/439 [===================>..........] - ETA: 0s - loss: 0.0125 - mean_absolute_error: 0.0781"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "330/439 [=====================>........] - ETA: 0s - loss: 0.0125 - mean_absolute_error: 0.0780"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "358/439 [=======================>......] - ETA: 0s - loss: 0.0126 - mean_absolute_error: 0.0781"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "386/439 [=========================>....] - ETA: 0s - loss: 0.0126 - mean_absolute_error: 0.0781"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "414/439 [===========================>..] - ETA: 0s - loss: 0.0127 - mean_absolute_error: 0.0784"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "439/439 [==============================] - 1s 2ms/step - loss: 0.0128 - mean_absolute_error: 0.0785\n"
     ]
    }
   ],
   "source": [
    "baseline = Baseline(label_index=column_indices['T (degC)'])\n",
    "\n",
    "baseline.compile(loss=tf.keras.losses.MeanSquaredError(),\n",
    "                 metrics=[tf.keras.metrics.MeanAbsoluteError()])\n",
    "\n",
    "val_performance = {}\n",
    "performance = {}\n",
    "val_performance['Baseline'] = baseline.evaluate(single_step_window.val)\n",
    "performance['Baseline'] = baseline.evaluate(single_step_window.test, verbose=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "nhBxQcCSs7Ec"
   },
   "source": [
    "몇 가지 성능 메트릭을 출력했지만 모델이 얼마나 잘 동작하는지에 대한 느낌은 주지 않습니다.\n",
    "\n",
    "`WindowGenerator`에는 플롯 메서드가 있지만 단일 샘플만으로는 플롯이 그다지 흥미롭지 않습니다.\n",
    "\n",
    "따라서 한 번에 24시간 연속 입력 및 레이블 창을 생성하는 더 넓은 `WindowGenerator`를 만듭니다. 새로운 `wide_window`는 모델이 작동하는 방식을 변경하지 않습니다. 이 모델은 단일 입력 타임스텝을 기반으로 1시간 미래를을 예측합니다. 여기서 `time` 축은 `batch` 축과 같은 역할을 합니다. 각 예측은 타임스텝 사이의 상호 작용 없이 독립적으로 이루어집니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:55:06.913414Z",
     "iopub.status.busy": "2022-12-14T22:55:06.912663Z",
     "iopub.status.idle": "2022-12-14T22:55:06.919176Z",
     "shell.execute_reply": "2022-12-14T22:55:06.918250Z"
    },
    "id": "C8jNR5uuJ5Zp"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Total window size: 25\n",
       "Input indices: [ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23]\n",
       "Label indices: [ 1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24]\n",
       "Label column name(s): ['T (degC)']"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wide_window = WindowGenerator(\n",
    "    input_width=24, label_width=24, shift=1,\n",
    "    label_columns=['T (degC)'])\n",
    "\n",
    "wide_window"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "ZAnj7CFZkuYv"
   },
   "source": [
    "이 확장된 창은 어떠한 코드 변경 없이 동일한 `baseline` 모델에 직접 전달할 수 있습니다. 이는 입력과 레이블이 동일한 수의 타임스텝을 가지며 기준이 입력을 출력으로 전달하기 때문에 가능합니다.\n",
    "\n",
    "![One prediction 1h into the future, ever hour.](images/last_window.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:55:06.922922Z",
     "iopub.status.busy": "2022-12-14T22:55:06.922137Z",
     "iopub.status.idle": "2022-12-14T22:55:07.032251Z",
     "shell.execute_reply": "2022-12-14T22:55:07.031488Z"
    },
    "id": "sGKdvdg087qs"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Input shape: (32, 24, 19)\n",
      "Output shape: (32, 24, 1)\n"
     ]
    }
   ],
   "source": [
    "print('Input shape:', wide_window.example[0].shape)\n",
    "print('Output shape:', baseline(wide_window.example[0]).shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "SKqQHX1K0JW-"
   },
   "source": [
    "기준 모델의 예측을 플롯하면 1시간씩 오른쪽으로 이동한 단순한 레이블임을 알 수 있습니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:55:07.035829Z",
     "iopub.status.busy": "2022-12-14T22:55:07.035535Z",
     "iopub.status.idle": "2022-12-14T22:55:07.464785Z",
     "shell.execute_reply": "2022-12-14T22:55:07.464091Z"
    },
    "id": "jQyAPVLgWTOZ"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x800 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "wide_window.plot(baseline)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "e93TLUhfAVg2"
   },
   "source": [
    "위의 세 가지 예제 플롯에서 단일 스텝 모델은 24시간 동안 실행됩니다. 이에 관해 몇 가지 설명이 필요합니다.\n",
    "\n",
    "- 파란색 `Inputs` 라인은 각 타임스텝의 입력 온도를 보여줍니다. 이 모델은 모든 특성을 수신하며 이 플롯은 온도만 표시합니다.\n",
    "- 녹색 `Labels` 점은 목표 예측 값을 나타냅니다. 이러한 점은 입력 시간이 아니라 예측 시간에 표시됩니다. 레이벨의 범위가 입력에 상대적으로 한 스텝 이동하는 이유가 여기에 있습니다.\n",
    "- 주황색 `Predictions` 십자는 각 출력 타임스텝에 대한 모델의 예측입니다. 모델이 완벽하게 예측하는 경우 예측은 `Labels` 바로 위에 놓여집니다."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "E4aOJScj52Yu"
   },
   "source": [
    "### 선형 모델\n",
    "\n",
    "이 작업에 적용할 수 있는 가장 간단한 **훈련 가능한** 모델은 입력과 출력 사이에 선형 변환을 삽입하는 것입니다. 이 경우 타임스텝의 출력은 해당 스텝에만 의존합니다.\n",
    "\n",
    "![A single step prediction](images/narrow_window.png)\n",
    "\n",
    "`activation` 세트가 없는 `tf.keras.layers.Dense`는 선형 모델입니다. 레이어는 데이터의 마지막 축을 `(batch, time, inputs)`에서 `(batch, time, units)`로만 변환하며, `batch` 및 `time` 축의 모든 항목에 독립적으로 적용됩니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:55:07.469234Z",
     "iopub.status.busy": "2022-12-14T22:55:07.468980Z",
     "iopub.status.idle": "2022-12-14T22:55:07.478749Z",
     "shell.execute_reply": "2022-12-14T22:55:07.478073Z"
    },
    "id": "6341OXuQ5xA9"
   },
   "outputs": [],
   "source": [
    "linear = tf.keras.Sequential([\n",
    "    tf.keras.layers.Dense(units=1)\n",
    "])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:55:07.482139Z",
     "iopub.status.busy": "2022-12-14T22:55:07.481475Z",
     "iopub.status.idle": "2022-12-14T22:55:08.103039Z",
     "shell.execute_reply": "2022-12-14T22:55:08.102023Z"
    },
    "id": "KwaOM8RucUSn"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Input shape: (32, 1, 19)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Output shape: (32, 1, 1)\n"
     ]
    }
   ],
   "source": [
    "print('Input shape:', single_step_window.example[0].shape)\n",
    "print('Output shape:', linear(single_step_window.example[0]).shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "OMZTYIj3bYLg"
   },
   "source": [
    "이 튜토리얼은 많은 모델을 훈련하므로 훈련 절차를 하나의 함수 패키지로 만듭니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:55:08.106666Z",
     "iopub.status.busy": "2022-12-14T22:55:08.106408Z",
     "iopub.status.idle": "2022-12-14T22:55:08.111662Z",
     "shell.execute_reply": "2022-12-14T22:55:08.110946Z"
    },
    "id": "CbCL6VIrk-Gt"
   },
   "outputs": [],
   "source": [
    "MAX_EPOCHS = 20\n",
    "\n",
    "def compile_and_fit(model, window, patience=2):\n",
    "  early_stopping = tf.keras.callbacks.EarlyStopping(monitor='val_loss',\n",
    "                                                    patience=patience,\n",
    "                                                    mode='min')\n",
    "\n",
    "  model.compile(loss=tf.keras.losses.MeanSquaredError(),\n",
    "                optimizer=tf.keras.optimizers.Adam(),\n",
    "                metrics=[tf.keras.metrics.MeanAbsoluteError()])\n",
    "\n",
    "  history = model.fit(window.train, epochs=MAX_EPOCHS,\n",
    "                      validation_data=window.val,\n",
    "                      callbacks=[early_stopping])\n",
    "  return history"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "OobVjM-schwj"
   },
   "source": [
    "모델을 훈련하고 성능을 평가합니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:55:08.114884Z",
     "iopub.status.busy": "2022-12-14T22:55:08.114650Z",
     "iopub.status.idle": "2022-12-14T22:56:01.757901Z",
     "shell.execute_reply": "2022-12-14T22:56:01.757055Z"
    },
    "id": "9agbz2qB9bLS"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/20\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "   1/1534 [..............................] - ETA: 18:04 - loss: 4.2131 - mean_absolute_error: 1.5781"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  20/1534 [..............................] - ETA: 4s - loss: 6.2882 - mean_absolute_error: 2.0040   "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  40/1534 [..............................] - ETA: 3s - loss: 5.8004 - mean_absolute_error: 1.9310"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  60/1534 [>.............................] - ETA: 3s - loss: 5.3894 - mean_absolute_error: 1.8501"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  81/1534 [>.............................] - ETA: 3s - loss: 4.9586 - mean_absolute_error: 1.7736"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 101/1534 [>.............................] - ETA: 3s - loss: 4.6297 - mean_absolute_error: 1.7087"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 121/1534 [=>............................] - ETA: 3s - loss: 4.3185 - mean_absolute_error: 1.6438"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 142/1534 [=>............................] - ETA: 3s - loss: 3.9882 - mean_absolute_error: 1.5713"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 164/1534 [==>...........................] - ETA: 3s - loss: 3.6969 - mean_absolute_error: 1.5043"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 185/1534 [==>...........................] - ETA: 3s - loss: 3.4349 - mean_absolute_error: 1.4396"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 205/1534 [===>..........................] - ETA: 3s - loss: 3.2087 - mean_absolute_error: 1.3808"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 225/1534 [===>..........................] - ETA: 3s - loss: 2.9975 - mean_absolute_error: 1.3231"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 245/1534 [===>..........................] - ETA: 3s - loss: 2.8155 - mean_absolute_error: 1.2718"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 265/1534 [====>.........................] - ETA: 3s - loss: 2.6488 - mean_absolute_error: 1.2225"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 285/1534 [====>.........................] - ETA: 3s - loss: 2.4978 - mean_absolute_error: 1.1756"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 304/1534 [====>.........................] - ETA: 3s - loss: 2.3666 - mean_absolute_error: 1.1330"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 325/1534 [=====>........................] - ETA: 3s - loss: 2.2335 - mean_absolute_error: 1.0888"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 345/1534 [=====>........................] - ETA: 3s - loss: 2.1216 - mean_absolute_error: 1.0515"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 365/1534 [======>.......................] - ETA: 2s - loss: 2.0190 - mean_absolute_error: 1.0158"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 385/1534 [======>.......................] - ETA: 2s - loss: 1.9254 - mean_absolute_error: 0.9824"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 406/1534 [======>.......................] - ETA: 2s - loss: 1.8349 - mean_absolute_error: 0.9487"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 427/1534 [=======>......................] - ETA: 2s - loss: 1.7527 - mean_absolute_error: 0.9182"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 447/1534 [=======>......................] - ETA: 2s - loss: 1.6807 - mean_absolute_error: 0.8908"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 468/1534 [========>.....................] - ETA: 2s - loss: 1.6104 - mean_absolute_error: 0.8629"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 489/1534 [========>.....................] - ETA: 2s - loss: 1.5454 - mean_absolute_error: 0.8366"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 510/1534 [========>.....................] - ETA: 2s - loss: 1.4852 - mean_absolute_error: 0.8117"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 531/1534 [=========>....................] - ETA: 2s - loss: 1.4298 - mean_absolute_error: 0.7889"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 552/1534 [=========>....................] - ETA: 2s - loss: 1.3783 - mean_absolute_error: 0.7672"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 574/1534 [==========>...................] - ETA: 2s - loss: 1.3277 - mean_absolute_error: 0.7453"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 595/1534 [==========>...................] - ETA: 2s - loss: 1.2828 - mean_absolute_error: 0.7258"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 616/1534 [===========>..................] - ETA: 2s - loss: 1.2408 - mean_absolute_error: 0.7072"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 638/1534 [===========>..................] - ETA: 2s - loss: 1.1997 - mean_absolute_error: 0.6887"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 659/1534 [===========>..................] - ETA: 2s - loss: 1.1628 - mean_absolute_error: 0.6720"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 680/1534 [============>.................] - ETA: 2s - loss: 1.1281 - mean_absolute_error: 0.6561"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 701/1534 [============>.................] - ETA: 2s - loss: 1.0953 - mean_absolute_error: 0.6408"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 722/1534 [=============>................] - ETA: 2s - loss: 1.0643 - mean_absolute_error: 0.6262"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 744/1534 [=============>................] - ETA: 1s - loss: 1.0338 - mean_absolute_error: 0.6116"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 765/1534 [=============>................] - ETA: 1s - loss: 1.0061 - mean_absolute_error: 0.5982"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 787/1534 [==============>...............] - ETA: 1s - loss: 0.9787 - mean_absolute_error: 0.5850"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 808/1534 [==============>...............] - ETA: 1s - loss: 0.9538 - mean_absolute_error: 0.5728"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 829/1534 [===============>..............] - ETA: 1s - loss: 0.9302 - mean_absolute_error: 0.5611"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 850/1534 [===============>..............] - ETA: 1s - loss: 0.9076 - mean_absolute_error: 0.5497"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 870/1534 [================>.............] - ETA: 1s - loss: 0.8873 - mean_absolute_error: 0.5396"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 891/1534 [================>.............] - ETA: 1s - loss: 0.8667 - mean_absolute_error: 0.5291"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 912/1534 [================>.............] - ETA: 1s - loss: 0.8471 - mean_absolute_error: 0.5191"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 933/1534 [=================>............] - ETA: 1s - loss: 0.8284 - mean_absolute_error: 0.5095"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 955/1534 [=================>............] - ETA: 1s - loss: 0.8097 - mean_absolute_error: 0.5000"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 976/1534 [==================>...........] - ETA: 1s - loss: 0.7926 - mean_absolute_error: 0.4913"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 997/1534 [==================>...........] - ETA: 1s - loss: 0.7762 - mean_absolute_error: 0.4829"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1018/1534 [==================>...........] - ETA: 1s - loss: 0.7605 - mean_absolute_error: 0.4748"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1038/1534 [===================>..........] - ETA: 1s - loss: 0.7461 - mean_absolute_error: 0.4674"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1060/1534 [===================>..........] - ETA: 1s - loss: 0.7309 - mean_absolute_error: 0.4595"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1080/1534 [====================>.........] - ETA: 1s - loss: 0.7176 - mean_absolute_error: 0.4527"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1100/1534 [====================>.........] - ETA: 1s - loss: 0.7048 - mean_absolute_error: 0.4459"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1120/1534 [====================>.........] - ETA: 1s - loss: 0.6925 - mean_absolute_error: 0.4396"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1141/1534 [=====================>........] - ETA: 0s - loss: 0.6800 - mean_absolute_error: 0.4331"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1161/1534 [=====================>........] - ETA: 0s - loss: 0.6685 - mean_absolute_error: 0.4271"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1182/1534 [======================>.......] - ETA: 0s - loss: 0.6568 - mean_absolute_error: 0.4209"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1203/1534 [======================>.......] - ETA: 0s - loss: 0.6456 - mean_absolute_error: 0.4151"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1224/1534 [======================>.......] - ETA: 0s - loss: 0.6347 - mean_absolute_error: 0.4094"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1245/1534 [=======================>......] - ETA: 0s - loss: 0.6242 - mean_absolute_error: 0.4040"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1265/1534 [=======================>......] - ETA: 0s - loss: 0.6145 - mean_absolute_error: 0.3989"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1286/1534 [========================>.....] - ETA: 0s - loss: 0.6047 - mean_absolute_error: 0.3938"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1307/1534 [========================>.....] - ETA: 0s - loss: 0.5952 - mean_absolute_error: 0.3888"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1328/1534 [========================>.....] - ETA: 0s - loss: 0.5859 - mean_absolute_error: 0.3839"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1349/1534 [=========================>....] - ETA: 0s - loss: 0.5770 - mean_absolute_error: 0.3791"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1370/1534 [=========================>....] - ETA: 0s - loss: 0.5683 - mean_absolute_error: 0.3745"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1390/1534 [==========================>...] - ETA: 0s - loss: 0.5603 - mean_absolute_error: 0.3703"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1410/1534 [==========================>...] - ETA: 0s - loss: 0.5525 - mean_absolute_error: 0.3662"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1431/1534 [==========================>...] - ETA: 0s - loss: 0.5446 - mean_absolute_error: 0.3621"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1451/1534 [===========================>..] - ETA: 0s - loss: 0.5372 - mean_absolute_error: 0.3582"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1471/1534 [===========================>..] - ETA: 0s - loss: 0.5301 - mean_absolute_error: 0.3544"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1491/1534 [============================>.] - ETA: 0s - loss: 0.5231 - mean_absolute_error: 0.3507"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1511/1534 [============================>.] - ETA: 0s - loss: 0.5164 - mean_absolute_error: 0.3471"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1532/1534 [============================>.] - ETA: 0s - loss: 0.5095 - mean_absolute_error: 0.3435"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1534/1534 [==============================] - 5s 3ms/step - loss: 0.5091 - mean_absolute_error: 0.3433 - val_loss: 0.0114 - val_mean_absolute_error: 0.0803\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 2/20\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "   1/1534 [..............................] - ETA: 39s - loss: 0.0050 - mean_absolute_error: 0.0572"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  20/1534 [..............................] - ETA: 4s - loss: 0.0114 - mean_absolute_error: 0.0803 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  41/1534 [..............................] - ETA: 3s - loss: 0.0109 - mean_absolute_error: 0.0795"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  61/1534 [>.............................] - ETA: 3s - loss: 0.0118 - mean_absolute_error: 0.0814"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  82/1534 [>.............................] - ETA: 3s - loss: 0.0116 - mean_absolute_error: 0.0804"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 102/1534 [>.............................] - ETA: 3s - loss: 0.0114 - mean_absolute_error: 0.0799"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 124/1534 [=>............................] - ETA: 3s - loss: 0.0114 - mean_absolute_error: 0.0800"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 146/1534 [=>............................] - ETA: 3s - loss: 0.0117 - mean_absolute_error: 0.0804"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 167/1534 [==>...........................] - ETA: 3s - loss: 0.0114 - mean_absolute_error: 0.0799"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 188/1534 [==>...........................] - ETA: 3s - loss: 0.0114 - mean_absolute_error: 0.0797"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 209/1534 [===>..........................] - ETA: 3s - loss: 0.0113 - mean_absolute_error: 0.0795"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 229/1534 [===>..........................] - ETA: 3s - loss: 0.0114 - mean_absolute_error: 0.0798"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 250/1534 [===>..........................] - ETA: 3s - loss: 0.0114 - mean_absolute_error: 0.0798"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 271/1534 [====>.........................] - ETA: 3s - loss: 0.0113 - mean_absolute_error: 0.0794"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 292/1534 [====>.........................] - ETA: 3s - loss: 0.0113 - mean_absolute_error: 0.0794"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 313/1534 [=====>........................] - ETA: 3s - loss: 0.0113 - mean_absolute_error: 0.0791"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 334/1534 [=====>........................] - ETA: 2s - loss: 0.0112 - mean_absolute_error: 0.0792"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 355/1534 [=====>........................] - ETA: 2s - loss: 0.0112 - mean_absolute_error: 0.0792"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 376/1534 [======>.......................] - ETA: 2s - loss: 0.0111 - mean_absolute_error: 0.0790"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 397/1534 [======>.......................] - ETA: 2s - loss: 0.0111 - mean_absolute_error: 0.0790"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 418/1534 [=======>......................] - ETA: 2s - loss: 0.0111 - mean_absolute_error: 0.0788"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 439/1534 [=======>......................] - ETA: 2s - loss: 0.0110 - mean_absolute_error: 0.0787"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 460/1534 [=======>......................] - ETA: 2s - loss: 0.0110 - mean_absolute_error: 0.0788"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 481/1534 [========>.....................] - ETA: 2s - loss: 0.0111 - mean_absolute_error: 0.0789"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 502/1534 [========>.....................] - ETA: 2s - loss: 0.0111 - mean_absolute_error: 0.0789"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 523/1534 [=========>....................] - ETA: 2s - loss: 0.0111 - mean_absolute_error: 0.0788"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 543/1534 [=========>....................] - ETA: 2s - loss: 0.0111 - mean_absolute_error: 0.0787"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 563/1534 [==========>...................] - ETA: 2s - loss: 0.0110 - mean_absolute_error: 0.0785"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 584/1534 [==========>...................] - ETA: 2s - loss: 0.0110 - mean_absolute_error: 0.0786"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 605/1534 [==========>...................] - ETA: 2s - loss: 0.0110 - mean_absolute_error: 0.0786"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 626/1534 [===========>..................] - ETA: 2s - loss: 0.0111 - mean_absolute_error: 0.0787"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 647/1534 [===========>..................] - ETA: 2s - loss: 0.0111 - mean_absolute_error: 0.0787"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 667/1534 [============>.................] - ETA: 2s - loss: 0.0111 - mean_absolute_error: 0.0788"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 688/1534 [============>.................] - ETA: 2s - loss: 0.0111 - mean_absolute_error: 0.0786"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 708/1534 [============>.................] - ETA: 2s - loss: 0.0111 - mean_absolute_error: 0.0785"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 728/1534 [=============>................] - ETA: 1s - loss: 0.0111 - mean_absolute_error: 0.0786"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 748/1534 [=============>................] - ETA: 1s - loss: 0.0111 - mean_absolute_error: 0.0785"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 768/1534 [==============>...............] - ETA: 1s - loss: 0.0110 - mean_absolute_error: 0.0785"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 788/1534 [==============>...............] - ETA: 1s - loss: 0.0110 - mean_absolute_error: 0.0784"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 808/1534 [==============>...............] - ETA: 1s - loss: 0.0110 - mean_absolute_error: 0.0784"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 829/1534 [===============>..............] - ETA: 1s - loss: 0.0110 - mean_absolute_error: 0.0784"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 849/1534 [===============>..............] - ETA: 1s - loss: 0.0110 - mean_absolute_error: 0.0784"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 870/1534 [================>.............] - ETA: 1s - loss: 0.0110 - mean_absolute_error: 0.0783"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 890/1534 [================>.............] - ETA: 1s - loss: 0.0110 - mean_absolute_error: 0.0781"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 911/1534 [================>.............] - ETA: 1s - loss: 0.0110 - mean_absolute_error: 0.0781"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 932/1534 [=================>............] - ETA: 1s - loss: 0.0109 - mean_absolute_error: 0.0780"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 953/1534 [=================>............] - ETA: 1s - loss: 0.0110 - mean_absolute_error: 0.0780"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 974/1534 [==================>...........] - ETA: 1s - loss: 0.0109 - mean_absolute_error: 0.0779"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 995/1534 [==================>...........] - ETA: 1s - loss: 0.0109 - mean_absolute_error: 0.0779"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1016/1534 [==================>...........] - ETA: 1s - loss: 0.0109 - mean_absolute_error: 0.0778"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1037/1534 [===================>..........] - ETA: 1s - loss: 0.0109 - mean_absolute_error: 0.0777"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1057/1534 [===================>..........] - ETA: 1s - loss: 0.0109 - mean_absolute_error: 0.0777"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1077/1534 [====================>.........] - ETA: 1s - loss: 0.0108 - mean_absolute_error: 0.0776"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1097/1534 [====================>.........] - ETA: 1s - loss: 0.0108 - mean_absolute_error: 0.0776"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1118/1534 [====================>.........] - ETA: 1s - loss: 0.0108 - mean_absolute_error: 0.0776"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1139/1534 [=====================>........] - ETA: 0s - loss: 0.0108 - mean_absolute_error: 0.0775"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1160/1534 [=====================>........] - ETA: 0s - loss: 0.0108 - mean_absolute_error: 0.0774"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1181/1534 [======================>.......] - ETA: 0s - loss: 0.0108 - mean_absolute_error: 0.0774"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1202/1534 [======================>.......] - ETA: 0s - loss: 0.0108 - mean_absolute_error: 0.0773"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1222/1534 [======================>.......] - ETA: 0s - loss: 0.0107 - mean_absolute_error: 0.0772"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1243/1534 [=======================>......] - ETA: 0s - loss: 0.0108 - mean_absolute_error: 0.0772"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1263/1534 [=======================>......] - ETA: 0s - loss: 0.0108 - mean_absolute_error: 0.0772"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1283/1534 [========================>.....] - ETA: 0s - loss: 0.0107 - mean_absolute_error: 0.0772"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1303/1534 [========================>.....] - ETA: 0s - loss: 0.0107 - mean_absolute_error: 0.0771"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1323/1534 [========================>.....] - ETA: 0s - loss: 0.0107 - mean_absolute_error: 0.0770"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1344/1534 [=========================>....] - ETA: 0s - loss: 0.0106 - mean_absolute_error: 0.0769"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1365/1534 [=========================>....] - ETA: 0s - loss: 0.0106 - mean_absolute_error: 0.0768"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1386/1534 [==========================>...] - ETA: 0s - loss: 0.0106 - mean_absolute_error: 0.0769"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1407/1534 [==========================>...] - ETA: 0s - loss: 0.0106 - mean_absolute_error: 0.0768"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1428/1534 [==========================>...] - ETA: 0s - loss: 0.0106 - mean_absolute_error: 0.0768"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1449/1534 [===========================>..] - ETA: 0s - loss: 0.0106 - mean_absolute_error: 0.0767"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1470/1534 [===========================>..] - ETA: 0s - loss: 0.0106 - mean_absolute_error: 0.0767"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1491/1534 [============================>.] - ETA: 0s - loss: 0.0106 - mean_absolute_error: 0.0766"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1512/1534 [============================>.] - ETA: 0s - loss: 0.0106 - mean_absolute_error: 0.0766"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1533/1534 [============================>.] - ETA: 0s - loss: 0.0106 - mean_absolute_error: 0.0765"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1534/1534 [==============================] - 5s 3ms/step - loss: 0.0106 - mean_absolute_error: 0.0765 - val_loss: 0.0098 - val_mean_absolute_error: 0.0736\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 3/20\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "   1/1534 [..............................] - ETA: 42s - loss: 0.0084 - mean_absolute_error: 0.0677"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  21/1534 [..............................] - ETA: 3s - loss: 0.0101 - mean_absolute_error: 0.0753 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  42/1534 [..............................] - ETA: 3s - loss: 0.0098 - mean_absolute_error: 0.0740"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  63/1534 [>.............................] - ETA: 3s - loss: 0.0105 - mean_absolute_error: 0.0755"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  84/1534 [>.............................] - ETA: 3s - loss: 0.0103 - mean_absolute_error: 0.0748"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 104/1534 [=>............................] - ETA: 3s - loss: 0.0100 - mean_absolute_error: 0.0744"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 125/1534 [=>............................] - ETA: 3s - loss: 0.0101 - mean_absolute_error: 0.0744"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 147/1534 [=>............................] - ETA: 3s - loss: 0.0103 - mean_absolute_error: 0.0750"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 168/1534 [==>...........................] - ETA: 3s - loss: 0.0101 - mean_absolute_error: 0.0745"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 189/1534 [==>...........................] - ETA: 3s - loss: 0.0100 - mean_absolute_error: 0.0743"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 210/1534 [===>..........................] - ETA: 3s - loss: 0.0100 - mean_absolute_error: 0.0741"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 231/1534 [===>..........................] - ETA: 3s - loss: 0.0100 - mean_absolute_error: 0.0740"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 252/1534 [===>..........................] - ETA: 3s - loss: 0.0100 - mean_absolute_error: 0.0739"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 273/1534 [====>.........................] - ETA: 3s - loss: 0.0100 - mean_absolute_error: 0.0738"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 294/1534 [====>.........................] - ETA: 3s - loss: 0.0100 - mean_absolute_error: 0.0738"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 314/1534 [=====>........................] - ETA: 3s - loss: 0.0099 - mean_absolute_error: 0.0734"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 335/1534 [=====>........................] - ETA: 2s - loss: 0.0099 - mean_absolute_error: 0.0734"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 356/1534 [=====>........................] - ETA: 2s - loss: 0.0099 - mean_absolute_error: 0.0736"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 377/1534 [======>.......................] - ETA: 2s - loss: 0.0098 - mean_absolute_error: 0.0734"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 398/1534 [======>.......................] - ETA: 2s - loss: 0.0098 - mean_absolute_error: 0.0732"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 419/1534 [=======>......................] - ETA: 2s - loss: 0.0097 - mean_absolute_error: 0.0729"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 439/1534 [=======>......................] - ETA: 2s - loss: 0.0097 - mean_absolute_error: 0.0729"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 460/1534 [=======>......................] - ETA: 2s - loss: 0.0098 - mean_absolute_error: 0.0731"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 481/1534 [========>.....................] - ETA: 2s - loss: 0.0098 - mean_absolute_error: 0.0732"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 502/1534 [========>.....................] - ETA: 2s - loss: 0.0098 - mean_absolute_error: 0.0733"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 523/1534 [=========>....................] - ETA: 2s - loss: 0.0099 - mean_absolute_error: 0.0734"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 543/1534 [=========>....................] - ETA: 2s - loss: 0.0099 - mean_absolute_error: 0.0732"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 564/1534 [==========>...................] - ETA: 2s - loss: 0.0098 - mean_absolute_error: 0.0731"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 585/1534 [==========>...................] - ETA: 2s - loss: 0.0098 - mean_absolute_error: 0.0733"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 606/1534 [==========>...................] - ETA: 2s - loss: 0.0099 - mean_absolute_error: 0.0733"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 626/1534 [===========>..................] - ETA: 2s - loss: 0.0099 - mean_absolute_error: 0.0734"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 646/1534 [===========>..................] - ETA: 2s - loss: 0.0099 - mean_absolute_error: 0.0734"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 666/1534 [============>.................] - ETA: 2s - loss: 0.0099 - mean_absolute_error: 0.0734"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 686/1534 [============>.................] - ETA: 2s - loss: 0.0099 - mean_absolute_error: 0.0734"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 707/1534 [============>.................] - ETA: 2s - loss: 0.0099 - mean_absolute_error: 0.0733"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 728/1534 [=============>................] - ETA: 1s - loss: 0.0099 - mean_absolute_error: 0.0733"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 749/1534 [=============>................] - ETA: 1s - loss: 0.0099 - mean_absolute_error: 0.0733"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 769/1534 [==============>...............] - ETA: 1s - loss: 0.0099 - mean_absolute_error: 0.0733"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 789/1534 [==============>...............] - ETA: 1s - loss: 0.0098 - mean_absolute_error: 0.0733"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 810/1534 [==============>...............] - ETA: 1s - loss: 0.0099 - mean_absolute_error: 0.0734"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 831/1534 [===============>..............] - ETA: 1s - loss: 0.0099 - mean_absolute_error: 0.0734"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 852/1534 [===============>..............] - ETA: 1s - loss: 0.0099 - mean_absolute_error: 0.0733"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 872/1534 [================>.............] - ETA: 1s - loss: 0.0099 - mean_absolute_error: 0.0732"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 892/1534 [================>.............] - ETA: 1s - loss: 0.0099 - mean_absolute_error: 0.0732"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 912/1534 [================>.............] - ETA: 1s - loss: 0.0098 - mean_absolute_error: 0.0731"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 932/1534 [=================>............] - ETA: 1s - loss: 0.0098 - mean_absolute_error: 0.0731"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 952/1534 [=================>............] - ETA: 1s - loss: 0.0098 - mean_absolute_error: 0.0731"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 972/1534 [==================>...........] - ETA: 1s - loss: 0.0098 - mean_absolute_error: 0.0730"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 992/1534 [==================>...........] - ETA: 1s - loss: 0.0098 - mean_absolute_error: 0.0730"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1012/1534 [==================>...........] - ETA: 1s - loss: 0.0098 - mean_absolute_error: 0.0729"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1031/1534 [===================>..........] - ETA: 1s - loss: 0.0098 - mean_absolute_error: 0.0729"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1051/1534 [===================>..........] - ETA: 1s - loss: 0.0098 - mean_absolute_error: 0.0729"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1072/1534 [===================>..........] - ETA: 1s - loss: 0.0098 - mean_absolute_error: 0.0728"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1093/1534 [====================>.........] - ETA: 1s - loss: 0.0098 - mean_absolute_error: 0.0728"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1114/1534 [====================>.........] - ETA: 1s - loss: 0.0098 - mean_absolute_error: 0.0728"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1135/1534 [=====================>........] - ETA: 0s - loss: 0.0098 - mean_absolute_error: 0.0728"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1156/1534 [=====================>........] - ETA: 0s - loss: 0.0098 - mean_absolute_error: 0.0727"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1177/1534 [======================>.......] - ETA: 0s - loss: 0.0097 - mean_absolute_error: 0.0726"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1198/1534 [======================>.......] - ETA: 0s - loss: 0.0097 - mean_absolute_error: 0.0726"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1219/1534 [======================>.......] - ETA: 0s - loss: 0.0097 - mean_absolute_error: 0.0726"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1240/1534 [=======================>......] - ETA: 0s - loss: 0.0097 - mean_absolute_error: 0.0726"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1261/1534 [=======================>......] - ETA: 0s - loss: 0.0097 - mean_absolute_error: 0.0726"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1282/1534 [========================>.....] - ETA: 0s - loss: 0.0097 - mean_absolute_error: 0.0726"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1303/1534 [========================>.....] - ETA: 0s - loss: 0.0097 - mean_absolute_error: 0.0726"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1324/1534 [========================>.....] - ETA: 0s - loss: 0.0097 - mean_absolute_error: 0.0725"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1345/1534 [=========================>....] - ETA: 0s - loss: 0.0097 - mean_absolute_error: 0.0724"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1365/1534 [=========================>....] - ETA: 0s - loss: 0.0096 - mean_absolute_error: 0.0724"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1385/1534 [==========================>...] - ETA: 0s - loss: 0.0096 - mean_absolute_error: 0.0724"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1406/1534 [==========================>...] - ETA: 0s - loss: 0.0096 - mean_absolute_error: 0.0723"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1426/1534 [==========================>...] - ETA: 0s - loss: 0.0096 - mean_absolute_error: 0.0723"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1447/1534 [===========================>..] - ETA: 0s - loss: 0.0096 - mean_absolute_error: 0.0723"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1468/1534 [===========================>..] - ETA: 0s - loss: 0.0097 - mean_absolute_error: 0.0723"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1488/1534 [============================>.] - ETA: 0s - loss: 0.0096 - mean_absolute_error: 0.0723"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1509/1534 [============================>.] - ETA: 0s - loss: 0.0096 - mean_absolute_error: 0.0723"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1530/1534 [============================>.] - ETA: 0s - loss: 0.0096 - mean_absolute_error: 0.0722"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1534/1534 [==============================] - 5s 3ms/step - loss: 0.0096 - mean_absolute_error: 0.0722 - val_loss: 0.0091 - val_mean_absolute_error: 0.0704\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 4/20\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "   1/1534 [..............................] - ETA: 41s - loss: 0.0129 - mean_absolute_error: 0.0779"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  20/1534 [..............................] - ETA: 4s - loss: 0.0087 - mean_absolute_error: 0.0704 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  40/1534 [..............................] - ETA: 3s - loss: 0.0092 - mean_absolute_error: 0.0712"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  60/1534 [>.............................] - ETA: 3s - loss: 0.0100 - mean_absolute_error: 0.0725"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  80/1534 [>.............................] - ETA: 3s - loss: 0.0098 - mean_absolute_error: 0.0725"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 101/1534 [>.............................] - ETA: 3s - loss: 0.0094 - mean_absolute_error: 0.0714"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 122/1534 [=>............................] - ETA: 3s - loss: 0.0096 - mean_absolute_error: 0.0720"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 143/1534 [=>............................] - ETA: 3s - loss: 0.0096 - mean_absolute_error: 0.0720"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 163/1534 [==>...........................] - ETA: 3s - loss: 0.0096 - mean_absolute_error: 0.0718"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 183/1534 [==>...........................] - ETA: 3s - loss: 0.0094 - mean_absolute_error: 0.0715"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 204/1534 [==>...........................] - ETA: 3s - loss: 0.0095 - mean_absolute_error: 0.0716"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 225/1534 [===>..........................] - ETA: 3s - loss: 0.0095 - mean_absolute_error: 0.0714"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 245/1534 [===>..........................] - ETA: 3s - loss: 0.0094 - mean_absolute_error: 0.0712"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 266/1534 [====>.........................] - ETA: 3s - loss: 0.0094 - mean_absolute_error: 0.0712"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 287/1534 [====>.........................] - ETA: 3s - loss: 0.0094 - mean_absolute_error: 0.0710"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 307/1534 [=====>........................] - ETA: 3s - loss: 0.0093 - mean_absolute_error: 0.0708"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 327/1534 [=====>........................] - ETA: 3s - loss: 0.0093 - mean_absolute_error: 0.0707"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 348/1534 [=====>........................] - ETA: 2s - loss: 0.0094 - mean_absolute_error: 0.0710"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 369/1534 [======>.......................] - ETA: 2s - loss: 0.0093 - mean_absolute_error: 0.0709"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 390/1534 [======>.......................] - ETA: 2s - loss: 0.0092 - mean_absolute_error: 0.0706"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 411/1534 [=======>......................] - ETA: 2s - loss: 0.0092 - mean_absolute_error: 0.0704"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 431/1534 [=======>......................] - ETA: 2s - loss: 0.0092 - mean_absolute_error: 0.0703"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 451/1534 [=======>......................] - ETA: 2s - loss: 0.0092 - mean_absolute_error: 0.0705"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 471/1534 [========>.....................] - ETA: 2s - loss: 0.0093 - mean_absolute_error: 0.0706"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 492/1534 [========>.....................] - ETA: 2s - loss: 0.0093 - mean_absolute_error: 0.0706"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 513/1534 [=========>....................] - ETA: 2s - loss: 0.0094 - mean_absolute_error: 0.0709"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 534/1534 [=========>....................] - ETA: 2s - loss: 0.0094 - mean_absolute_error: 0.0707"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 555/1534 [=========>....................] - ETA: 2s - loss: 0.0093 - mean_absolute_error: 0.0707"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 576/1534 [==========>...................] - ETA: 2s - loss: 0.0093 - mean_absolute_error: 0.0708"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 597/1534 [==========>...................] - ETA: 2s - loss: 0.0093 - mean_absolute_error: 0.0709"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 617/1534 [===========>..................] - ETA: 2s - loss: 0.0094 - mean_absolute_error: 0.0710"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 638/1534 [===========>..................] - ETA: 2s - loss: 0.0094 - mean_absolute_error: 0.0709"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 659/1534 [===========>..................] - ETA: 2s - loss: 0.0094 - mean_absolute_error: 0.0710"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 679/1534 [============>.................] - ETA: 2s - loss: 0.0094 - mean_absolute_error: 0.0710"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 700/1534 [============>.................] - ETA: 2s - loss: 0.0094 - mean_absolute_error: 0.0710"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 721/1534 [=============>................] - ETA: 2s - loss: 0.0094 - mean_absolute_error: 0.0709"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 742/1534 [=============>................] - ETA: 1s - loss: 0.0094 - mean_absolute_error: 0.0709"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 763/1534 [=============>................] - ETA: 1s - loss: 0.0094 - mean_absolute_error: 0.0709"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 784/1534 [==============>...............] - ETA: 1s - loss: 0.0093 - mean_absolute_error: 0.0709"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 805/1534 [==============>...............] - ETA: 1s - loss: 0.0094 - mean_absolute_error: 0.0710"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 825/1534 [===============>..............] - ETA: 1s - loss: 0.0094 - mean_absolute_error: 0.0710"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 845/1534 [===============>..............] - ETA: 1s - loss: 0.0094 - mean_absolute_error: 0.0710"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 865/1534 [===============>..............] - ETA: 1s - loss: 0.0094 - mean_absolute_error: 0.0710"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 886/1534 [================>.............] - ETA: 1s - loss: 0.0094 - mean_absolute_error: 0.0709"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 907/1534 [================>.............] - ETA: 1s - loss: 0.0094 - mean_absolute_error: 0.0709"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 928/1534 [=================>............] - ETA: 1s - loss: 0.0094 - mean_absolute_error: 0.0708"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 948/1534 [=================>............] - ETA: 1s - loss: 0.0093 - mean_absolute_error: 0.0708"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 968/1534 [=================>............] - ETA: 1s - loss: 0.0094 - mean_absolute_error: 0.0708"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 988/1534 [==================>...........] - ETA: 1s - loss: 0.0094 - mean_absolute_error: 0.0708"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1008/1534 [==================>...........] - ETA: 1s - loss: 0.0093 - mean_absolute_error: 0.0707"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1028/1534 [===================>..........] - ETA: 1s - loss: 0.0093 - mean_absolute_error: 0.0707"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1048/1534 [===================>..........] - ETA: 1s - loss: 0.0093 - mean_absolute_error: 0.0707"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1068/1534 [===================>..........] - ETA: 1s - loss: 0.0093 - mean_absolute_error: 0.0707"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1089/1534 [====================>.........] - ETA: 1s - loss: 0.0093 - mean_absolute_error: 0.0706"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1109/1534 [====================>.........] - ETA: 1s - loss: 0.0093 - mean_absolute_error: 0.0707"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1130/1534 [=====================>........] - ETA: 1s - loss: 0.0093 - mean_absolute_error: 0.0707"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1151/1534 [=====================>........] - ETA: 0s - loss: 0.0093 - mean_absolute_error: 0.0707"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1171/1534 [=====================>........] - ETA: 0s - loss: 0.0093 - mean_absolute_error: 0.0706"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1191/1534 [======================>.......] - ETA: 0s - loss: 0.0093 - mean_absolute_error: 0.0706"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1210/1534 [======================>.......] - ETA: 0s - loss: 0.0093 - mean_absolute_error: 0.0705"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1231/1534 [=======================>......] - ETA: 0s - loss: 0.0093 - mean_absolute_error: 0.0705"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1251/1534 [=======================>......] - ETA: 0s - loss: 0.0093 - mean_absolute_error: 0.0706"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1271/1534 [=======================>......] - ETA: 0s - loss: 0.0093 - mean_absolute_error: 0.0706"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1291/1534 [========================>.....] - ETA: 0s - loss: 0.0093 - mean_absolute_error: 0.0706"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1311/1534 [========================>.....] - ETA: 0s - loss: 0.0093 - mean_absolute_error: 0.0705"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1331/1534 [=========================>....] - ETA: 0s - loss: 0.0093 - mean_absolute_error: 0.0705"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1351/1534 [=========================>....] - ETA: 0s - loss: 0.0092 - mean_absolute_error: 0.0704"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1372/1534 [=========================>....] - ETA: 0s - loss: 0.0092 - mean_absolute_error: 0.0704"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1392/1534 [==========================>...] - ETA: 0s - loss: 0.0092 - mean_absolute_error: 0.0704"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1412/1534 [==========================>...] - ETA: 0s - loss: 0.0092 - mean_absolute_error: 0.0704"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1433/1534 [===========================>..] - ETA: 0s - loss: 0.0092 - mean_absolute_error: 0.0704"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1454/1534 [===========================>..] - ETA: 0s - loss: 0.0092 - mean_absolute_error: 0.0704"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1475/1534 [===========================>..] - ETA: 0s - loss: 0.0093 - mean_absolute_error: 0.0704"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1495/1534 [============================>.] - ETA: 0s - loss: 0.0092 - mean_absolute_error: 0.0704"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1516/1534 [============================>.] - ETA: 0s - loss: 0.0092 - mean_absolute_error: 0.0703"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1534/1534 [==============================] - 5s 3ms/step - loss: 0.0092 - mean_absolute_error: 0.0703 - val_loss: 0.0088 - val_mean_absolute_error: 0.0693\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 5/20\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "   1/1534 [..............................] - ETA: 41s - loss: 0.0173 - mean_absolute_error: 0.0875"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  20/1534 [..............................] - ETA: 4s - loss: 0.0090 - mean_absolute_error: 0.0711 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  40/1534 [..............................] - ETA: 3s - loss: 0.0088 - mean_absolute_error: 0.0706"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  61/1534 [>.............................] - ETA: 3s - loss: 0.0098 - mean_absolute_error: 0.0721"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  81/1534 [>.............................] - ETA: 3s - loss: 0.0096 - mean_absolute_error: 0.0715"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 102/1534 [>.............................] - ETA: 3s - loss: 0.0092 - mean_absolute_error: 0.0706"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 123/1534 [=>............................] - ETA: 3s - loss: 0.0092 - mean_absolute_error: 0.0703"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 144/1534 [=>............................] - ETA: 3s - loss: 0.0092 - mean_absolute_error: 0.0705"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 165/1534 [==>...........................] - ETA: 3s - loss: 0.0093 - mean_absolute_error: 0.0708"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 186/1534 [==>...........................] - ETA: 3s - loss: 0.0093 - mean_absolute_error: 0.0706"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 207/1534 [===>..........................] - ETA: 3s - loss: 0.0092 - mean_absolute_error: 0.0704"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 228/1534 [===>..........................] - ETA: 3s - loss: 0.0092 - mean_absolute_error: 0.0703"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 248/1534 [===>..........................] - ETA: 3s - loss: 0.0092 - mean_absolute_error: 0.0701"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 268/1534 [====>.........................] - ETA: 3s - loss: 0.0092 - mean_absolute_error: 0.0701"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 289/1534 [====>.........................] - ETA: 3s - loss: 0.0091 - mean_absolute_error: 0.0701"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 309/1534 [=====>........................] - ETA: 3s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 330/1534 [=====>........................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 350/1534 [=====>........................] - ETA: 2s - loss: 0.0092 - mean_absolute_error: 0.0702"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 371/1534 [======>.......................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0701"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 392/1534 [======>.......................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 413/1534 [=======>......................] - ETA: 2s - loss: 0.0090 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 434/1534 [=======>......................] - ETA: 2s - loss: 0.0090 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 454/1534 [=======>......................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 474/1534 [========>.....................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 495/1534 [========>.....................] - ETA: 2s - loss: 0.0092 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 516/1534 [=========>....................] - ETA: 2s - loss: 0.0092 - mean_absolute_error: 0.0701"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 537/1534 [=========>....................] - ETA: 2s - loss: 0.0092 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 557/1534 [=========>....................] - ETA: 2s - loss: 0.0092 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 577/1534 [==========>...................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0701"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 597/1534 [==========>...................] - ETA: 2s - loss: 0.0092 - mean_absolute_error: 0.0702"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 617/1534 [===========>..................] - ETA: 2s - loss: 0.0092 - mean_absolute_error: 0.0704"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 638/1534 [===========>..................] - ETA: 2s - loss: 0.0092 - mean_absolute_error: 0.0703"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 659/1534 [===========>..................] - ETA: 2s - loss: 0.0092 - mean_absolute_error: 0.0703"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 679/1534 [============>.................] - ETA: 2s - loss: 0.0092 - mean_absolute_error: 0.0703"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 699/1534 [============>.................] - ETA: 2s - loss: 0.0092 - mean_absolute_error: 0.0703"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 720/1534 [=============>................] - ETA: 2s - loss: 0.0092 - mean_absolute_error: 0.0703"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 741/1534 [=============>................] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0702"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 762/1534 [=============>................] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0703"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 783/1534 [==============>...............] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0703"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 803/1534 [==============>...............] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0703"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 823/1534 [===============>..............] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0704"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 843/1534 [===============>..............] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0703"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 864/1534 [===============>..............] - ETA: 1s - loss: 0.0093 - mean_absolute_error: 0.0703"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 884/1534 [================>.............] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0702"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 904/1534 [================>.............] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0703"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 924/1534 [=================>............] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0702"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 945/1534 [=================>............] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0702"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 965/1534 [=================>............] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0702"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 985/1534 [==================>...........] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0701"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1006/1534 [==================>...........] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0701"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1027/1534 [===================>..........] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0701"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1047/1534 [===================>..........] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1068/1534 [===================>..........] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0701"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1089/1534 [====================>.........] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0701"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1109/1534 [====================>.........] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1129/1534 [=====================>........] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0701"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1149/1534 [=====================>........] - ETA: 0s - loss: 0.0092 - mean_absolute_error: 0.0701"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1169/1534 [=====================>........] - ETA: 0s - loss: 0.0092 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1188/1534 [======================>.......] - ETA: 0s - loss: 0.0092 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1208/1534 [======================>.......] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1228/1534 [=======================>......] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1248/1534 [=======================>......] - ETA: 0s - loss: 0.0092 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1267/1534 [=======================>......] - ETA: 0s - loss: 0.0092 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1286/1534 [========================>.....] - ETA: 0s - loss: 0.0092 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1306/1534 [========================>.....] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1327/1534 [========================>.....] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1348/1534 [=========================>....] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1369/1534 [=========================>....] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1389/1534 [==========================>...] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1409/1534 [==========================>...] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1429/1534 [==========================>...] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1449/1534 [===========================>..] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1468/1534 [===========================>..] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1487/1534 [============================>.] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1507/1534 [============================>.] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1526/1534 [============================>.] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1534/1534 [==============================] - 5s 3ms/step - loss: 0.0091 - mean_absolute_error: 0.0698 - val_loss: 0.0087 - val_mean_absolute_error: 0.0688\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 6/20\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "   1/1534 [..............................] - ETA: 42s - loss: 0.0074 - mean_absolute_error: 0.0709"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  20/1534 [..............................] - ETA: 4s - loss: 0.0089 - mean_absolute_error: 0.0700 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  40/1534 [..............................] - ETA: 3s - loss: 0.0092 - mean_absolute_error: 0.0711"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  60/1534 [>.............................] - ETA: 3s - loss: 0.0097 - mean_absolute_error: 0.0714"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  81/1534 [>.............................] - ETA: 3s - loss: 0.0096 - mean_absolute_error: 0.0713"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 101/1534 [>.............................] - ETA: 3s - loss: 0.0093 - mean_absolute_error: 0.0706"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 122/1534 [=>............................] - ETA: 3s - loss: 0.0092 - mean_absolute_error: 0.0703"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 143/1534 [=>............................] - ETA: 3s - loss: 0.0092 - mean_absolute_error: 0.0703"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 163/1534 [==>...........................] - ETA: 3s - loss: 0.0091 - mean_absolute_error: 0.0702"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 184/1534 [==>...........................] - ETA: 3s - loss: 0.0091 - mean_absolute_error: 0.0701"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 204/1534 [==>...........................] - ETA: 3s - loss: 0.0091 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 225/1534 [===>..........................] - ETA: 3s - loss: 0.0092 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 246/1534 [===>..........................] - ETA: 3s - loss: 0.0092 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 267/1534 [====>.........................] - ETA: 3s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 287/1534 [====>.........................] - ETA: 3s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 307/1534 [=====>........................] - ETA: 3s - loss: 0.0091 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 327/1534 [=====>........................] - ETA: 3s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 348/1534 [=====>........................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 368/1534 [======>.......................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 389/1534 [======>.......................] - ETA: 2s - loss: 0.0090 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 410/1534 [=======>......................] - ETA: 2s - loss: 0.0090 - mean_absolute_error: 0.0695"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 430/1534 [=======>......................] - ETA: 2s - loss: 0.0090 - mean_absolute_error: 0.0695"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 450/1534 [=======>......................] - ETA: 2s - loss: 0.0090 - mean_absolute_error: 0.0695"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 470/1534 [========>.....................] - ETA: 2s - loss: 0.0090 - mean_absolute_error: 0.0694"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 491/1534 [========>.....................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 511/1534 [========>.....................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 531/1534 [=========>....................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 552/1534 [=========>....................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 573/1534 [==========>...................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 594/1534 [==========>...................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 615/1534 [===========>..................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 635/1534 [===========>..................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 655/1534 [===========>..................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 675/1534 [============>.................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 696/1534 [============>.................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0701"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 716/1534 [=============>................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 737/1534 [=============>................] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 757/1534 [=============>................] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 778/1534 [==============>...............] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0701"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 799/1534 [==============>...............] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 820/1534 [===============>..............] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0701"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 841/1534 [===============>..............] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0702"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 862/1534 [===============>..............] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0702"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 882/1534 [================>.............] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0701"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 903/1534 [================>.............] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0701"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 924/1534 [=================>............] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 945/1534 [=================>............] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0701"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 965/1534 [=================>............] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 986/1534 [==================>...........] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1007/1534 [==================>...........] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1028/1534 [===================>..........] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1049/1534 [===================>..........] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1071/1534 [===================>..........] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1092/1534 [====================>.........] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1112/1534 [====================>.........] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1133/1534 [=====================>........] - ETA: 0s - loss: 0.0092 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1154/1534 [=====================>........] - ETA: 0s - loss: 0.0092 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1174/1534 [=====================>........] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1195/1534 [======================>.......] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1216/1534 [======================>.......] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1237/1534 [=======================>......] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1258/1534 [=======================>......] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1278/1534 [=======================>......] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1299/1534 [========================>.....] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1320/1534 [========================>.....] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1340/1534 [=========================>....] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1360/1534 [=========================>....] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1380/1534 [=========================>....] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1400/1534 [==========================>...] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1420/1534 [==========================>...] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1440/1534 [===========================>..] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1461/1534 [===========================>..] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1482/1534 [===========================>..] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1503/1534 [============================>.] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1524/1534 [============================>.] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1534/1534 [==============================] - 5s 3ms/step - loss: 0.0091 - mean_absolute_error: 0.0697 - val_loss: 0.0087 - val_mean_absolute_error: 0.0694\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 7/20\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "   1/1534 [..............................] - ETA: 40s - loss: 0.0088 - mean_absolute_error: 0.0751"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  20/1534 [..............................] - ETA: 4s - loss: 0.0095 - mean_absolute_error: 0.0714 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  41/1534 [..............................] - ETA: 3s - loss: 0.0084 - mean_absolute_error: 0.0694"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  62/1534 [>.............................] - ETA: 3s - loss: 0.0094 - mean_absolute_error: 0.0703"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  84/1534 [>.............................] - ETA: 3s - loss: 0.0094 - mean_absolute_error: 0.0707"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 105/1534 [=>............................] - ETA: 3s - loss: 0.0090 - mean_absolute_error: 0.0695"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 127/1534 [=>............................] - ETA: 3s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 150/1534 [=>............................] - ETA: 3s - loss: 0.0092 - mean_absolute_error: 0.0702"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 171/1534 [==>...........................] - ETA: 3s - loss: 0.0091 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 192/1534 [==>...........................] - ETA: 3s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 213/1534 [===>..........................] - ETA: 3s - loss: 0.0090 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 234/1534 [===>..........................] - ETA: 3s - loss: 0.0092 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 255/1534 [===>..........................] - ETA: 3s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 276/1534 [====>.........................] - ETA: 3s - loss: 0.0090 - mean_absolute_error: 0.0694"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 297/1534 [====>.........................] - ETA: 2s - loss: 0.0090 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 318/1534 [=====>........................] - ETA: 2s - loss: 0.0090 - mean_absolute_error: 0.0695"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 339/1534 [=====>........................] - ETA: 2s - loss: 0.0090 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 360/1534 [======>.......................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 381/1534 [======>.......................] - ETA: 2s - loss: 0.0090 - mean_absolute_error: 0.0695"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 402/1534 [======>.......................] - ETA: 2s - loss: 0.0090 - mean_absolute_error: 0.0694"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 423/1534 [=======>......................] - ETA: 2s - loss: 0.0089 - mean_absolute_error: 0.0692"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 444/1534 [=======>......................] - ETA: 2s - loss: 0.0090 - mean_absolute_error: 0.0692"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 466/1534 [========>.....................] - ETA: 2s - loss: 0.0089 - mean_absolute_error: 0.0693"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 487/1534 [========>.....................] - ETA: 2s - loss: 0.0090 - mean_absolute_error: 0.0693"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 508/1534 [========>.....................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 529/1534 [=========>....................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 550/1534 [=========>....................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0695"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 570/1534 [==========>...................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 590/1534 [==========>...................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 610/1534 [==========>...................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 630/1534 [===========>..................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 650/1534 [===========>..................] - ETA: 2s - loss: 0.0092 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 670/1534 [============>.................] - ETA: 2s - loss: 0.0092 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 690/1534 [============>.................] - ETA: 2s - loss: 0.0092 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 710/1534 [============>.................] - ETA: 2s - loss: 0.0092 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 730/1534 [=============>................] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 751/1534 [=============>................] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 772/1534 [==============>...............] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 793/1534 [==============>...............] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 814/1534 [==============>...............] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 835/1534 [===============>..............] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0701"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 856/1534 [===============>..............] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0701"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 877/1534 [================>.............] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 897/1534 [================>.............] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 917/1534 [================>.............] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 937/1534 [=================>............] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 957/1534 [=================>............] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 977/1534 [==================>...........] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 998/1534 [==================>...........] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1018/1534 [==================>...........] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1038/1534 [===================>..........] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1058/1534 [===================>..........] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1078/1534 [====================>.........] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1099/1534 [====================>.........] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1120/1534 [====================>.........] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1140/1534 [=====================>........] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1160/1534 [=====================>........] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1180/1534 [======================>.......] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1201/1534 [======================>.......] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1221/1534 [======================>.......] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1241/1534 [=======================>......] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1261/1534 [=======================>......] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1281/1534 [========================>.....] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1301/1534 [========================>.....] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1321/1534 [========================>.....] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1341/1534 [=========================>....] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1361/1534 [=========================>....] - ETA: 0s - loss: 0.0090 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1381/1534 [==========================>...] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1402/1534 [==========================>...] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1423/1534 [==========================>...] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1444/1534 [===========================>..] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1465/1534 [===========================>..] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1486/1534 [============================>.] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1507/1534 [============================>.] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1528/1534 [============================>.] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1534/1534 [==============================] - 5s 3ms/step - loss: 0.0091 - mean_absolute_error: 0.0696 - val_loss: 0.0087 - val_mean_absolute_error: 0.0688\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 8/20\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "   1/1534 [..............................] - ETA: 41s - loss: 0.0115 - mean_absolute_error: 0.0759"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  19/1534 [..............................] - ETA: 4s - loss: 0.0084 - mean_absolute_error: 0.0678 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  39/1534 [..............................] - ETA: 4s - loss: 0.0090 - mean_absolute_error: 0.0703"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  60/1534 [>.............................] - ETA: 3s - loss: 0.0094 - mean_absolute_error: 0.0703"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  80/1534 [>.............................] - ETA: 3s - loss: 0.0094 - mean_absolute_error: 0.0704"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 100/1534 [>.............................] - ETA: 3s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 121/1534 [=>............................] - ETA: 3s - loss: 0.0089 - mean_absolute_error: 0.0691"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 144/1534 [=>............................] - ETA: 3s - loss: 0.0092 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 164/1534 [==>...........................] - ETA: 3s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 184/1534 [==>...........................] - ETA: 3s - loss: 0.0090 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 205/1534 [===>..........................] - ETA: 3s - loss: 0.0090 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 225/1534 [===>..........................] - ETA: 3s - loss: 0.0091 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 245/1534 [===>..........................] - ETA: 3s - loss: 0.0091 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 265/1534 [====>.........................] - ETA: 3s - loss: 0.0091 - mean_absolute_error: 0.0694"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 285/1534 [====>.........................] - ETA: 3s - loss: 0.0091 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 305/1534 [====>.........................] - ETA: 3s - loss: 0.0091 - mean_absolute_error: 0.0695"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 325/1534 [=====>........................] - ETA: 3s - loss: 0.0090 - mean_absolute_error: 0.0693"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 346/1534 [=====>........................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 366/1534 [======>.......................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 387/1534 [======>.......................] - ETA: 2s - loss: 0.0090 - mean_absolute_error: 0.0695"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 408/1534 [======>.......................] - ETA: 2s - loss: 0.0090 - mean_absolute_error: 0.0694"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 428/1534 [=======>......................] - ETA: 2s - loss: 0.0089 - mean_absolute_error: 0.0690"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 449/1534 [=======>......................] - ETA: 2s - loss: 0.0090 - mean_absolute_error: 0.0693"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 469/1534 [========>.....................] - ETA: 2s - loss: 0.0090 - mean_absolute_error: 0.0694"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 490/1534 [========>.....................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 511/1534 [========>.....................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 532/1534 [=========>....................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 553/1534 [=========>....................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 573/1534 [==========>...................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 593/1534 [==========>...................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 614/1534 [===========>..................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 635/1534 [===========>..................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 656/1534 [===========>..................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 677/1534 [============>.................] - ETA: 2s - loss: 0.0092 - mean_absolute_error: 0.0701"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 698/1534 [============>.................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 719/1534 [=============>................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 740/1534 [=============>................] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 761/1534 [=============>................] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 782/1534 [==============>...............] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 802/1534 [==============>...............] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 823/1534 [===============>..............] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 843/1534 [===============>..............] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 864/1534 [===============>..............] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 885/1534 [================>.............] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 905/1534 [================>.............] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 926/1534 [=================>............] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 946/1534 [=================>............] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 967/1534 [=================>............] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 987/1534 [==================>...........] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1008/1534 [==================>...........] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1028/1534 [===================>..........] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1048/1534 [===================>..........] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1069/1534 [===================>..........] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1090/1534 [====================>.........] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1111/1534 [====================>.........] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1132/1534 [=====================>........] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1153/1534 [=====================>........] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1173/1534 [=====================>........] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1194/1534 [======================>.......] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1215/1534 [======================>.......] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1236/1534 [=======================>......] - ETA: 0s - loss: 0.0090 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1257/1534 [=======================>......] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1278/1534 [=======================>......] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1299/1534 [========================>.....] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1320/1534 [========================>.....] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1341/1534 [=========================>....] - ETA: 0s - loss: 0.0090 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1362/1534 [=========================>....] - ETA: 0s - loss: 0.0090 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1383/1534 [==========================>...] - ETA: 0s - loss: 0.0090 - mean_absolute_error: 0.0695"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1404/1534 [==========================>...] - ETA: 0s - loss: 0.0090 - mean_absolute_error: 0.0695"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1425/1534 [==========================>...] - ETA: 0s - loss: 0.0090 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1446/1534 [===========================>..] - ETA: 0s - loss: 0.0090 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1467/1534 [===========================>..] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1488/1534 [============================>.] - ETA: 0s - loss: 0.0090 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1510/1534 [============================>.] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1531/1534 [============================>.] - ETA: 0s - loss: 0.0090 - mean_absolute_error: 0.0695"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1534/1534 [==============================] - 5s 3ms/step - loss: 0.0090 - mean_absolute_error: 0.0695 - val_loss: 0.0086 - val_mean_absolute_error: 0.0687\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 9/20\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "   1/1534 [..............................] - ETA: 36s - loss: 0.0174 - mean_absolute_error: 0.1005"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  20/1534 [..............................] - ETA: 3s - loss: 0.0087 - mean_absolute_error: 0.0699 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  41/1534 [..............................] - ETA: 3s - loss: 0.0089 - mean_absolute_error: 0.0706"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  62/1534 [>.............................] - ETA: 3s - loss: 0.0095 - mean_absolute_error: 0.0709"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  83/1534 [>.............................] - ETA: 3s - loss: 0.0094 - mean_absolute_error: 0.0708"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 104/1534 [=>............................] - ETA: 3s - loss: 0.0090 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 125/1534 [=>............................] - ETA: 3s - loss: 0.0091 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 147/1534 [=>............................] - ETA: 3s - loss: 0.0090 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 167/1534 [==>...........................] - ETA: 3s - loss: 0.0090 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 187/1534 [==>...........................] - ETA: 3s - loss: 0.0090 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 208/1534 [===>..........................] - ETA: 3s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 229/1534 [===>..........................] - ETA: 3s - loss: 0.0090 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 250/1534 [===>..........................] - ETA: 3s - loss: 0.0090 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 271/1534 [====>.........................] - ETA: 3s - loss: 0.0090 - mean_absolute_error: 0.0695"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 292/1534 [====>.........................] - ETA: 3s - loss: 0.0090 - mean_absolute_error: 0.0695"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 313/1534 [=====>........................] - ETA: 3s - loss: 0.0090 - mean_absolute_error: 0.0693"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 334/1534 [=====>........................] - ETA: 2s - loss: 0.0090 - mean_absolute_error: 0.0694"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 354/1534 [=====>........................] - ETA: 2s - loss: 0.0090 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 375/1534 [======>.......................] - ETA: 2s - loss: 0.0090 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 397/1534 [======>.......................] - ETA: 2s - loss: 0.0090 - mean_absolute_error: 0.0694"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 418/1534 [=======>......................] - ETA: 2s - loss: 0.0089 - mean_absolute_error: 0.0692"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 439/1534 [=======>......................] - ETA: 2s - loss: 0.0089 - mean_absolute_error: 0.0691"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 459/1534 [=======>......................] - ETA: 2s - loss: 0.0089 - mean_absolute_error: 0.0692"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 480/1534 [========>.....................] - ETA: 2s - loss: 0.0089 - mean_absolute_error: 0.0692"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 500/1534 [========>.....................] - ETA: 2s - loss: 0.0090 - mean_absolute_error: 0.0695"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 521/1534 [=========>....................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 541/1534 [=========>....................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0695"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 561/1534 [=========>....................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 582/1534 [==========>...................] - ETA: 2s - loss: 0.0090 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 603/1534 [==========>...................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 624/1534 [===========>..................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 645/1534 [===========>..................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 666/1534 [============>.................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 687/1534 [============>.................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 708/1534 [============>.................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 729/1534 [=============>................] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 750/1534 [=============>................] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 772/1534 [==============>...............] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 793/1534 [==============>...............] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 814/1534 [==============>...............] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 835/1534 [===============>..............] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 856/1534 [===============>..............] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 876/1534 [================>.............] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 896/1534 [================>.............] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 917/1534 [================>.............] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 938/1534 [=================>............] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 958/1534 [=================>............] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 978/1534 [==================>...........] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 998/1534 [==================>...........] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1019/1534 [==================>...........] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1039/1534 [===================>..........] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1059/1534 [===================>..........] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1080/1534 [====================>.........] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1100/1534 [====================>.........] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1121/1534 [====================>.........] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1142/1534 [=====================>........] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1162/1534 [=====================>........] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1183/1534 [======================>.......] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1204/1534 [======================>.......] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1225/1534 [======================>.......] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1246/1534 [=======================>......] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1267/1534 [=======================>......] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1287/1534 [========================>.....] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1308/1534 [========================>.....] - ETA: 0s - loss: 0.0090 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1329/1534 [========================>.....] - ETA: 0s - loss: 0.0090 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1349/1534 [=========================>....] - ETA: 0s - loss: 0.0090 - mean_absolute_error: 0.0695"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1370/1534 [=========================>....] - ETA: 0s - loss: 0.0090 - mean_absolute_error: 0.0695"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1391/1534 [==========================>...] - ETA: 0s - loss: 0.0090 - mean_absolute_error: 0.0695"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1412/1534 [==========================>...] - ETA: 0s - loss: 0.0090 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1433/1534 [===========================>..] - ETA: 0s - loss: 0.0090 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1454/1534 [===========================>..] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1475/1534 [===========================>..] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1496/1534 [============================>.] - ETA: 0s - loss: 0.0090 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1517/1534 [============================>.] - ETA: 0s - loss: 0.0090 - mean_absolute_error: 0.0695"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1534/1534 [==============================] - 5s 3ms/step - loss: 0.0090 - mean_absolute_error: 0.0695 - val_loss: 0.0086 - val_mean_absolute_error: 0.0687\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 10/20\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "   1/1534 [..............................] - ETA: 43s - loss: 0.0112 - mean_absolute_error: 0.0691"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  20/1534 [..............................] - ETA: 4s - loss: 0.0091 - mean_absolute_error: 0.0706 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  40/1534 [..............................] - ETA: 3s - loss: 0.0087 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  61/1534 [>.............................] - ETA: 3s - loss: 0.0095 - mean_absolute_error: 0.0709"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  81/1534 [>.............................] - ETA: 3s - loss: 0.0094 - mean_absolute_error: 0.0706"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 101/1534 [>.............................] - ETA: 3s - loss: 0.0090 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 122/1534 [=>............................] - ETA: 3s - loss: 0.0090 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 143/1534 [=>............................] - ETA: 3s - loss: 0.0090 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 163/1534 [==>...........................] - ETA: 3s - loss: 0.0091 - mean_absolute_error: 0.0702"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 183/1534 [==>...........................] - ETA: 3s - loss: 0.0090 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 203/1534 [==>...........................] - ETA: 3s - loss: 0.0090 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 223/1534 [===>..........................] - ETA: 3s - loss: 0.0090 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 243/1534 [===>..........................] - ETA: 3s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 263/1534 [====>.........................] - ETA: 3s - loss: 0.0090 - mean_absolute_error: 0.0695"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 283/1534 [====>.........................] - ETA: 3s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 304/1534 [====>.........................] - ETA: 3s - loss: 0.0090 - mean_absolute_error: 0.0695"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 324/1534 [=====>........................] - ETA: 3s - loss: 0.0090 - mean_absolute_error: 0.0694"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 344/1534 [=====>........................] - ETA: 2s - loss: 0.0090 - mean_absolute_error: 0.0695"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 364/1534 [======>.......................] - ETA: 2s - loss: 0.0090 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 385/1534 [======>.......................] - ETA: 2s - loss: 0.0090 - mean_absolute_error: 0.0694"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 405/1534 [======>.......................] - ETA: 2s - loss: 0.0089 - mean_absolute_error: 0.0693"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 426/1534 [=======>......................] - ETA: 2s - loss: 0.0089 - mean_absolute_error: 0.0691"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 447/1534 [=======>......................] - ETA: 2s - loss: 0.0089 - mean_absolute_error: 0.0691"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 468/1534 [========>.....................] - ETA: 2s - loss: 0.0089 - mean_absolute_error: 0.0692"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 489/1534 [========>.....................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0695"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 509/1534 [========>.....................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 529/1534 [=========>....................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0695"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 549/1534 [=========>....................] - ETA: 2s - loss: 0.0090 - mean_absolute_error: 0.0695"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 569/1534 [==========>...................] - ETA: 2s - loss: 0.0090 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 589/1534 [==========>...................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 609/1534 [==========>...................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 629/1534 [===========>..................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 648/1534 [===========>..................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 668/1534 [============>.................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 687/1534 [============>.................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 707/1534 [============>.................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 727/1534 [=============>................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 747/1534 [=============>................] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 767/1534 [==============>...............] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 787/1534 [==============>...............] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 806/1534 [==============>...............] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 826/1534 [===============>..............] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 845/1534 [===============>..............] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 864/1534 [===============>..............] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 883/1534 [================>.............] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 902/1534 [================>.............] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 922/1534 [=================>............] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 942/1534 [=================>............] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 962/1534 [=================>............] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 982/1534 [==================>...........] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1002/1534 [==================>...........] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1022/1534 [==================>...........] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1042/1534 [===================>..........] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1062/1534 [===================>..........] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1081/1534 [====================>.........] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1100/1534 [====================>.........] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1120/1534 [====================>.........] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1140/1534 [=====================>........] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1160/1534 [=====================>........] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1180/1534 [======================>.......] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1200/1534 [======================>.......] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1221/1534 [======================>.......] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1242/1534 [=======================>......] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1262/1534 [=======================>......] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1282/1534 [========================>.....] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1303/1534 [========================>.....] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1324/1534 [========================>.....] - ETA: 0s - loss: 0.0090 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1345/1534 [=========================>....] - ETA: 0s - loss: 0.0090 - mean_absolute_error: 0.0695"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1366/1534 [=========================>....] - ETA: 0s - loss: 0.0090 - mean_absolute_error: 0.0695"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1386/1534 [==========================>...] - ETA: 0s - loss: 0.0090 - mean_absolute_error: 0.0695"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1405/1534 [==========================>...] - ETA: 0s - loss: 0.0090 - mean_absolute_error: 0.0695"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1425/1534 [==========================>...] - ETA: 0s - loss: 0.0090 - mean_absolute_error: 0.0695"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1446/1534 [===========================>..] - ETA: 0s - loss: 0.0090 - mean_absolute_error: 0.0695"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1467/1534 [===========================>..] - ETA: 0s - loss: 0.0090 - mean_absolute_error: 0.0695"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1488/1534 [============================>.] - ETA: 0s - loss: 0.0090 - mean_absolute_error: 0.0695"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1510/1534 [============================>.] - ETA: 0s - loss: 0.0090 - mean_absolute_error: 0.0695"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1531/1534 [============================>.] - ETA: 0s - loss: 0.0090 - mean_absolute_error: 0.0695"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1534/1534 [==============================] - 5s 3ms/step - loss: 0.0090 - mean_absolute_error: 0.0695 - val_loss: 0.0086 - val_mean_absolute_error: 0.0686\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 11/20\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "   1/1534 [..............................] - ETA: 40s - loss: 0.0154 - mean_absolute_error: 0.0941"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  19/1534 [..............................] - ETA: 4s - loss: 0.0087 - mean_absolute_error: 0.0680 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  39/1534 [..............................] - ETA: 3s - loss: 0.0085 - mean_absolute_error: 0.0690"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  60/1534 [>.............................] - ETA: 3s - loss: 0.0096 - mean_absolute_error: 0.0715"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  80/1534 [>.............................] - ETA: 3s - loss: 0.0094 - mean_absolute_error: 0.0709"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 101/1534 [>.............................] - ETA: 3s - loss: 0.0090 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 123/1534 [=>............................] - ETA: 3s - loss: 0.0090 - mean_absolute_error: 0.0695"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 145/1534 [=>............................] - ETA: 3s - loss: 0.0090 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 166/1534 [==>...........................] - ETA: 3s - loss: 0.0090 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 186/1534 [==>...........................] - ETA: 3s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 207/1534 [===>..........................] - ETA: 3s - loss: 0.0090 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 228/1534 [===>..........................] - ETA: 3s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 249/1534 [===>..........................] - ETA: 3s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 270/1534 [====>.........................] - ETA: 3s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 291/1534 [====>.........................] - ETA: 3s - loss: 0.0090 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 311/1534 [=====>........................] - ETA: 3s - loss: 0.0090 - mean_absolute_error: 0.0695"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 332/1534 [=====>........................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 352/1534 [=====>........................] - ETA: 2s - loss: 0.0090 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 372/1534 [======>.......................] - ETA: 2s - loss: 0.0090 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 393/1534 [======>.......................] - ETA: 2s - loss: 0.0090 - mean_absolute_error: 0.0695"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 414/1534 [=======>......................] - ETA: 2s - loss: 0.0089 - mean_absolute_error: 0.0694"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 435/1534 [=======>......................] - ETA: 2s - loss: 0.0089 - mean_absolute_error: 0.0693"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 456/1534 [=======>......................] - ETA: 2s - loss: 0.0089 - mean_absolute_error: 0.0693"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 477/1534 [========>.....................] - ETA: 2s - loss: 0.0090 - mean_absolute_error: 0.0695"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 497/1534 [========>.....................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 517/1534 [=========>....................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 538/1534 [=========>....................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 559/1534 [=========>....................] - ETA: 2s - loss: 0.0090 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 580/1534 [==========>...................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 600/1534 [==========>...................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 621/1534 [===========>..................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 641/1534 [===========>..................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 661/1534 [===========>..................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 682/1534 [============>.................] - ETA: 2s - loss: 0.0092 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 703/1534 [============>.................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 724/1534 [=============>................] - ETA: 2s - loss: 0.0091 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 744/1534 [=============>................] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 764/1534 [=============>................] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 784/1534 [==============>...............] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 804/1534 [==============>...............] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 824/1534 [===============>..............] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 845/1534 [===============>..............] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 865/1534 [===============>..............] - ETA: 1s - loss: 0.0092 - mean_absolute_error: 0.0700"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 885/1534 [================>.............] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 906/1534 [================>.............] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 926/1534 [=================>............] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 946/1534 [=================>............] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 966/1534 [=================>............] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 987/1534 [==================>...........] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1008/1534 [==================>...........] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1029/1534 [===================>..........] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1050/1534 [===================>..........] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1071/1534 [===================>..........] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1092/1534 [====================>.........] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1113/1534 [====================>.........] - ETA: 1s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1134/1534 [=====================>........] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1154/1534 [=====================>........] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0699"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1174/1534 [=====================>........] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1195/1534 [======================>.......] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1216/1534 [======================>.......] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1236/1534 [=======================>......] - ETA: 0s - loss: 0.0090 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1256/1534 [=======================>......] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0698"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1276/1534 [=======================>......] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1297/1534 [========================>.....] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1318/1534 [========================>.....] - ETA: 0s - loss: 0.0090 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1338/1534 [=========================>....] - ETA: 0s - loss: 0.0090 - mean_absolute_error: 0.0697"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1359/1534 [=========================>....] - ETA: 0s - loss: 0.0090 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1380/1534 [=========================>....] - ETA: 0s - loss: 0.0090 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1401/1534 [==========================>...] - ETA: 0s - loss: 0.0090 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1422/1534 [==========================>...] - ETA: 0s - loss: 0.0090 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1443/1534 [===========================>..] - ETA: 0s - loss: 0.0090 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1464/1534 [===========================>..] - ETA: 0s - loss: 0.0091 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1484/1534 [============================>.] - ETA: 0s - loss: 0.0090 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1505/1534 [============================>.] - ETA: 0s - loss: 0.0090 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1525/1534 [============================>.] - ETA: 0s - loss: 0.0090 - mean_absolute_error: 0.0696"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1534/1534 [==============================] - 5s 3ms/step - loss: 0.0090 - mean_absolute_error: 0.0696 - val_loss: 0.0087 - val_mean_absolute_error: 0.0688\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/439 [..............................] - ETA: 30s - loss: 0.0067 - mean_absolute_error: 0.0662"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 24/439 [>.............................] - ETA: 0s - loss: 0.0088 - mean_absolute_error: 0.0687 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 48/439 [==>...........................] - ETA: 0s - loss: 0.0087 - mean_absolute_error: 0.0690"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 73/439 [===>..........................] - ETA: 0s - loss: 0.0086 - mean_absolute_error: 0.0687"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 98/439 [=====>........................] - ETA: 0s - loss: 0.0085 - mean_absolute_error: 0.0683"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "123/439 [=======>......................] - ETA: 0s - loss: 0.0089 - mean_absolute_error: 0.0692"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "148/439 [=========>....................] - ETA: 0s - loss: 0.0089 - mean_absolute_error: 0.0693"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "175/439 [==========>...................] - ETA: 0s - loss: 0.0089 - mean_absolute_error: 0.0691"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "200/439 [============>.................] - ETA: 0s - loss: 0.0090 - mean_absolute_error: 0.0695"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "225/439 [==============>...............] - ETA: 0s - loss: 0.0089 - mean_absolute_error: 0.0693"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "250/439 [================>.............] - ETA: 0s - loss: 0.0089 - mean_absolute_error: 0.0694"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "275/439 [=================>............] - ETA: 0s - loss: 0.0088 - mean_absolute_error: 0.0689"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "300/439 [===================>..........] - ETA: 0s - loss: 0.0087 - mean_absolute_error: 0.0688"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "325/439 [=====================>........] - ETA: 0s - loss: 0.0087 - mean_absolute_error: 0.0687"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "350/439 [======================>.......] - ETA: 0s - loss: 0.0087 - mean_absolute_error: 0.0686"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "374/439 [========================>.....] - ETA: 0s - loss: 0.0087 - mean_absolute_error: 0.0686"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "399/439 [==========================>...] - ETA: 0s - loss: 0.0087 - mean_absolute_error: 0.0685"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "424/439 [===========================>..] - ETA: 0s - loss: 0.0087 - mean_absolute_error: 0.0687"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "439/439 [==============================] - 1s 2ms/step - loss: 0.0087 - mean_absolute_error: 0.0688\n"
     ]
    }
   ],
   "source": [
    "history = compile_and_fit(linear, single_step_window)\n",
    "\n",
    "val_performance['Linear'] = linear.evaluate(single_step_window.val)\n",
    "performance['Linear'] = linear.evaluate(single_step_window.test, verbose=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "7U9XukYh8beN"
   },
   "source": [
    "`baseline` 모델과 마찬가지로 선형 모델은 넓은 범위의 배치에서 호출할 수 있습니다. 이러한 방식으로 모델은 연속적인 타임스텝에 대해 일련의 독립적인 예측을 수행합니다. `time` 축은 다른 `batch` 축처럼 작동합니다. 각 타임스텝에서 예측 사이에 상호 작용은 없습니다.\n",
    "\n",
    "![A single step prediction](images/wide_window.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:56:01.762532Z",
     "iopub.status.busy": "2022-12-14T22:56:01.761918Z",
     "iopub.status.idle": "2022-12-14T22:56:01.767437Z",
     "shell.execute_reply": "2022-12-14T22:56:01.766698Z"
    },
    "id": "K9UVM5Sw9KQN"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Input shape: (32, 24, 19)\n",
      "Output shape: (32, 24, 1)\n"
     ]
    }
   ],
   "source": [
    "print('Input shape:', wide_window.example[0].shape)\n",
    "print('Output shape:', baseline(wide_window.example[0]).shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "X-CGj85oKaOG"
   },
   "source": [
    "다음은 `wide_widow`에 대한 예제 예측을 플롯한 내용입니다. 많은 경우 예측이 단순히 입력 온도를 반환하는 것보다는 분명히 더 낮지만 몇 가지 경우에는 더 나쁘다는 사실에 주목하세요."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:56:01.770839Z",
     "iopub.status.busy": "2022-12-14T22:56:01.770581Z",
     "iopub.status.idle": "2022-12-14T22:56:02.236283Z",
     "shell.execute_reply": "2022-12-14T22:56:02.235537Z"
    },
    "id": "bCC8VVo-OvwV"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x800 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "wide_window.plot(linear)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Is51vU8EMl6c"
   },
   "source": [
    "선형 모델의 한 가지 장점은 해석하기가 상대적으로 간단하다는 것입니다. 레이어의 가중치를 가져와 각 입력에 할당된 가중치를 시각화할 수 있습니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:56:02.241250Z",
     "iopub.status.busy": "2022-12-14T22:56:02.240618Z",
     "iopub.status.idle": "2022-12-14T22:56:02.450194Z",
     "shell.execute_reply": "2022-12-14T22:56:02.449486Z"
    },
    "id": "d4uCTbsmK8VI"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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AtgirAAAAsC3CKgAAAGyLsAoAAADbIqwCAADAtgirAAAAsC3CKgAAAGyLsAoAAADbIqwCAADAtgirAAAAsC3CKgAAAGyLsAoAAADbIqwCAADAttK4ewAAUhbW7zdLX//I8AaWvj4AAM7AnVUAAADYFmEVAAAAtkVYBQAAgG0RVgEAAGBbhFUAAADYFmEVAAAAtkVYBQAAgG0RVgEAAGBbhFUAAADYFmEVAAAAtkVYBQAAgG0RVgEAAGBbhFUAAADYFmEVAAAAtkVYBQAAgG0RVgEAAGBbLgmrY8aMUVhYmHx8fFShQgWtX7/+vudOmDBBVatWVZYsWZQlSxZFRkY+8HwAAACkXpaH1enTp6tnz54aNGiQNm3apFKlSikqKkqnT59O8fxly5bpxRdf1NKlS7VmzRqFhoaqTp06+uuvv6weKgAAAGzG8rA6YsQIdejQQW3atFHRokU1duxYZciQQZMmTUrx/G+//VavvfaaSpcurSJFiujLL79UQkKCFi9ebPVQAQAAYDOWhtWbN29q48aNioyM/P+Cnp6KjIzUmjVrHuo1rl69qlu3bikgICDF52/cuKHY2NgkDwAAAKQOlobVs2fPKj4+XkFBQUmOBwUFKSYm5qFeo2/fvsqZM2eSwHu3YcOGyc/Pz/EIDQ391+MGAACAPdi6G8Dw4cP1/fff66effpKPj0+K5/Tv31+XLl1yPI4fP+7iUQIAAMAqaax88cDAQHl5eenUqVNJjp86dUrBwcEP/NqPPvpIw4cP16JFi1SyZMn7nuft7S1vb2+njBcAAAD2Yumd1XTp0qlcuXJJFkclLpaqVKnSfb/ugw8+0NChQzVv3jw98cQTVg4RAAAANmbpnVVJ6tmzp1q1aqUnnnhCERERGjlypOLi4tSmTRtJUsuWLRUSEqJhw4ZJkt5//30NHDhQ06ZNU1hYmGNua6ZMmZQpUyarhwsAAAAbsTysPv/88zpz5owGDhyomJgYlS5dWvPmzXMsujp27Jg8Pf//Bu8XX3yhmzdv6j//+U+S1xk0aJDefvttq4cLAAAAG7E8rEpSly5d1KVLlxSfW7ZsWZI/HzlyxPoBAQAA4JFg624AAAAAeLy55M4qgEdHWL/fLH39I8MbWPr6AIDUhTurAAAAsC3CKgAAAGyLsAoAAADbIqwCAADAtgirAAAAsC3CKgAAAGyLsAoAAADbIqwCAADAtgirAAAAsC3CKgAAAGyLsAoAAADbIqwCAADAtgirAAAAsC3CKgAAAGyLsAoAAADbIqwCAADAtgirAAAAsC3CKgAAAGyLsAoAAADbIqwCAADAtgirAAAAsC3CKgAAAGyLsAoAAADbIqwCAADAtgirAAAAsC3CKgAAAGyLsAoAAADbIqwCAADAtgirAAAAsC3CKgAAAGwrjbsHkBqE9fvN0tc/MryBpa8PAABgV9xZBQAAgG0RVgEAAGBbhFUAAADYFmEVAAAAtkVYBQAAgG0RVgEAAGBbhFUAAADYFmEVAAAAtkVYBQAAgG0RVgEAAGBbhFUAAADYFmEVAAAAtkVYBQAAgG0RVgEAAGBbhFUAAADYFmEVAAAAtkVYBQAAgG0RVgEAAGBbhFUAAADYFmEVAAAAtpXG3QMAHlZYv98sff0jwxtY+voAAOCf484qAAAAbIuwCgAAANsirAIAAMC2CKsAAACwLcIqAAAAbIuwCgAAANsirAIAAMC26LMKAAD+Ffpgw0rcWQUAAIBtEVYBAABgW4RVAAAA2BZhFQAAALZFWAUAAIBtEVYBAABgW7SuAgAglaCFFFIj7qwCAADAtgirAAAAsC3CKgAAAGyLsAoAAADbIqwCAADAtlwSVseMGaOwsDD5+PioQoUKWr9+/QPP/+GHH1SkSBH5+PioRIkSmjt3riuGCQAAAJuxPKxOnz5dPXv21KBBg7Rp0yaVKlVKUVFROn36dIrnr169Wi+++KLatWunzZs3q0mTJmrSpIl27Nhh9VABAABgM5b3WR0xYoQ6dOigNm3aSJLGjh2r3377TZMmTVK/fv2Snf/pp5+qbt266t27tyRp6NChWrhwoUaPHq2xY8daPVwAAIAHop+ta1l6Z/XmzZvauHGjIiMj/7+gp6ciIyO1Zs2aFL9mzZo1Sc6XpKioqPuef+PGDcXGxiZ5AAAAIHWw9M7q2bNnFR8fr6CgoCTHg4KCtGfPnhS/JiYmJsXzY2JiUjx/2LBhGjx4sHMG/D9y1zsgd72zc9f18v/ZNR63/8/UdU3dxw0/N1zjcfv//Lj++33kuwH0799fly5dcjyOHz/u7iEBAADASSy9sxoYGCgvLy+dOnUqyfFTp04pODg4xa8JDg7+R+d7e3vL29vbOQMGAACArVgaVtOlS6dy5cpp8eLFatKkiSQpISFBixcvVpcuXVL8mkqVKmnx4sX673//6zi2cOFCVapUycqhAvdl149FAAB4HFjeDaBnz55q1aqVnnjiCUVERGjkyJGKi4tzdAdo2bKlQkJCNGzYMElS9+7dVb16dX388cdq0KCBvv/+e23YsEHjx4+3eqgAAACwGcvD6vPPP68zZ85o4MCBiomJUenSpTVv3jzHIqpjx47J0/P/p85WrlxZ06ZN01tvvaU33nhDBQsW1M8//6zixYtbPVQAAADYjOVhVZK6dOly34/9ly1bluxYs2bN1KxZM4tHBQAAALtzSVgFAADAv/O4rqEgrAIA4GSPa6gArPDI91kFAABA6kVYBQAAgG0RVgEAAGBbhFUAAADYFmEVAAAAtkVYBQAAgG0RVgEAAGBbhFUAAADYFpsCPMJoOg0AAFI77qwCAADAtgirAAAAsC3CKgAAAGyLsAoAAADbYoEVAAB4JLHQ+PHAnVUAAADYFmEVAAAAtkVYBQAAgG0RVgEAAGBbhFUAAADYFmEVAAAAtkVYBQAAgG0RVgEAAGBbhFUAAADYFmEVAAAAtkVYBQAAgG0RVgEAAGBbhFUAAADYFmEVAAAAtkVYBQAAgG0RVgEAAGBbhFUAAADYFmEVAAAAtkVYBQAAgG0RVgEAAGBbhFUAAADYFmEVAAAAtkVYBQAAgG0RVgEAAGBbhFUAAADYFmEVAAAAtkVYBQAAgG0RVgEAAGBbhFUAAADYVhp3DwAA3OnI8AbuHgIA4AG4swoAAADbIqwCAADAtgirAAAAsC3CKgAAAGyLsAoAAADbIqwCAADAtmhdBcAWaCEFAEgJd1YBAABgW4RVAAAA2BZhFQAAALZFWAUAAIBtEVYBAABgW4RVAAAA2BZhFQAAALZFWAUAAIBtEVYBAABgW4RVAAAA2BZhFQAAALZFWAUAAIBtEVYBAABgW4RVAAAA2BZhFQAAALaVxt0DAAC4zpHhDdw9BAD4R7izCgAAANsirAIAAMC2CKsAAACwLcIqAAAAbIuwCgAAANuyrBvA+fPn1bVrV82ZM0eenp569tln9emnnypTpkz3PX/QoEFasGCBjh07pmzZsqlJkyYaOnSo/Pz8rBomALgFq/IB4OFYdmf15Zdf1s6dO7Vw4UL9+uuvWrFihV555ZX7nn/ixAmdOHFCH330kXbs2KEpU6Zo3rx5ateunVVDBAAAgM15GGOMs1909+7dKlq0qP744w898cQTkqR58+apfv36+vPPP5UzZ86Hep0ffvhBzZs3V1xcnNKkebibwLGxsfLz89OlS5fk6+v7P18DAAAArPFP8pold1bXrFkjf39/R1CVpMjISHl6emrdunUP/TqJF/CgoHrjxg3FxsYmeQAAACB1sCSsxsTEKHv27EmOpUmTRgEBAYqJiXmo1zh79qyGDh36wKkDkjRs2DD5+fk5HqGhof/zuAEAAGAv/yis9uvXTx4eHg987Nmz518PKjY2Vg0aNFDRokX19ttvP/Dc/v3769KlS47H8ePH/3V9AAAA2MM/6gbQq1cvtW7d+oHn5MuXT8HBwTp9+nSS47dv39b58+cVHBz8wK+/fPmy6tatq8yZM+unn35S2rRpH3i+t7e3vL29H2r8AAAAeLT8o7CaLVs2ZcuW7W/Pq1Spki5evKiNGzeqXLlykqQlS5YoISFBFSpUuO/XxcbGKioqSt7e3po9e7Z8fHz+yfAAAACQylgyZzU8PFx169ZVhw4dtH79eq1atUpdunTRCy+84OgE8Ndff6lIkSJav369pDtBtU6dOoqLi9PEiRMVGxurmJgYxcTEKD4+3ophAgAAwOYs2xTg22+/VZcuXVS7dm3HpgCjRo1yPH/r1i3t3btXV69elSRt2rTJ0SmgQIECSV7r8OHDCgsLs2qoAAAAsClL+qy6E31WAQAA7M3tfVYBAAAAZyCsAgAAwLYIqwAAALAtwioAAABsi7AKAAAA2yKsAgAAwLYIqwAAALAtwioAAABsi7AKAAAA27Jsu1V3SdyQKzY21s0jAQAAQEoSc9rDbKSa6sLq5cuXJUmhoaFuHgkAAAAe5PLly/Lz83vgOR7mYSLtIyQhIUEnTpxQ5syZ5eHh4e7hJBMbG6vQ0FAdP378b/fCpS51qUtd6lKXutR9lOo+LGOMLl++rJw5c8rT88GzUlPdnVVPT0/lypXL3cP4W76+vm755qEudalLXepSl7rUtYO/u6OaiAVWAAAAsC3CKgAAAGyLsOpi3t7eGjRokLy9valLXepSl7rUpS51U1VdK6S6BVYAAABIPbizCgAAANsirAIAAMC2CKsAAACwLcIqAAAAbIuwCgCATVy9etXdQwBsJ9XtYIU7Dh8+rJUrV+ro0aO6evWqsmXLpjJlyqhSpUry8fGxrO6NGze0bt26ZHXz5s1rWc1Ex44dS1K3WLFiLmnZ4c5rvnsMqaE9ycNy1fXa4e/Wldz1c8OdDh06pHz58rm0Zu3atTV16lSFhIQkOb5+/Xo1b95c+/bts6RuWFiY2rZtq9atWyt37tyW1LifxYsXa/HixTp9+rQSEhKSPDdp0iRLah4/flweHh6OXS3Xr1+vadOmqWjRonrllVcsqZno4sWLWr9+fYrX27JlS0trJ4qNjdWSJUtUuHBhhYeHu6SmZQwsEx8fb5YsWWIGDx5s2rZta1544QXTtWtXM2nSJHPs2DFLan7zzTemfPnyxsPDwwQHB5uyZcuaKlWqmPDwcJMuXTrj6+trXn31VXPkyBGn1o2OjjbNmjUzPj4+xsvLywQEBJiQkBCTPn164+npaQoUKGA++OADExsb69S6hw8fNn369DG5c+c2np6exsPDw/Hw9vY2kZGRZsaMGSY+Pt6pdY1x3zUbY8zcuXNNy5YtTd68eU2aNGmMp6enyZw5s6lWrZp55513zF9//eX0msYYc+HCBTNp0iTTpk0bU6tWLVOxYkXTsGFDM3DgQLNq1SpLahrj+ut159+tMa7/2eGunxt3O3369H2f27Ztm2V1PTw8TI0aNczXX39trl27Zlmdu9WvX98EBASY77//3hhz5+970KBBJm3atKZ79+6W1f3kk09MqVKljJeXl4mMjDTfffeduX79umX1Er399tvG09PTREREmMaNG5smTZokeVjlySefNFOnTjXGGHPy5Enj6+trKlWqZAIDA83gwYMtqzt79myTOXNm4+HhYfz8/Iy/v7/jkSVLFsvqNmvWzHz22WfGGGOuXr1qChYsaNKmTWvSpEljZs6caVldVyCsWuDq1atm6NChJmfOnMbHx8dUrFjRNG3a1Lz88sumXr16JjQ01Hh5eZl69eqZNWvWOK1u6dKlTUREhBkzZkyKv9CuX79uli5dajp27GgCAwPNjBkznFK3YcOGJiQkxPTu3dusWLHCXL16NcnzBw8eNFOmTDFRUVEmODjYLFiwwCl1u3btanx9fU2zZs3M1KlTzZ49e0xsbKy5deuWOXXqlFm8eLF5++23TZEiRUyxYsXM+vXrnVLXGPdd86xZs0zBggVNcHCwadu2rRk7dqyZPXu2WbhwoZk+fboZMGCAqVGjhvH29jYdO3Z8YAD4J/766y/Trl074+PjY/Lly2deeOEF07NnT/Pmm2+aV1991VStWtVkyJDBhIeHO34BO4M7rtddf7fGuOdnh7t+btwrKCjI/Prrr8mOf/jhh8bHx8eSmsYYs3nzZtOtWzeTLVs24+fnZ1555RWzbt06y+olGj16tMmQIYN58cUXTaVKlUzOnDnN/PnzLa9rjDEbN240Xbt2NYGBgSZLliymc+fOZuPGjZbVCw4OdoRGV/L39zd79uwxxhjz6aefmsqVKxtjjJk/f77JmzevZXULFixounfvbuLi4iyrkZKgoCCzZcsWY4wx3377rSlQoICJi4szn3/+uSldurRLx+JshFUL5MqVyzRr1sz89ttv5ubNmymec+TIEfPee++ZPHnymPHjxzul7rx58x763LNnz5oNGzY4pe7YsWPve5332rlzp1m0aJFT6vbr18+cPXv2oc79/fffzY8//uiUusa475orVqxofv3117+9U/znn3+avn37mhEjRjilbvbs2U3v3r3Nzp0773vO1atXzbRp00zFihXNhx9+6JS67rhed/3dGuOenx3u+rlxr/fff994e3ubTp06matXr5o///zT1KpVy2TLls3MmjXLkpp3u3Xrlvnxxx9Nw4YNTdq0aU2xYsXMxx9/7LQ3fCnp16+f8fDwMGnTprX0k4n7uXnzphk5cqTx9vY2np6eplSpUmbixIkmISHBqXUCAgLMgQMHnPqaDyNjxozm8OHDxpg7b0KHDx9ujDHm6NGjlr4BypAhgzl48KBlr38/Pj4+jjecLVq0MH379jXG3LnejBkzunw8zkRYtcCuXbse+tybN2+65R+xs926detvz3lQ0IG9Peybgv/1fNzxOP7suNumTZtMsWLFTIECBUxAQICpV6+eOXnypEvHcP36dTNixAjj7e3tmE7UokULc+LECafVOH/+vGnatKnx8/Mz48ePNy+//LLJmDGjGTNmjNNqPMjNmzfN9OnTTd26dY2Xl5epUqWKmTRpkhkyZIgJCgoyL774olPr9enTxwwZMsSpr/kwIiIiTN++fc2KFSuMj4+P467jmjVrTEhIiGV1n3nmGTN9+nTLXv9+ChYsaKZPn26uXLlismXLZhYvXmyMMWbLli0ma9asLh+PMxFWLXTr1i0zePBgc/z4cZfV/Ouvv0yvXr3MpUuXkj138eJF8/rrr5uYmBin133uuece+PzOnTtNUFCQ0+tevXrV/PLLLynOHbx06ZL55ZdfXDInK9H27dvN6NGjzaeffmrZHShj7vyyyZcv3z8KN86q26ZNG3Po0CGX13XH9T5ubt++neTPa9euNcuXL3/oO83/VmxsrHn++edNmjRpTJo0acyUKVNcUtcYY/744w/z6quvmixZsphcuXKZN9980xw6dMisWLHC1K5d25QvX95ptXLmzGmqVKmS5N/R999/bwICAkz9+vWdVudeGzduNF26dDFZs2Y12bJlM7169TK7d+9Ocs727dudftexW7duxt/f31SrVs106dLF9OjRI8nDKkuXLjX+/v7G09PTtGnTxnG8f//+5plnnrGs7pdffmly585tBg0aZGbOnGl++eWXJA+rjBkzxqRJk8b4+/ubUqVKOT6RGjVqlKlRo4ZldV2BsGqxTJkyOT6GcIVevXqZDh063Pf5jh07mj59+ji9bmhoqOnYsWOKz+3atcsEBQVZ8sNh5MiRplatWvd9vnbt2mb06NFOr5uS0aNHm+zZs5tmzZqZJk2aGF9fX/POO+9YVi9nzpxuCW++vr4uD6vGuOd6ExdE3PsICAgwOXPmNNWqVTOTJk1yWr2tW7c+9MOZTpw4YapUqWK8vLxMtWrVzPnz502DBg0cixULFSrk1DuLKYmOjjZhYWGmbNmyZteuXWbChAkmc+bM5rnnnjPnz5+3rO7HH39sihcvbtKmTWsaN25s5syZk2zayfHjx42Xl5fTag4ZMiTFqS3Hjx83kZGRTqtzL09PTxMVFWVmzJhx3zcgV65cMa1bt3Zq3Ro1atz3UbNmTafWutft27eTff8cPnzYnDp1yrKady/0vffh6elpWV1j7rzpmjVrlrl8+bLj2K+//mqio6MtrWs1wqrFGjVq5NK7A8WKFTMrV6687/OrVq0yRYsWdXrdXbt2mcDAQNO/f/8kx3fv3m2Cg4NN48aNk921cYby5cub2bNn3/f5OXPmOPWOyN3uXYxSpEgRc+bMGcefV69ebQIDAy2pbYwx7777rmnVqtVDTcFwppYtWzptLuw/4Y7rHTFihMmaNatp3ry5GTVqlBk1apRp3ry5CQwMNO+++65p37698fb2dtq888RfZg/6RWfFL7wWLVqYypUrm9mzZ5vnn3/eVK5c2VStWtX8+eef5ujRo6ZKlSqmc+fOTq15r3Tp0pk+ffokCVEHDhwwFStWtOQj28Q3XAUKFDDDhg17YBi/ceOGS3+OW8XKbg52dvr0abNy5UqzcuVKS+cg20lCQoLT5x67E31WLVavXj3169dP27dvV7ly5ZQxY8Ykzzdq1Mip9Q4fPvzA/nm5cuXSkSNHnFpTksLDwzV37lzVrl1bAQEBev3117Vnzx7VrFlT5cuX18yZM+Xl5eX0uvv371epUqXu+3zJkiW1f/9+p9eVpMjISL322mvq1q2bPDw8lDVrVs2bN0/NmjXTzZs3tWjRImXLls2S2pL0xx9/aPHixVqwYIFKlCiR7Htr1qxZltQtWLCghgwZolWrVqX4Pd2tWzdL6rrjeqOjo/XOO++oU6dOSY6PGzdOCxYs0I8//qiSJUtq1KhR6tChw7+ud/jw4X/9Gv+LRYsWadasWapYsaKqVKmiwMBALVy40NEHdMiQIU65vpQcPnxYefPm1YIFC1S9evUkz+XPn1+rVq3Su+++6/S6+fPnV548eVSjRg2FhIQk64V5t3Tp0qlVq1b/umaePHlUq1Yt1apVSzVq1FBoaOi/fs1/WrdmzZqOvqOpXVxcnLp27aqpU6c6/n69vLzUsmVLffbZZ8qQIYObR+h8U6dO1Ycffuj4vVeoUCH17t1bLVq0cPPI/h0PY4xx9yBSM0/P+28S5uHhofj4eKfWCwwM1KxZs1StWrUUn1+xYoWaNm2qs2fPOrVuoiVLlujpp59Wnz59NGHCBJUpU0azZs1SunTpLKmXOXNmLVu2TOXKlUvx+Y0bN6pGjRq6fPmy02vHxsaqX79+2rBhg8aPH6906dKpRYsW2rx5szw8PBQeHq7JkyerfPnyTq8tSW3atHng85MnT7ak7oMa4nt4eOjQoUOW1HXH9WbKlElbtmxRgQIFkhw/cOCASpcurStXrujgwYMqWbKk4uLinF7fVdKnT699+/Y5wtO9133s2DEVKVLEkt2VPD09lSdPHtWsWdMR4lwRppYtW+Z4rFu3Tjdv3lS+fPkcga5mzZoKCgpyas233347Sb28efM6rrtmzZoKDg52aj131m3atKmmTJkiX19fNW3a9IHnWvXGumPHjlq0aJFGjx6tKlWqSLrzBrRbt2566qmn9MUXXzit1qhRo/TKK6/Ix8dHo0aNeuC5Vr2hHzFihAYMGKAuXbokud4xY8bonXfeUY8ePSyp6xLuvrUL56pfv75p3779fZ9v166dqVevnqVj+Omnn0yaNGlM/fr1LV+YUaFCBUc7kpS89957pkKFCpaOYdWqVaZUqVKmR48eJi4uzsTGxpoLFy5YWhOuERoamuKUhxEjRpjQ0FBjzJ15plYsHjTmzsfgXbp0MbVr1za1a9c2Xbt2taQDQO7cuZP0Fu3bt685d+6c489btmyxbErL0qVLzaBBg0z16tWNj4+PY9OFV155xXz33XeWLAi917Vr18zixYvNgAEDTNWqVR2tnKyYMmXMnY4DixcvNgMHDjTVqlVz1CtSpIh57bXXLKnp6rqtW7d2LHxt3br1Ax9WyZo1q1m6dGmy40uWLHH693NYWJijC0pYWNh9H1b2dw0LCzNfffVVsuNTpkwxYWFhltV1BcJqKrNkyRLj5eVlevXqleSHfExMjOnZs6fx8vJytLNwpnsXoqRJk8Zkzpw52cIUZxs3bpzJmDGjmTNnTrLnZs+ebTJmzGjGjRvn9Lr3unXrlhkyZIgpVKhQio3N8WgaP3688fLyMg0bNjRDhw41Q4cONY0aNTJp0qQxX375pTHGmI8++uhvu2H8L+bNm2fSpUtnIiIiHKumIyIijLe3t1M3IjDmztz6kSNH3vf50aNHP3Aho7O4OjTe68aNG2bJkiWmd+/extfX1/LFMInOnz9v3nzzTZfWdGddV0mfPn2KizJ37NhhMmTI4IYRWcvb29vs378/2fF9+/YZb29vN4zIeZgG4AJxcXFavny5jh07pps3byZ5zoqPA8aNG6fu3bvr1q1b8vX1lYeHhy5duqS0adPqk08+0auvvur0ml999dVDneeMeV/3at68uaZNm6YiRYqocOHCkqQ9e/Zo3759eu655/Tdd985vaYk3b59W+PHj9fu3btVqlQptWnTRgcPHlSnTp2UNWtWjR492ukfI95r5syZmjFjRorfW5s2bbKs7p9//qnZs2enWHfEiBGW1XXH9a5atUqjR4/W3r17JUmFCxdW165dVblyZUvqJSpTpoyioqI0fPjwJMf79eunBQsWWPr3e6/169crQ4YMKl68uEvq3bx5U6tWrdLvv/+ucePG6cqVK06fMpVYZ+3atVq6dKnjY/LQ0FBVq1ZN1apVU/Xq1R+4BuDf1F2zZk2SaQghISGOmlbtHe+uuteuXZMxxjFH9OjRo/rpp59UtGhR1alTx5KaklS7dm1lzZpVU6dOlY+Pj2MsrVq10vnz57Vo0SLLat8tPj5e27dvV548eZQlSxbL6hQvXlwvvfSS3njjjSTH33nnHU2fPl3bt2+3rLbl3ByWU71NmzaZ4OBg4+vra7y8vEy2bNmMh4eHyZgxo6UfB/z5559mxIgR5rXXXjOvvvqq+eSTT1za79XVpk+fbho3bmyKFi1qwsPDTePGjS1vytyyZUsTHh5u+vbtaypXrmy6du3qeO7LL780efPmNZ9//rll9T/99FOTKVMm06VLF5MuXTrTsWNHExkZafz8/Mwbb7xhWd1FixaZDBkymOLFi5s0adKY0qVLG39/f+Pn52dpGxp3Xe/93LsNq7N5e3ubffv2JTu+d+9eS+6S3L5929FOKSEhwZLuHfdz48YNs3z5cvP222+bGjVqmPTp05tChQqZ9u3bm6lTp5qjR486vWbNmjVNhgwZTLFixcxrr71mvvvuO8vbcw0ePNhRNzw83HTs2NFMmzbN/PXXX6mybqKnnnrKfPHFF8YYYy5cuGCyZ89ucuXKZXx8fCz9Gbl9+3aTM2dOkzVrVlOrVi1Tq1YtkzVrVhMSEmJ27NhhWd3u3bs7Pnm5ffu2qVy5suP3fkrTEpxl5syZxsvLy0RFRZkhQ4aYIUOGmKioKJMmTRqX7AJnJcKqxapXr246dOhg4uPjTaZMmczBgwfNsWPHTLVq1Zy6/ac7pab2GP+En5+f4yOmuLg4ky9fviTPnzp1yuk7wdytcOHCZtq0acYY4/jeMsaYAQMGWNpmqHz58mbgwIFJ6l6+fNk0atTI0l887rjeu9+A3O3KlSuWN9nOlSuXmTFjRrLj06dPd8yXdaaPP/7YMT931KhR5uOPP3Z6jZS4IzQaY0yaNGlMaGio6dq1q/nxxx9dsuuah4eHyZMnj/niiy9cusubu+omypo1qyMcTpgwwZQsWdLEx8ebGTNmmCJFilhaOy4uzowfP9707NnT9OzZ00yYMMHyN5ohISHmjz/+MMbcWcORM2dOs3fvXvPWW2+ZypUrW1p7w4YN5uWXXzZly5Y1ZcuWNS+//LLZtGmTpTVdgbBqMT8/P7Nnzx7HfyeGm7Vr15rChQtbVvfeHTMSH7NnzzYLFixwalP38PBw891335kbN2488Lx9+/aZTp06mWHDhjmtdqJLly6l+IiNjf3bcf2vChUqZEaOHGlu3LhhaT/X+0mfPr2jb2K2bNkcWwnu27fPBAQEWFY3U6ZMjkU+/v7+jl9CW7ZsMXny5LGsrjuuN1++fI5gnujy5cvmySefNE8++aQlNRMNHjzY+Pv7m+HDh5sVK1aYFStWmGHDhhl/f39Ltq68efOmqVq1qtmyZYupVq2ay/rZuiM0GnPnDcfvv/9u+vbtayIiIky6dOlM8eLFTefOnc0PP/xgST/OefPmmb59+5oKFSo46nXp0sWyeu6umyh9+vSOu+PNmjUzb7/9tjHmTq/q9OnTW17f1by9vR2fZHbo0MF0797dGHOnt2/mzJndOLJHF2HVYoGBgY6P8goWLGjmzZtnjLnTLN/KCd73ay5+d1PxxJ1q/q1FixaZcuXKmSxZspjnnnvOfPDBB+abb74xM2fONBMmTDA9evQw5cuXNxkyZDB9+vQxFy9edMIVJpV4Tfd75M6d2wwcODDFXWP+VwsWLDDZsmUznp6eJiQkxKxatcppr/0w8ubN63jHXK5cOTN27FhjjDHz58+3ZDFboqCgIMebrvDwcMf2gVu2bDEZM2a0rK47rvfAgQMmR44c5pNPPjHG3NkOtFKlSqZq1armypUrltRMlJCQYEaMGGFCQkIc/35DQkLMyJEjnf5pxttvv20GDx5smjVrZjJlymSee+45M3jwYDN48GCn1kmJO0JjSmJjY83cuXNN7969Tfny5U26dOlMsWLFLK3322+/mT59+jjqFS1a1PLNF9xRt0SJEubTTz81x44dM76+vmb16tXGmDt3Aa3qpGHMnW4wEydOTHZ84sSJD+wi82/lzp3bzJ8/39y+fduEhoY6Ft3u2LHD+Pv7W1b3t99+c2SMu82bN8/MnTvXsrquQFi12FNPPWW+/fZbY4wx7du3NxEREeabb74xUVFRJiIiwrK6ixYtMhUqVDCLFi0ysbGxJjY21ixatMhUqlTJ/PbbbyY6OtoUK1bMtG3b1mk1V65cabp06WJKlSpl/P39jbe3twkJCTFPP/20+eyzzyzdMvGrr74yuXLlMm+99ZaZPXu2mT17tnnrrbdMaGioGTdunHnnnXeMv7+/effdd51aNyEhwW07orRr185xh2L06NEmffr0JjIy0vj7+zv17/VejRs3duzY1KtXL1OgQAHzzjvvmLJly5ratWtbVtdd17t161YTEBBgPv30U1OxYkVTvXp1y4PqvRL/DVtl2bJlZtmyZaZ79+4mPDzc/Pe//3UcczVXh8ZE8fHxZu3atWbYsGGmTp06JkOGDC5ZIX/79m2zevVq069fP5euyndl3R9++MGkTZvWeHp6mqeeespx/L333jN169a1rG6ePHlSvImwdu1aS1s5DRo0yPj5+ZkiRYqY3Llzm+vXrxtj7oTkihUrWla3RIkS5rfffkt2/PfffzclS5a0rK4rEFYt9scff5glS5YYY+7MYYyKijKZM2c2ZcuWdXyMaYVixYql+I80Ojra0QZm4cKFlsx9c4datWqluKBq+vTpjpY7U6dOtXTqhavFx8cn+aj2u+++M127djWjRo2ybOqDMcYcPHjQsTf9lStXTMeOHU2JEiVM06ZNLd3O0V3Xa8ydrXMzZsxoatWqZfl8N3c5ffq0qVSpkrl06ZKpVKlSkq2DXclVoTE+Pt6sW7fOvP/++6Zu3bomc+bMxtPT04SGhpqWLVuayZMnW/L9nFh3+PDhSermzp3btGrVyrJtXd1VN9HJkyfNpk2bkny6tW7dOrN7927Lanp7e6c45e3gwYOWt3L64YcfzIgRI5IsbJ4yZYr5+eefLavp4+NjDh8+nOz44cOHH/lWXbSuSqXSp0+vP/74I1mrme3btysiIkLXrl3T0aNHFR4ebsmuNK6WPn16bdu2TQULFkxyPHE71qtXr+rw4cMqVqyYU663bt26evvtt1WxYsUHnnf58mV9/vnnypQpkzp37vyv68J6ZcqUkYeHR7LjR48eVfbs2ZU+fXrHMSvbR507d04DBw7U0qVLdfr06WTbgZ4/f96p9caNG6fQ0FDVr19f8+fP15EjR9SxY0en1khJQkKCNmzYoGXLlmnp0qVatWqV4uLiFBIS4thJqmbNmsqTJ49T6/r6+iouLk7BwcGOGjVq1FD+/PmdWudu9erV0+rVq3X58mXlzJnTUbNmzZrKly9fqqvrbgULFtSgQYPUvHnzJMe//vprDRo0yLLd9twlODhY06ZNU61atZIcX7RokV566SWdPn3aTSP799K4ewCPi9OnTzv6NBYpUsTSPeMlqVy5curdu7emTp3qqHXmzBn16dPHsf3n/v37XbY3tdVCQ0M1ceLEZD0pJ06c6LjGc+fOOa3HXbNmzfTss8/Kz89PDRs21BNPPKGcOXPKx8dHFy5c0K5duxQdHa25c+eqQYMG+vDDD51S914XLlzQxIkTtXv3bklS0aJF1aZNGwUEBFhS724bNmxIUvd+W946kyuut0mTJk57rX+jRYsWOnDggNq1a6egoKAUA7QztWvXzrE9dJ06dZKFY6v4+/snCY2ffPKJ5aFRkj788EPVrFlThQoVsrTO3fz9/R11731jnRrruluHDh303//+V7du3XIEuMWLF6tPnz7q1auXm0fnfI0bN9Z///tf/fTTT45/PwcOHFCvXr3UqFEjN4/uX3L3rd3ULjY21jRv3tykSZPGsUgiTZo05uWXX7ZkoVGiPXv2mMKFC5t06dKZ/Pnzm/z585t06dKZIkWKmL179xpj7rTUmDp1qmVjcKVffvnFpEuXzpQsWdK0a9fOtGvXzpQqVcp4e3s7drf6/PPPTY8ePZxW8/r16+brr782Tz/9tPH390+yiK148eKmV69eKe6e4izLly83fn5+JjQ01DzzzDPmmWeeMblz5za+vr5m+fLlltU9fvy4efLJJ42Hh4djZzIPDw9TpUoVS3v5uvJ6E9tiuVOmTJksnSp0L3e1rho7dqzjZxLgTAkJCaZPnz6ObXw9PT1NhgwZXLJw0B0uXrxoKlasaNKkSePY3jVNmjSmZs2aj/wW4EwDsNjzzz+vzZs367PPPlOlSpUkSWvWrFH37t1VunRpff/995bVTkhI0IIFC7Rv3z5Jd3beeeqppxx3T1Kbw4cPa9y4cUmut2PHjgoLC3NJ/UuXLunatWvKmjWr0qZNa3m9EiVKqFKlSvriiy/k5eUl6c5OKa+99ppWr15t2W4ldevW1cWLF/XVV185dgzbu3ev2rRpI19fX82bN8+Suq683kyZMiksLEyNGjVSkyZNFBER4bTXfljly5fXZ5999rdTTZzl1q1bql27tj777DN169ZNixcvVpo0fPiGR9+VK1e0e/dupU+fXgULFpS3t7e7h2QZY4wWLlyorVu3Kn369CpZsqSqVavm7mH9a4RVi2XMmFHz58/Xk08+meT4ypUrVbduXcXFxVk+huvXr8vb29vyjxHhWunTp9eWLVscgTHR3r17Vbp0aV27ds2yuqtXr1aZMmWSHN+4caOqVq1q2RxoV17v9evXtXDhQv3yyy/69ddf5eHhoaefflqNGjXSU0895di60Up//PGH+vXrp4EDB6p48eLJ3gD5+vo6rdbgwYPl4eGhHTt26Pfff1f9+vVVrFgxSdLAgQOdVgePp7i4OGXMmNHdw3CJ27dva9q0aYqKirJ8u+3HSeq8xWYjWbNmlZ+fX7Ljfn5+lu4RnJCQoKFDhyokJESZMmXS4cOHJUkDBgzQxIkTLavr5eWV4iTuc+fOOe6GWWXlypVq3ry5KleurL/++kvSnYn00dHRltZ1l7Jlyzrmbt5t9+7dKlWqlGV1Q0NDdevWrWTH4+PjlTNnTsvquvJ6fXx81LBhQ3355Zc6efKkfvzxR2XNmlV9+/ZVYGCgmjRpokmTJunMmTNOrXs3f39/xcbGqlatWsqePbuyZMmiLFmyyN/f3+k/O2rUqKHq1asrZ86cCg0NVc6cOVW9enVVr17dqXXweAoKClLbtm1T7c/iu6VJk0adOnXS9evX3T2U1MWtkxAeA+PGjTORkZHm5MmTjmMnT540derUcTQ1t8LgwYNNvnz5zDfffGPSp0/vmIP3/fffW9rnzcPDw5w6dSrZ8b/++sv4+PhYVnfmzJkmffr0pn379sbb29txvZ999pmpV6+eZXVdbevWrY7H999/b3Lnzm0+/PBDs3LlSrNy5Urz4YcfmrCwMPP9999bNoaff/7ZREREOLYTNOZOi7aKFSuan376yam17HC999q3b5/56KOPTNWqVU26dOnM6NGjLalTvnx5U6lSJfP999+bpUuXOvqeWtX/1C6tq5D6/PTTT6Zx48Ymbdq0pmDBgmbYsGHmr7/+cvewLFO9enVLW1Q9jpgGYIF7W9/s379fN27cUO7cuSVJx44dk7e3twoWLGhZ65sCBQpo3Lhxql27tjJnzqytW7cqX7582rNnjypVqqQLFy44td6oUaMkST169NDQoUOVKVMmx3Px8fFasWKFjhw5os2bNzu1bqIyZcqoR48eatmyZZLr3bx5s+rVq6eYmBhL6rqap6enPDw89Hf/bD08PBQfH++0ulmyZEnyPR0XF6fbt2875jQm/nfGjBmd2lLJXdf7sM6dO6fz589bssI6Q4YM2rx5c7JpD1ZxV+uqx9GUKVPUunXrZMdv376tAQMGaNiwYamqbqIzZ87o66+/1pQpU7R7925FRUWpbdu2atSoUaqaHz1jxgz1799fPXr0ULly5ZJNgShZsqSbRvboIqxaYPDgwQ997qBBgywZQ/r06bVnzx7lyZMnSXjbtWuXIiIidOXKFafWy5s3r6Q7vShz5cqV5CP/dOnSKSwsTEOGDFGFChWcWjdRhgwZtGvXLoWFhSW53kOHDqlo0aKp5iOZo0ePPvS5zuxL+dVXXz30ua1atXJaXXddb6LZs2eneNzDw0M+Pj4qWLCgZQv4qlWrpoEDByoyMtKS14f7+Pr6KioqSuPHj3dM6di7d69eeuklnTt3TkeOHElVdVPy2WefqXfv3rp586YCAwPVqVMn9evXTxkyZHBaDXfNlU1pEXPim26r3lin9rmyqeetjI1YFUD/iaJFi2rlypXJfoHPnDkz2cIYZ0icE1uzZk3NmjXL0vm4KQkODtaBAweSBYfo6GiXNb2+efNmis3bE++oO4MVgexhODOA/hPuut5ETZo0SfHO7t2/eJ588kn9/PPPTv+e79q1q7p3767evXurRIkSyRZYWXV35sSJE4qOjk7xe7lbt26W1HzcbN68Wc2bN1eJEiU0efJk7du3T3369FGTJk30+eefp7q6iU6dOqWvvvpKU6ZM0dGjR/Wf//xH7dq1059//qn3339fa9eu1YIFC5xWLygoSM8995zatm2bbJGzlRJ/H7pS4lzZlOb1pwaEVRe6cuVKsh/+zlzRe7eBAweqVatW+uuvv5SQkKBZs2Zp7969mjp1qn799VdLakrS0qVLHf+d+AveFV0IOnTooO7du2vSpEny8PDQiRMntGbNGr3++usaMGCApbX379+vtm3bavXq1UmOW/kuOpE7g8Xp06dTrGvlR1yuvt6FCxfqzTff1LvvvutoX7V+/XoNGDBAb731lvz8/NSxY0e9/vrrTl+4+Pzzz0uS2rZt6zhm9d2ZKVOmqGPHjkqXLp2yZs2a5N+uh4cHYdVJ8ufPr1WrVum///2v6tatKy8vL3311Vd68cUXU2XdWbNmafLkyZo/f76KFi2q1157Tc2bN5e/v7/jnMqVKys8PNypdb/55htNmTJFtWrVUlhYmNq2bauWLVtauhBUct+b7IiICG3ZssXtb/It4Z6pso+PQ4cOmfr16zv2t058JDaPt9KKFStMZGSkyZYtm0mfPr2pUqWKmT9/vqU1jTHmq6++MsWLFzfe3t7G29vblChRwvLNBxISEsw777xjMmbM6GjO7+PjY9566y1L6xpjTOXKlU21atXM3LlzzebNm82WLVuSPKwyefJkky5dOpMpUyaTJ08eRxPosLAwkzdvXsvqbtiwwRQrVszxfXz3w8rvaXdcb7FixcyqVauSHY+OjjZFixY1xhizcOFCExoa6vTaR44ceeDDCrly5TLvvPNOkv3bYY3Zs2ebbNmymSpVqphs2bKZ2rVru2TRkTvq+vr6mldeecWsX7/+vudcvXrVvP3225bUP336tPn4449NiRIlTJo0aUyDBg3Mjz/+aG7dumVJvUQ7d+40v//+u/nll1+SPKwyffp0ky9fPvPZZ5+Z1atXJ1mgunXrVsvqugJh1WKVK1d26Yped/v4449NhgwZTJ8+fRz/MHv37m0yZMjg2B3HSjdu3DA7d+4069atM5cvX7a8njHGZMiQwezevdslte7mrmBRsmRJ88wzz5i1a9eaw4cPuyREGeOe6/Xx8THbt29Pdnzbtm2O7hZHjhwx6dOnd1rNAQMGmA0bNjjt9f6JgIAAc+DAAbfUfpy88sorxtvb23z00UcmISHBnDx50tSrV88EBASY6dOnp7q6cXFxlr32PzVq1Cjj7e1tPDw8TLZs2cyAAQOcPr6DBw+akiVLOt7A3/1m3so39PfePLi7vtU3x6xGWLVYxowZzZ49e9w9DJcJCwszX331VbLjU6ZMMWFhYW4YkfWeeOIJs3LlSpfXdVewyJQpk9m/f7/L67rjeqtUqWLq1q1rTp8+7Th2+vRpU7duXVO1alVjzJ07q4UKFXJazTZt2phs2bKZkJAQ06lTJzN37lxz48YNp73+g/Tu3dsMGzbMJbUeZ8WKFUvxU5fRo0ebjBkzprq6d7t27Zq5dOlSkofVYmJizPvvv2/Cw8NNhgwZzMsvv2yWLFlipk6daooVK2aeeuopp9Z7+umnTePGjc2ZM2dMpkyZzK5du8zKlStNRESEWbFihVNr3c0dn8a4Ct0ALFazZk29+eabLlnRe297oQdxZnuhu/n4+GjHjh0qUKBAkuP79+9XiRIlnLoqv2nTpg997qxZs5xWV5JiY2Md/71hwwa99dZbeu+991JcCGPVvOQ+ffooICBA/fr1s+T176dJkyZq0aKFnn32WZfWdcf17t27V40bN9bhw4cVGhoqSTp+/Ljy5cunX375RYUKFdLPP/+sy5cvq0WLFk6rm5CQoFWrVmnOnDn65ZdfdPLkST311FNq3Lixnn76aQUEBDit1t3i4+P19NNP69q1ayl+L48YMcKSuo+bGzdu3HfLz71791rWrsxddePi4tS3b1/NmDFD586dS/a8VfP6750r2759+2RzZQ8ePKjw8HDdvHnTaXUDAwO1ZMkSlSxZUn5+flq/fr0KFy6sJUuWqFevXpa1cEzNCKsWO3jwoDp16qTmzZunuGWiMxej3N1e6Ny5c3rnnXcUFRWlSpUqSZLWrFmj+fPna8CAAerRo4fT6t6tePHieumll/TGG28kOf7OO+9o+vTpTt2/vU2bNo7/Nsbop59+kp+fn5544glJd7b/vHjxopo2barJkyc7ra70//0/765/7xsFY/ECK3cFi7Nnz6pVq1aKiIhI8Xu6UaNGltR11/UmJCRowYIF2rdvnySpcOHCeuqpp1JsT2OV3bt3O4Lrxo0bFRERoUaNGunFF19USEiI0+q88847GjhwoAoXLqygoKBkC6yWLFnitFp4fHTu3FlLly7V0KFD1aJFC40ZM0Z//fWXxo0bp+HDh+vll1+2pK6fn59eeOEFtW/fXuXLl0/xnGvXrumDDz5wahefLFmyaNOmTcqbN6/y58+vL7/8UjVr1tTBgwdVokQJy7akTrRr1y4dO3YsWQC36mezKxBWLbZ27Vq99NJLSfrXWb2iV5KeffZZ1axZU126dElyfPTo0Vq0aJF+/vlnS+r++OOPev755xUZGakqVapIklatWqXFixdrxowZeuaZZyyp27dvX50/f15jx4519HiNj4/Xa6+9Jl9fX3344YdOrbd8+fKHPteqLSvdFSzmzJmjFi1aJLm7fHddq76nCVJ3nD59WnPmzNHs2bNVtWpVvf7660577SxZsuiTTz5JsXE8nGvmzJmaMWNGiqHCqs1i3FU3d+7cmjp1qmrUqCFfX19t2rRJBQoU0Ndff63vvvtOc+fOtaTu1atXndq39WFVrVpVvXr1UpMmTfTSSy/pwoULeuuttzR+/Hht3LhRO3bssKTuoUOH9Mwzz2j79u1JWu4l/qx0x8YpTuOm6QePjfDwcNO0aVOXL0bJmDFjivMK9+/fb/ncpA0bNpiXX37ZlC1b1pQtW9a8/PLLZtOmTZbWDAwMTHFu8J49e0xAQIBldW/evGlq1apl9u3bZ1mN+/H39zeTJ092ed08efKYzp07m5iYGJfWddX1fvfddw997rFjx0x0dLSFo3GtoKAgt3wvP24+/fRTkylTJtOlSxeTLl0607FjRxMZGWn8/PzMG2+8kerqZsyY0Rw9etQYY0xISIhZt26dMeZOt5zUOFd23rx55scffzTG3PmdW7hwYePh4WECAwPN4sWLLavrrrmyrkBYtViGDBncshgld+7c5qOPPkp2/KOPPjK5c+d2+Xis5u/vn+JezD///LPx9/e3tHZgYKBbfsG7K1hkypTJLQu7XHW91apVM0WKFDHvv/++2bVrV7LnL168aH777Tfz4osvmsDAQKe2onnmmWce+mGF9957z3Tt2tWS18b/K1y4sJk2bZox5s6/p4MHDxpj7nSC6Ny5c6qrW6JECUf3m9q1a5tevXoZY+6E55CQEMvqXrlyxXTu3Nlky5YtSetIq1flp+TcuXMmISHB0hpZs2Z1tKjy9fV13MBZvHixKV26tKW1rcamABarVauWtm7dmmzBkdUGDx6s9u3ba9myZY4tTtetW6d58+ZpwoQJltaOj4/XTz/95NhJo2jRomrcuLGlez+3adNG7dq108GDBx3N29etW6fhw4cnmdtqhebNm2vixIkaPny4pXXu1b17d3322WcaNWqUS+s2bdpUS5cuVf78+V1a11XXu3z5cs2ePVufffaZ+vfvr4wZMyooKEg+Pj66cOGCYmJiFBgYqNatW2vHjh1O3drQz8/Paa/1v1i/fr2WLFmiX3/9VcWKFUs2L9jZCxUfV8eOHVPlypUl3dka+/Lly5KkFi1aqGLFiho9enSqqtumTRtt3bpV1atXV79+/dSwYUONHj1at27dsnTRXp8+fbR06VJ98cUXKc6VtdqBAwd08OBBVatWTQEBAcl2wnO2+Ph4Zc6cWdKdRV4nTpxQ4cKFlSdPHu3du9fS2lYjrFqsYcOG6tGjh7Zv357iohCrJjy3bt1a4eHhGjVqlOMXTHh4uKKjox3h1Qo7d+5Uo0aNFBMT41hZ+v777ytbtmyaM2eOihcvbkndjz76SMHBwfr444918uRJSVKOHDnUu3dv9erVy5KaiW7fvq1JkyZp0aJFKleuXLK9qK36YeyuYFGoUCH1799f0dHRKX5PW7XLkSuvt1GjRmrUqJHOnj2r6OhoHT16VNeuXVNgYKDKlCmjMmXKWLLAytkLAf8pf3//f9RlA/+b4OBgnT9/Xnny5FHu3Lm1du1alSpVSocPH7Y00Lir7t0LeiMjI7Vnzx5t3LhRBQoUsHTHuzlz5jjmyrZp00ZVq1ZVgQIFlCdPHn377beWLew6d+6cnnvuOS1dulQeHh7av3+/8uXLp3bt2ilLliz6+OOPLalbvHhxbd26VXnz5lWFChX0wQcfKF26dBo/frzLth23CgusLPagX2hWb8XpDpUqVVK2bNn01VdfOfZKv3Dhglq3bq0zZ84k25LUCokLf6xqGXWvmjVr3vc5Kxf+/N0dY6uCT968ee/7nIeHhw4dOmRJXXddr7udOXPGcVekcOHCypYtm9NruGshyuOqffv2Cg0N1aBBgzRmzBj17t1bVapU0YYNG9S0aVOnb93r7rrukilTJu3atUu5c+dWrly5NGvWLEVEROjw4cMqUaKErly5Ykndli1b6vTp0/ryyy8VHh6urVu3Kl++fJo/f7569uypnTt3WlJ3/vz5iouLU9OmTXXgwAE9/fTT2rdvn7Jmzarp06erVq1altR1BcJqKhIXF5fsrp4zz38Y6dOn14YNG1SsWLEkx3fs2KHy5cvr2rVrTq0HpFZxcXHq2rWrpk6dqoSEBEmSl5eXWrZsqc8++8yp4TJDhgyqVauWGjVqpMaNGzt1agOSS0hIUEJCgmNq1Pfff6/Vq1erYMGC6tixo9KlS5dq6iYkJGjKlCmaNWuWjhw5Ig8PD+XNm1f/+c9/1KJFi4fuDf6/KFmypD777DNVr15dkZGRKl26tD766CONGjVKH3zwgf78809L6gYHB2v+/PkqVaqUMmfO7Airhw4dUsmSJS0LySk5f/78P+rBbleuaxQIyxUoUEDDhw93fAyeEmOMFi5cqHr16lky969QoUI6depUsuOnT592+rzdunXrau3atX973uXLl/X+++9rzJgxTq0PWKlnz55avny55syZo4sXL+rixYv65ZdftHz5cqdPbdmzZ4+ioqI0Y8YM5cmTRxUqVNC7777r1L7I+H+enp5J5vC/8MILGjVqlLp27WpZUHVHXWOMGjVqpPbt2+uvv/5SiRIlVKxYMR09elStW7e2rJVhosS5spLUr18/jRkzRj4+PurRo4d69+5tWd24uLgU30yeP3/+vpsyONOBAwc0f/58Xbt2zbINRFyNO6sW+P777/XCCy881LnHjx/XsWPHHD1J/429e/fqjTfe0G+//aZSpUrpiSeeUM6cOR0LQ3bt2qU1a9YoTZo06t+/vzp27OjoSeosc+fOVZ8+ffT222+rYsWKku70mh0yZIiGDx+uJ5980nHuv/2YfuLEiRo4cKD8/PzUsGHDFK83Ojpac+fOVYMGDfThhx8qd+7c/6qmu9WtWzfJ/9v7uXz5sj7//HNlypRJnTt3/td1hw8fru7duyt9+vR/e+66det09uxZNWjQ4F/Xddf12kFgYKBmzpypGjVqJDm+dOlSPffcczpz5owldS9duqS5c+fql19+0bx58xQQEOCYw1u9enWn/8x4XF2/fl3btm3T6dOnHXfOE1nZvN2VdSdPnqzu3bvrl19+STZdasmSJWrSpIlGjx6tli1bOrXu/Rw9etTSubInTpxQzpw5Vb9+fZUrV05Dhw5V5syZtW3bNuXJk0cvvPCCEhISNHPmTKfXlu4/V7Zt27aWzpV1CTd1IUjV3Nn6xhhjjh49aj766CPTuHFjU7p0aVO4cGFTpUoV06VLFzNnzhxz+/Ztp9a7m4eHh+OR2B4kpT87q23I9evXzddff22efvpp4+/vn6RW8eLFTa9evVL8O3hUffnllyZnzpwmPDzc9OnTx8yYMcNER0ebDRs2mIULF5pPP/3UNGvWzGTMmNE899xzjt6G/1aLFi1MYGCgefXVV83cuXPN6dOnHc/dunXLbN261YwZM8ZUqlTJ5MmTxyxfvtwpdd11vXaQPn36FL93d+zYYTJkyOCSMdy8edPMnz/fdOnSxeTOndtkyZLFfPPNNy6pnZr9/vvvJlu2bEl+Xt79syu11H3qqafMsGHD7vv8u+++a+rUqeP0uu7i7+9vvv32W7Njxw6TPXt2U7duXZMuXTrzn//8x4SHh5ugoCBL2/61aNHCREVFmePHjydpTTZv3jxTtGhRy+q6AndWLZLY+mbJkiUPbH3To0ePVDU/zN07O126dEnXrl1T1qxZk60WTy1u3LihH374QdOnT1d0dLQuXbok6c7ipqJFiyoqKkrt2rVTeHi4U+tu3bpVo0eP1syZMxUbGysvLy95e3s7tg4sU6aM2rdvr9atW8vHx8dpdd11ve5Wu3ZtZc2aVVOnTnX8/7x27ZpatWql8+fPa9GiRS4f06ZNmxQfH3/frSvxcAoWLKg6depo4MCBLv357+q6wcHBmjdvnkqXLp3i85s3b1a9evUUExPj9NrumCv7+eefq2/fvqpbt67Gjh2rsWPHauvWrbpy5YrKli2rzp07K0eOHE6vm8hOc2WdjbBqMVe3vnGXIUOG6PXXX2dFsRu4OqAnJCRo27ZtSb6nS5curcDAQMtrS6693vj4eE2ZMkWLFy9O8WNTK7d43bFjh6KionTjxg2VKlVK0p03DD4+Ppo/f36yRYzOsG3bthSPe3h4yMfHR7lz53bJnLvUztfXV5s3b3Z5r2JX102XLp2OHj1634B24sQJ5c2bVzdu3HBqXWOMGjZsqLlz56pUqVIqUqSIjDHavXu3tm/frkaNGlm25fjhw4fVrl077dq1S+PHj7d0Sse9MmfOrE2bNqlgwYJJwuqGDRsUFRWlc+fOuWwszkZYhVN4eXnp5MmTyp49u7uHAjhNly5dNGXKFDVo0EA5cuRIdjfmk08+sbT+1atX9e2332rPnj2S7vRKfvnllx9q7vD/wtPT84F3nNKmTavnn39e48aNc+rd88dN27ZtVaVKFbVr1y5V1/Xy8lJMTMx9262dOnVKOXPmdHoLRzvMlR09erR69Oih8PDwZBvibNq0yam13D1X1hUIq3AKT09PxcTEEFaRqgQGBmrq1KmqX7++u4fiEr/88ov69u2r3r17O3aCW79+vT7++GMNGjRIt2/fVr9+/fT888/ro48+cvNoH11Xr15Vs2bNlC1bNpdurOHqup6enqpXr95978bfuHFD8+bNc3pYrVOnjmrVqqV+/fql+Px7772n5cuXa/78+U6tm+jo0aNq06aNduzYoY4dOyYLq4MGDXJqvSxZsmjMmDEqVaqUatWqpbJly2rJkiVq1KiRdu7cqfPnz2vVqlUuv5PvTIRVOIWnp6dOnTplScNywF1y5sypZcuWqVChQm6pf+LECUVHR6c4BcGKQBMREaGhQ4cqKioqyfH58+drwIABWr9+vX7++Wf16tVLBw8edHr9x8XEiRPVqVMn+fj4KGvWrEnuZlu5sYar6z7sVtfO3tDDnXNlJ0yYoF69eikyMlLjxo1zye9Ed8+VdQXCairjrrmjnp6e8vPz+9tJ6+fPn3fRiIB/7+OPP9ahQ4c0evRolzfVnjJliqNRu6sCTfr06bV582YVKVIkyfE9e/aoTJkyunbtmo4cOaKiRYs6FtbhnwsODla3bt3Ur18/l65dcFddV3PXXNm6detq/fr1GjlypMvacSVy51xZVyCspjLumjvq6empkSNHys/P74HntWrVypL6AwcOVM2aNVWpUiXm0qUio0aN0iuvvCIfHx8dO3ZMoaGhlofGpk2bJvnzkiVLFBAQoGLFiiX72HTWrFmWjSM0NFSdOnVS//79XRYsypQpo1KlSmn8+PGOJvG3bt1Shw4dtHXrVm3evFmrVq1S8+bNdfjwYZeMKTUKCAjQH3/84fKPZd1V19XcNVf2qaee0uTJk5UrVy6nvu4/4cq5sq6U5u9PgbMkvi+w8petO997vPDCC26bs7pmzRqNGDFCt2/fVvny5VW9enXVqFFDVapUsWwxirstXbo02eKBROPGjVPHjh0tqdu2bVt9+umnypw5c5LjiduDTpo0yWm1evbsqRdeeEE+Pj7KmzevS96I3fuGy+pddu7n6tWreuGFF1x6B2zMmDFq1KiRcuXK5Wiavn37dsXHx+vXX3+VJB06dEivvfaay8aUGrVq1UrTp0/XG2+88VjUdTVjjFq3bv3AubJWWLhwoSWv+7COHj2qWbNmKUuWLGrcuHGysPoo486qC0ycOFGffPKJ9u/fL+lOr7v//ve/at++vdNruWvuqB26Ady+fVvr1q3TihUrtHz5cq1evVo3btxQ+fLlFR0d7bZxWcXb21vdunXTe++957jjd/bsWbVp00bR0dG6cOGCJXXv93d99uxZBQcH6/bt206rlTt3bvXv31/169dX3rx5tWHDhvu2yHrUdye7V58+fRQQEHDfRSJWuXz5sr799lvt27dPklS4cGG99NJLyd6c4H/XrVs3TZ06VaVKlVLJkiWT3bEfMWJEqqrrau6aK+tO7pgr60qEVYsNHDhQI0aMUNeuXVWpUiVJd+4CJt6qHzJkiFPruWvuqJ26Aezbt09Lly7VokWL9PPPP8vPz09nz55197CcbvXq1WrZsqUyZcqkadOmOeYsFS5cWFOnTlWePHmcWi82NlbGGGXJkkX79+9P8sMwPj5ec+bMUb9+/XTixAmn1Rw/fry6du36wABsjJGHh4fTP9KT7jThN8Y45oAfPXpUP/30k4oWLao6deo4vd7d4uPj9fTTT+vatWsprtxOLcHicXS/T0SkO5+8WdW/1111YS13zpV1FcKqxbJly6ZRo0bpxRdfTHL8u+++U9euXZ0eotw9d9Rdxo8fr2XLlmn58uW6ceOGqlatqho1aqhGjRoqWbKkyxfHuMqVK1fUqVMnzZw5UwkJCRo6dKj69OljyfX+XQ9ODw8PDR48WG+++aZT616+fFlHjx5VyZIltWjRImXNmjXF8xIb5ztTnTp11LRpU3Xq1EkXL15U4cKFlS5dOp09e1YjRozQq6++6vSaid555x0NHDhQhQsXVlBQULIFVs4KFmvXrlXFihUf6tyrV6/q8OHDlmxIAOB/Y4e5spZzza6ujy8/Pz+zb9++ZMf37t1r/Pz8nF7Pw8PDnDp1yumva3ceHh4me/bs5v333zeXL19293BcZuPGjaZw4cImf/78Jn369KZNmzbmypUrltRatmyZWbp0qfHw8DCzZs0yy5YtczxWr15t/vrrL0vqJpoyZYq5fv26pTXulTVrVrNjxw5jjDETJkwwJUuWNPHx8WbGjBmmSJEiltb29/c3kydPtrSGMcYUKFDA1KlTx8yYMeO+3zs7d+40/fv3N8HBwearr76yfEwAcDfurFqsa9euSps2bbKP7F5//XVdu3ZNY8aMcWo9O8wddYeff/5ZK1as0LJly7R7926VKVPGcWf1ySefTJXbwA4fPlyDBg3SK6+8og8//FAHDhxQixYtFBsbq2+++cYx7cTZjh49qty5c7vlbvXFixc1c+ZMHTx4UL1791ZAQIA2bdqkoKAghYSEOL1ehgwZtGfPHuXOnVvPPfecihUrpkGDBun48eMqXLiwpe2bgoODtXLlShUsWNCyGtKd1f5ffPGFxowZo0OHDqlQoULKmTOnfHx8dOHCBe3Zs0dXrlzRM888ozfeeEMlSpSwdDwAcC/CqsW6du2qqVOnKjQ01PFR27p163Ts2DG1bNkyyTw0Z8xBs9PcUXe5dOmSVq5cqR9++EHfffedPD09df36dXcPy+ly5MihSZMmqV69eo5jt27d0htvvKFRo0ZZtuJ18uTJypQpk5o1a5bk+A8//KCrV69aNsVk27ZtioyMlJ+fn44cOaK9e/cqX758euutt3Ts2DFNnTrV6TVLliyp9u3b65lnnlHx4sU1b948VapUSRs3blSDBg0saSqeaNiwYTp58qRGjRplWY17bdiwQdHR0Tp69KiuXbumwMBAlSlTRjVr1lRAQIDLxgEAdyOsWuxBE9rvxuT2f+/cuXNavny5li1bpmXLlmnnzp3KkiWLqlatqp9++sndw3O6s2fP3ndl/PLly1W9enVL6hYqVEjjxo1L9r29fPlyvfLKK9q7d68ldWvXrq1y5crpgw8+UObMmbV161bly5dPq1ev1ksvvaQjR444vebMmTP10ksvKT4+XrVr19aCBQsk3QmSK1as0O+//+70momeeeYZLVmyRFmzZnV5j1cAsBPCKlKFEiVKaPfu3cqSJYuqVaumGjVqqHr16o5ekXAeHx8f7dmzR2FhYUmOHzlyROHh4bp27Zoldf38/LRp0yblz58/SVg9evSoChcubNnd85iYGJ08eVKlSpVy9Dxdv369fH19k+305Ex/134nNbXdAYAHST0dY/FY69Spk6pXr67ixYu7eygutWHDBs2YMUPHjh3TzZs3kzxn1Z237Nmza9u2bcnC6tatW++7Ut8ZvL29FRsbm+z4vn37LO0pGBwcrODg4CTHIiIiLKuXiDAKAHek3s2B8Vjp3Lmzihcvrps3b2rv3r1ObUxvV99//70qV66s3bt366efftKtW7e0c+dOLVmy5G9bl/0bL774orp166alS5cqPj5e8fHxWrJkibp3764XXnjBsrqNGjXSkCFDdOvWLUl3ps4cO3ZMffv21bPPPmtZXQCAezENAKnCtWvX1KVLF3311VeS7txty5cvn7p27aqQkBCX7wLkCiVLllTHjh3VuXNnx8fiefPmVceOHZUjRw4NHjzYkro3b95UixYt9MMPPzi280tISFDLli01duxYx57yznbp0iX95z//0YYNG3T58mXlzJlTMTExqlSpkubOnauMGTNaUtddzp07p4EDB2rp0qU6ffq0EhISkjzv7I09AMCuCKtIFbp3765Vq1Zp5MiRqlu3rrZt26Z8+fLpl19+0dtvv63Nmze7e4hOlzFjRu3cuVNhYWHKmjWrli1b5pi7W6tWLZ08edLS+vv27dPWrVuVPn16lShRwuk7Zt1PdHS0tm3bpitXrqhs2bKKjIx0SV1Xq1+/vg4cOKB27dol2xRASn0bewDA/TBnFanCzz//rOnTp6tixYpJfqkXK1ZMBw8edOPIrJMlSxZdvnxZkhQSEqIdO3aoRIkSunjxoqX9PxMVKlRIhQoVsrzOvZ588kk9+eSTLq/raitXrlR0dLQlO3M9yPLly/XRRx9p9+7dkqSiRYuqd+/eqlq1qkvHAQCJCKtIFc6cOZNib9m4uLhUu9VqtWrVtHDhQpUoUULNmjVT9+7dtWTJEi1cuFC1a9e2tPaff/6p2bNnp7iwy5l71v+THqPdunVzWl07KFKkiGWdFe7nm2++UZs2bdS0aVPH/89Vq1apdu3amjJlil566SWXjgcAJKYBIJWoVq2amjVrpq5duypz5szatm2b8ubNq65du2r//v2aN2+eu4fodOfPn9f169eVM2dOJSQk6IMPPtDq1atVsGBBvfXWW8qSJYsldRcvXqxGjRopX7582rNnj4oXL64jR47IGKOyZcs6tV9w3rx5k/z5zJkzunr1qvz9/SXd2dEqQ4YMyp49uw4dOuS0unbwxx9/qF+/fho4cKCKFy+erM+qr6+v02uGh4frlVdeUY8ePZIcHzFihCZMmOC42woArkRYRaoQHR2tevXqqXnz5poyZYo6duyoXbt2afXq1Vq+fLnKlSvn7iGmGhEREapXr54GDx7sWNiVPXt2vfzyy6pbt65effVVS+pOmzZNn3/+uSZOnKjChQtLkvbu3asOHTqoY8eOevnlly2p6y779+/XSy+9pE2bNiU5boyRh4eH4uPjnV7T29tbO3fuVIECBZIcP3DggIoXL54qd4IDYH+EVaQaBw8e1PDhw7V161bH4pu+ffum+r3MT58+neJqcas2RMicObO2bNmi/PnzK0uWLIqOjlaxYsW0detWNW7c2JKdpCQpf/78mjlzpsqUKZPk+MaNG/Wf//xHhw8ftqSuu0RERChNmjTq3r17igusrNihrECBAurdu7c6duyY5PjYsWP18ccfa//+/U6vCQB/hzmrSDXy58+vCRMmuHsYLrNx40a1atVKu3fv1r3vOa268ybd6UKQOE81R44cOnjwoIoVKybpzhawVjl58mSK/XPj4+N16tQpy+q6y44dO7R582bHXWRX6NWrl7p166YtW7aocuXKku7MWZ0yZYo+/fRTl40DAO5GWMUjK6XdjO7Hivl97ta2bVsVKlRIEydOTPHOm1UqVqyo6OhohYeHq379+urVq5e2b9+uWbNmqWLFipbVrV27tjp27Kgvv/xSZcuWlXQnsL/66qupsn3VE088oePHj7s0rL766qsKDg7Wxx9/rBkzZki6M491+vTpaty4scvGAQB3YxoAHlmenp4PHdCsusvoTpkzZ9bmzZuTzS+02qFDh3TlyhWVLFlScXFx6tWrl2Nh14gRIyzrt3rmzBm1atVK8+bNcyw2un37tqKiojRlypQUu0E8yn744Qe9/fbb6t27t0qUKJFsgZVV0zwAwG4Iq3hkLV++3PHfR44cUb9+/dS6dWtVqlRJkrRmzRp99dVXGjZsWKpsoN6kSRO1aNHCpVuNxsbGat26dbp586YiIiKULVs2l9VOtG/fPu3Zs0fSnfZO7uj16gqensl3w/bw8LB0gVWimzdvpjgPOnfu3JbVBID7IawiVahdu7bat2+vF198McnxadOmafz48Vq2bJl7Bmahs2fPqlWrVoqIiEixtVGjRo2cWm/Lli2qX7++Tp06JWOMMmfOrBkzZigqKsqpdVJih5DsakePHn3g81bcwd6/f7/atm2r1atXJznuioAMAPdDWEWqkCFDBm3dulUFCxZMcnzfvn0qXbq0S3Z0crU5c+aoRYsWKc7dtSJYREVF6cqVK/roo4/k4+OjoUOHavv27ZavEHdnSH7cVKlSRWnSpFG/fv2UI0eOZNNsXL2bFgBIhFWkEoULF1bjxo31wQcfJDnep08f/fLLL9q7d6+bRmadsLAwPf300xowYICCgoIsrxcYGKgFCxY4FjddvHhRAQEBunjxoqUL2NwVkt1h7dq1D71I7erVqzp8+LCjE4MzZMyYURs3blSRIkWc9poA8G/RDQCpwieffKJnn31Wv//+uypUqCBJWr9+vfbv368ff/zRzaOzxrlz59SjRw+XBFXpzo5ZuXLlcvzZ399fGTNm1Llz5ywNqxs3bkwSkidNmqSAgADFxsamui4PLVq0UL58+dS+fXvVr19fGTNmTHbOrl279M0332jy5Ml6//33nRpWixYtamn7MQD4XxBWkSrUr19f+/fv1xdffOHYErJhw4bq1KmTQkND3Tw6azRt2lRLly5V/vz5XVZz165diomJcfzZGKPdu3fr8uXLjmPOXqXurpDsDrt27dIXX3yht956Sy+99JIKFSqknDlzysfHRxcuXNCePXt05coVPfPMM1qwYIFTNry4exrJ+++/rz59+ui9995LsQNBavv/DeDRwDQAPNKGDBmi119/XRkyZHD3UFzu3Xff1ciRI9WgQYMUg0W3bt2cWi+xVVhKPzKsXKXu6empJUuWKCAgwHGscuXKmjFjRpIQm9paOW3YsEHR0dE6evSorl27psDAQJUpU0Y1a9ZM8v/i37q3BVzi3+PdWGAFwJ0Iq3ikeXl56eTJk6mux+bDyJs3732f8/Dw0KFDh5xa7+9Wpydy9ip1d4Xkx8XdLeD+jhVbvALA32EaAB5pj/N7rcOHD7u03uXLl1W8eHGX1pRcf52Pm8QAeuvWLdWtW1djx45N1lUDANyJsIpHnqu2GbUTd/QdLVmypMqXL6/27dvrhRdeUObMmS2vKbkvJD9u0qZNq23btrl7GACQTPItUoBHTKFChRQQEPDAR2qyZcsWFSlSRFFRUWrYsKEKFCig+fPnW153+fLlKlasmHr16qUcOXKoVatWWrlypeV1S5YsqQoVKmjChAlJFnLB+Zo3b66JEye6exgAkARzVvFI8/T01MiRI+Xn5/fA81LTdqvu7jsaFxenGTNmaMqUKVq5cqUKFCigdu3aqVWrVgoODnZ6vZUrV2ry5MmaOXOmEhIS9Oyzz6p9+/aqWrWq02s97rp27aqpU6eqYMGCKleuXLLWWSNGjHDTyAA8zgireKR5enoqJibmsVpg5a7m/Ck5cOCAJk+erK+//loxMTGqW7euZs+ebUktV4fkx1HNmjXv+5yHh4eWLFniwtEAwB2EVTzSHsduACkF9MyZM2vbtm0P7BBglbi4OH377bfq37+/Ll686JJV+a4Mya62ZMkSdenSRWvXrk325uPSpUuqXLmyxo4dy51lAI8NFljhkfa4vtdyR3P+e61YsUKTJk3Sjz/+KE9PTz333HNq166dpTUTFShQQG+88Yby5Mmj/v3767fffnNJXVcYOXKkOnTokOJdcj8/P3Xs2FEjRowgrAJ4bHBnFXjEuLPv6IkTJzRlyhRNmTJFBw4cUOXKldWuXTs999xzKW4NaoX7heSKFSu6pL7V8uTJo3nz5ik8PDzF5/fs2aM6dero2LFjLh4ZALgHd1aBR4y7+o7Wq1dPixYtUmBgoFq2bKm2bduqcOHCLqmdUkgeNWqUS0Oyq5w6dSrZbmR3S5Mmjc6cOePCEQGAexFWgUeMu/qOpk2bVjNnztTTTz8tLy8vl9V1Z0h2h5CQEO3YsUMFChRI8flt27YpR44cLh4VALgP0wCAR4ynp6dbmvO7S6NGjdSuXTuXh2R36dq1q5YtW6Y//vhDPj4+SZ67du2aIiIiVLNmTY0aNcpNIwQA1yKsAo8Y+o6mbqdOnVLZsmXl5eWlLl26OO4i79mzR2PGjFF8fLw2bdqkoKAgN48UAFyDsAo8oug7mnodPXpUr776qubPn+9YSOfh4aGoqCiNGTPGLS3KAMBdCKtAKpCa+44+zi5cuKADBw7IGKOCBQsqS5Ys7h4SALgcYRVIJdzRnB/Wunjxog4cOCDpTm9Zf39/9w4IANzA090DAPDvrFixQq1bt1ZwcLB69+6tpk2batWqVe4eFv6FI0eOqEGDBgoMDFSFChVUoUIFBQYG6umnn9aRI0fcPTwAcCnurAKPIDs054c1jh8/rvLlyytt2rR67bXXHJsD7Nq1S1988YVu376tP/74Q7ly5XLzSAHANQirwCPmces7+rhp166dDhw4oPnz56fYuqpu3boqWLCgvvzySzeNEABci00BgEeMu5rzwzXmzZun6dOnJwuqkpQ+fXoNHTpUL7zwghtGBgDuwZ1VALARb29vHTx48L4f8//5558qUKCArl+/7uKRAYB7sMAKAGwkR44c2rVr132f37FjB310ATxWCKsAYCNNmjTR66+/rjNnziR77vTp0+rbt6+aNGni+oEBgJswDQAAbOTChQuqUKGCYmJi1Lx5cxUpUkTGGO3evVvTpk1TcHCw1q5dq4CAAHcPFQBcgrAKADZz4cIFvfHGG5o+fbouXrwoSfL399dzzz2n9957j6AK4LFCWAUAmzLGOKYDZMuWTR4eHm4eEQC4HmEVAAAAtsUCKwCwmblz56p9+/bq06ePdu/eneS5CxcuqFatWm4aGQC4HmEVAGxk2rRpatSokWJiYrRmzRqVLVtW3377reP5mzdvavny5W4cIQC4FjtYAYCNfPjhhxoxYoS6desmSZoxY4batm2r69evq127dm4eHQC4HmEVAGxk//79atiwoePPzz33nLJly6ZGjRrp1q1beuaZZ9w4OgBwPcIqANiIr6+vTp06pbx58zqO1axZU7/++quefvpp/fnnn24cHQC4HnNWAcBGIiIi9Pvvvyc7Xr16dc2ZM0cjR450/aAAwI0IqwBgIz169JCPj0+Kz9WoUUNz5sxRy5YtXTwqAHAf+qwCAADAtpizCgA2Ehsb+1Dn+fr6WjwSALAH7qwCgI14eno+cFtVY4w8PDwUHx/vwlEBgPtwZxUAbGTp0qWO/zbGqH79+vryyy8VEhLixlEBgPtwZxUAbCxz5szaunWr8uXL5+6hAIBb0A0AAAAAtkVYBQAAgG0RVgHA5h604AoAUjsWWAGAjTRt2jTJn69fv65OnTopY8aMSY7PmjXLlcMCALchrAKAjfj5+SX5c/Pmzd00EgCwB7oBAAAAwLaYswoAAADbIqwCAADAtgirAAAAsC3CKgAAAGyLsAoAAADbIqwCAADAtgirAAAAsC3CKgAAAGzr/wCSzW8h51drCwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.bar(x = range(len(train_df.columns)),\n",
    "        height=linear.layers[0].kernel[:,0].numpy())\n",
    "axis = plt.gca()\n",
    "axis.set_xticks(range(len(train_df.columns)))\n",
    "_ = axis.set_xticklabels(train_df.columns, rotation=90)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Ylng7215boIY"
   },
   "source": [
    "때로 모델은 입력 `T (degC)`에 가장 많은 가중치를 두지 않습니다. 이것은 무작위 초기화의 위험 중 하나입니다. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "W18e6da1cNbw"
   },
   "source": [
    "### 밀집\n",
    "\n",
    "실제로 여러 타임스텝에서 동작하는 모델을 적용하기 전에 더 깊고 강력한 단일 입력 스텝 모델의 성능을 확인하는 것이 좋습니다.\n",
    "\n",
    "다음 모델은 입력과 출력 사이에 몇 개의 `Dense` 레이어를 쌓는다는 점을 제외하면 `linear` 모델과 유사합니다. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:56:02.454701Z",
     "iopub.status.busy": "2022-12-14T22:56:02.454014Z",
     "iopub.status.idle": "2022-12-14T22:57:26.455127Z",
     "shell.execute_reply": "2022-12-14T22:57:26.454218Z"
    },
    "id": "Z86WkYp7cNAD"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/20\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "   1/1534 [..............................] - ETA: 35:16 - loss: 0.6807 - mean_absolute_error: 0.6755"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  15/1534 [..............................] - ETA: 5s - loss: 0.2967 - mean_absolute_error: 0.3759   "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  30/1534 [..............................] - ETA: 5s - loss: 0.1886 - mean_absolute_error: 0.2997"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  45/1534 [..............................] - ETA: 5s - loss: 0.1394 - mean_absolute_error: 0.2513"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  61/1534 [>.............................] - ETA: 5s - loss: 0.1089 - mean_absolute_error: 0.2167"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  77/1534 [>.............................] - ETA: 4s - loss: 0.0905 - mean_absolute_error: 0.1945"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  92/1534 [>.............................] - ETA: 4s - loss: 0.0786 - mean_absolute_error: 0.1789"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 108/1534 [=>............................] - ETA: 4s - loss: 0.0693 - mean_absolute_error: 0.1667"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 123/1534 [=>............................] - ETA: 4s - loss: 0.0623 - mean_absolute_error: 0.1571"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 138/1534 [=>............................] - ETA: 4s - loss: 0.0573 - mean_absolute_error: 0.1500"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 153/1534 [=>............................] - ETA: 4s - loss: 0.0529 - mean_absolute_error: 0.1439"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 169/1534 [==>...........................] - ETA: 4s - loss: 0.0491 - mean_absolute_error: 0.1382"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 184/1534 [==>...........................] - ETA: 4s - loss: 0.0462 - mean_absolute_error: 0.1342"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 200/1534 [==>...........................] - ETA: 4s - loss: 0.0434 - mean_absolute_error: 0.1300"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 215/1534 [===>..........................] - ETA: 4s - loss: 0.0411 - mean_absolute_error: 0.1264"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 230/1534 [===>..........................] - ETA: 4s - loss: 0.0393 - mean_absolute_error: 0.1235"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 246/1534 [===>..........................] - ETA: 4s - loss: 0.0376 - mean_absolute_error: 0.1211"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 261/1534 [====>.........................] - ETA: 4s - loss: 0.0362 - mean_absolute_error: 0.1193"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 277/1534 [====>.........................] - ETA: 4s - loss: 0.0347 - mean_absolute_error: 0.1171"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 293/1534 [====>.........................] - ETA: 4s - loss: 0.0334 - mean_absolute_error: 0.1151"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 308/1534 [=====>........................] - ETA: 4s - loss: 0.0324 - mean_absolute_error: 0.1135"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 323/1534 [=====>........................] - ETA: 4s - loss: 0.0315 - mean_absolute_error: 0.1120"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 338/1534 [=====>........................] - ETA: 4s - loss: 0.0306 - mean_absolute_error: 0.1106"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 354/1534 [=====>........................] - ETA: 3s - loss: 0.0297 - mean_absolute_error: 0.1092"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 369/1534 [======>.......................] - ETA: 3s - loss: 0.0289 - mean_absolute_error: 0.1079"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 385/1534 [======>.......................] - ETA: 3s - loss: 0.0282 - mean_absolute_error: 0.1067"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 400/1534 [======>.......................] - ETA: 3s - loss: 0.0276 - mean_absolute_error: 0.1057"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 416/1534 [=======>......................] - ETA: 3s - loss: 0.0268 - mean_absolute_error: 0.1043"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 432/1534 [=======>......................] - ETA: 3s - loss: 0.0262 - mean_absolute_error: 0.1031"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 447/1534 [=======>......................] - ETA: 3s - loss: 0.0256 - mean_absolute_error: 0.1021"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 462/1534 [========>.....................] - ETA: 3s - loss: 0.0251 - mean_absolute_error: 0.1012"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 477/1534 [========>.....................] - ETA: 3s - loss: 0.0246 - mean_absolute_error: 0.1003"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 492/1534 [========>.....................] - ETA: 3s - loss: 0.0242 - mean_absolute_error: 0.0995"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 508/1534 [========>.....................] - ETA: 3s - loss: 0.0237 - mean_absolute_error: 0.0987"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 523/1534 [=========>....................] - ETA: 3s - loss: 0.0233 - mean_absolute_error: 0.0979"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 539/1534 [=========>....................] - ETA: 3s - loss: 0.0228 - mean_absolute_error: 0.0970"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 555/1534 [=========>....................] - ETA: 3s - loss: 0.0225 - mean_absolute_error: 0.0963"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 571/1534 [==========>...................] - ETA: 3s - loss: 0.0221 - mean_absolute_error: 0.0956"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 587/1534 [==========>...................] - ETA: 3s - loss: 0.0218 - mean_absolute_error: 0.0950"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 603/1534 [==========>...................] - ETA: 3s - loss: 0.0214 - mean_absolute_error: 0.0944"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 618/1534 [===========>..................] - ETA: 3s - loss: 0.0211 - mean_absolute_error: 0.0938"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 633/1534 [===========>..................] - ETA: 3s - loss: 0.0208 - mean_absolute_error: 0.0932"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 648/1534 [===========>..................] - ETA: 2s - loss: 0.0205 - mean_absolute_error: 0.0927"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 663/1534 [===========>..................] - ETA: 2s - loss: 0.0203 - mean_absolute_error: 0.0923"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 679/1534 [============>.................] - ETA: 2s - loss: 0.0200 - mean_absolute_error: 0.0918"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 695/1534 [============>.................] - ETA: 2s - loss: 0.0198 - mean_absolute_error: 0.0912"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 711/1534 [============>.................] - ETA: 2s - loss: 0.0196 - mean_absolute_error: 0.0909"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 727/1534 [=============>................] - ETA: 2s - loss: 0.0194 - mean_absolute_error: 0.0907"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 742/1534 [=============>................] - ETA: 2s - loss: 0.0193 - mean_absolute_error: 0.0905"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 758/1534 [=============>................] - ETA: 2s - loss: 0.0191 - mean_absolute_error: 0.0901"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 774/1534 [==============>...............] - ETA: 2s - loss: 0.0189 - mean_absolute_error: 0.0897"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 790/1534 [==============>...............] - ETA: 2s - loss: 0.0187 - mean_absolute_error: 0.0894"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 806/1534 [==============>...............] - ETA: 2s - loss: 0.0185 - mean_absolute_error: 0.0890"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 821/1534 [===============>..............] - ETA: 2s - loss: 0.0183 - mean_absolute_error: 0.0886"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 837/1534 [===============>..............] - ETA: 2s - loss: 0.0181 - mean_absolute_error: 0.0882"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 853/1534 [===============>..............] - ETA: 2s - loss: 0.0180 - mean_absolute_error: 0.0879"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 869/1534 [===============>..............] - ETA: 2s - loss: 0.0178 - mean_absolute_error: 0.0875"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 885/1534 [================>.............] - ETA: 2s - loss: 0.0176 - mean_absolute_error: 0.0872"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 900/1534 [================>.............] - ETA: 2s - loss: 0.0175 - mean_absolute_error: 0.0869"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 915/1534 [================>.............] - ETA: 2s - loss: 0.0174 - mean_absolute_error: 0.0866"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 931/1534 [=================>............] - ETA: 2s - loss: 0.0172 - mean_absolute_error: 0.0863"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 947/1534 [=================>............] - ETA: 1s - loss: 0.0171 - mean_absolute_error: 0.0861"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 962/1534 [=================>............] - ETA: 1s - loss: 0.0170 - mean_absolute_error: 0.0859"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 978/1534 [==================>...........] - ETA: 1s - loss: 0.0169 - mean_absolute_error: 0.0858"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 994/1534 [==================>...........] - ETA: 1s - loss: 0.0168 - mean_absolute_error: 0.0856"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1010/1534 [==================>...........] - ETA: 1s - loss: 0.0166 - mean_absolute_error: 0.0854"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1026/1534 [===================>..........] - ETA: 1s - loss: 0.0165 - mean_absolute_error: 0.0851"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1042/1534 [===================>..........] - ETA: 1s - loss: 0.0164 - mean_absolute_error: 0.0848"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1058/1534 [===================>..........] - ETA: 1s - loss: 0.0163 - mean_absolute_error: 0.0846"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1074/1534 [====================>.........] - ETA: 1s - loss: 0.0162 - mean_absolute_error: 0.0843"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1089/1534 [====================>.........] - ETA: 1s - loss: 0.0160 - mean_absolute_error: 0.0840"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1105/1534 [====================>.........] - ETA: 1s - loss: 0.0159 - mean_absolute_error: 0.0839"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1121/1534 [====================>.........] - ETA: 1s - loss: 0.0158 - mean_absolute_error: 0.0836"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1136/1534 [=====================>........] - ETA: 1s - loss: 0.0157 - mean_absolute_error: 0.0834"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1151/1534 [=====================>........] - ETA: 1s - loss: 0.0156 - mean_absolute_error: 0.0832"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1166/1534 [=====================>........] - ETA: 1s - loss: 0.0156 - mean_absolute_error: 0.0831"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1182/1534 [======================>.......] - ETA: 1s - loss: 0.0155 - mean_absolute_error: 0.0830"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1197/1534 [======================>.......] - ETA: 1s - loss: 0.0154 - mean_absolute_error: 0.0827"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1212/1534 [======================>.......] - ETA: 1s - loss: 0.0153 - mean_absolute_error: 0.0825"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1227/1534 [======================>.......] - ETA: 1s - loss: 0.0152 - mean_absolute_error: 0.0823"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1243/1534 [=======================>......] - ETA: 0s - loss: 0.0151 - mean_absolute_error: 0.0821"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1259/1534 [=======================>......] - ETA: 0s - loss: 0.0150 - mean_absolute_error: 0.0819"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1275/1534 [=======================>......] - ETA: 0s - loss: 0.0149 - mean_absolute_error: 0.0816"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1291/1534 [========================>.....] - ETA: 0s - loss: 0.0148 - mean_absolute_error: 0.0814"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1307/1534 [========================>.....] - ETA: 0s - loss: 0.0147 - mean_absolute_error: 0.0812"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1323/1534 [========================>.....] - ETA: 0s - loss: 0.0146 - mean_absolute_error: 0.0810"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1339/1534 [=========================>....] - ETA: 0s - loss: 0.0146 - mean_absolute_error: 0.0809"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1354/1534 [=========================>....] - ETA: 0s - loss: 0.0145 - mean_absolute_error: 0.0807"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1369/1534 [=========================>....] - ETA: 0s - loss: 0.0144 - mean_absolute_error: 0.0806"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1385/1534 [==========================>...] - ETA: 0s - loss: 0.0144 - mean_absolute_error: 0.0805"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1400/1534 [==========================>...] - ETA: 0s - loss: 0.0143 - mean_absolute_error: 0.0804"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1416/1534 [==========================>...] - ETA: 0s - loss: 0.0143 - mean_absolute_error: 0.0803"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1431/1534 [==========================>...] - ETA: 0s - loss: 0.0142 - mean_absolute_error: 0.0801"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1446/1534 [===========================>..] - ETA: 0s - loss: 0.0141 - mean_absolute_error: 0.0800"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1461/1534 [===========================>..] - ETA: 0s - loss: 0.0141 - mean_absolute_error: 0.0799"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1476/1534 [===========================>..] - ETA: 0s - loss: 0.0140 - mean_absolute_error: 0.0798"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1491/1534 [============================>.] - ETA: 0s - loss: 0.0140 - mean_absolute_error: 0.0797"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1506/1534 [============================>.] - ETA: 0s - loss: 0.0139 - mean_absolute_error: 0.0795"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1522/1534 [============================>.] - ETA: 0s - loss: 0.0138 - mean_absolute_error: 0.0794"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1534/1534 [==============================] - 8s 4ms/step - loss: 0.0138 - mean_absolute_error: 0.0793 - val_loss: 0.0085 - val_mean_absolute_error: 0.0693\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 2/20\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "   1/1534 [..............................] - ETA: 40s - loss: 0.0088 - mean_absolute_error: 0.0709"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  16/1534 [..............................] - ETA: 5s - loss: 0.0083 - mean_absolute_error: 0.0652 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  31/1534 [..............................] - ETA: 5s - loss: 0.0075 - mean_absolute_error: 0.0634"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  47/1534 [..............................] - ETA: 5s - loss: 0.0076 - mean_absolute_error: 0.0637"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  62/1534 [>.............................] - ETA: 4s - loss: 0.0079 - mean_absolute_error: 0.0640"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  78/1534 [>.............................] - ETA: 4s - loss: 0.0080 - mean_absolute_error: 0.0635"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  94/1534 [>.............................] - ETA: 4s - loss: 0.0080 - mean_absolute_error: 0.0637"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 111/1534 [=>............................] - ETA: 4s - loss: 0.0080 - mean_absolute_error: 0.0639"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 126/1534 [=>............................] - ETA: 4s - loss: 0.0079 - mean_absolute_error: 0.0632"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 141/1534 [=>............................] - ETA: 4s - loss: 0.0082 - mean_absolute_error: 0.0642"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 157/1534 [==>...........................] - ETA: 4s - loss: 0.0081 - mean_absolute_error: 0.0644"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 173/1534 [==>...........................] - ETA: 4s - loss: 0.0081 - mean_absolute_error: 0.0645"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 189/1534 [==>...........................] - ETA: 4s - loss: 0.0081 - mean_absolute_error: 0.0644"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 205/1534 [===>..........................] - ETA: 4s - loss: 0.0080 - mean_absolute_error: 0.0646"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 221/1534 [===>..........................] - ETA: 4s - loss: 0.0080 - mean_absolute_error: 0.0644"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 237/1534 [===>..........................] - ETA: 4s - loss: 0.0081 - mean_absolute_error: 0.0646"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 252/1534 [===>..........................] - ETA: 4s - loss: 0.0081 - mean_absolute_error: 0.0647"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 268/1534 [====>.........................] - ETA: 4s - loss: 0.0081 - mean_absolute_error: 0.0649"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 284/1534 [====>.........................] - ETA: 4s - loss: 0.0081 - mean_absolute_error: 0.0652"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 299/1534 [====>.........................] - ETA: 4s - loss: 0.0080 - mean_absolute_error: 0.0650"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 315/1534 [=====>........................] - ETA: 4s - loss: 0.0080 - mean_absolute_error: 0.0649"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 331/1534 [=====>........................] - ETA: 3s - loss: 0.0081 - mean_absolute_error: 0.0653"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 347/1534 [=====>........................] - ETA: 3s - loss: 0.0081 - mean_absolute_error: 0.0653"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 363/1534 [======>.......................] - ETA: 3s - loss: 0.0082 - mean_absolute_error: 0.0657"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 378/1534 [======>.......................] - ETA: 3s - loss: 0.0082 - mean_absolute_error: 0.0657"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 394/1534 [======>.......................] - ETA: 3s - loss: 0.0082 - mean_absolute_error: 0.0657"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 410/1534 [=======>......................] - ETA: 3s - loss: 0.0082 - mean_absolute_error: 0.0656"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 426/1534 [=======>......................] - ETA: 3s - loss: 0.0081 - mean_absolute_error: 0.0654"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 441/1534 [=======>......................] - ETA: 3s - loss: 0.0081 - mean_absolute_error: 0.0654"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 456/1534 [=======>......................] - ETA: 3s - loss: 0.0081 - mean_absolute_error: 0.0655"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 472/1534 [========>.....................] - ETA: 3s - loss: 0.0081 - mean_absolute_error: 0.0654"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 487/1534 [========>.....................] - ETA: 3s - loss: 0.0081 - mean_absolute_error: 0.0654"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 503/1534 [========>.....................] - ETA: 3s - loss: 0.0081 - mean_absolute_error: 0.0652"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 518/1534 [=========>....................] - ETA: 3s - loss: 0.0080 - mean_absolute_error: 0.0652"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 533/1534 [=========>....................] - ETA: 3s - loss: 0.0080 - mean_absolute_error: 0.0650"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 549/1534 [=========>....................] - ETA: 3s - loss: 0.0080 - mean_absolute_error: 0.0650"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 565/1534 [==========>...................] - ETA: 3s - loss: 0.0081 - mean_absolute_error: 0.0650"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 581/1534 [==========>...................] - ETA: 3s - loss: 0.0081 - mean_absolute_error: 0.0651"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 597/1534 [==========>...................] - ETA: 3s - loss: 0.0080 - mean_absolute_error: 0.0650"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 612/1534 [==========>...................] - ETA: 3s - loss: 0.0080 - mean_absolute_error: 0.0648"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 627/1534 [===========>..................] - ETA: 3s - loss: 0.0079 - mean_absolute_error: 0.0647"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 642/1534 [===========>..................] - ETA: 2s - loss: 0.0080 - mean_absolute_error: 0.0649"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 657/1534 [===========>..................] - ETA: 2s - loss: 0.0080 - mean_absolute_error: 0.0649"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 672/1534 [============>.................] - ETA: 2s - loss: 0.0080 - mean_absolute_error: 0.0649"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 687/1534 [============>.................] - ETA: 2s - loss: 0.0080 - mean_absolute_error: 0.0649"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 702/1534 [============>.................] - ETA: 2s - loss: 0.0079 - mean_absolute_error: 0.0648"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 717/1534 [=============>................] - ETA: 2s - loss: 0.0080 - mean_absolute_error: 0.0647"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 732/1534 [=============>................] - ETA: 2s - loss: 0.0080 - mean_absolute_error: 0.0648"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 747/1534 [=============>................] - ETA: 2s - loss: 0.0080 - mean_absolute_error: 0.0649"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 763/1534 [=============>................] - ETA: 2s - loss: 0.0081 - mean_absolute_error: 0.0651"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 778/1534 [==============>...............] - ETA: 2s - loss: 0.0081 - mean_absolute_error: 0.0651"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 793/1534 [==============>...............] - ETA: 2s - loss: 0.0081 - mean_absolute_error: 0.0652"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 808/1534 [==============>...............] - ETA: 2s - loss: 0.0081 - mean_absolute_error: 0.0651"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 823/1534 [===============>..............] - ETA: 2s - loss: 0.0081 - mean_absolute_error: 0.0651"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 838/1534 [===============>..............] - ETA: 2s - loss: 0.0081 - mean_absolute_error: 0.0651"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 854/1534 [===============>..............] - ETA: 2s - loss: 0.0081 - mean_absolute_error: 0.0650"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 870/1534 [================>.............] - ETA: 2s - loss: 0.0081 - mean_absolute_error: 0.0651"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 885/1534 [================>.............] - ETA: 2s - loss: 0.0081 - mean_absolute_error: 0.0651"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 900/1534 [================>.............] - ETA: 2s - loss: 0.0081 - mean_absolute_error: 0.0651"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 916/1534 [================>.............] - ETA: 2s - loss: 0.0081 - mean_absolute_error: 0.0652"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 931/1534 [=================>............] - ETA: 2s - loss: 0.0081 - mean_absolute_error: 0.0651"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 946/1534 [=================>............] - ETA: 1s - loss: 0.0081 - mean_absolute_error: 0.0651"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 961/1534 [=================>............] - ETA: 1s - loss: 0.0081 - mean_absolute_error: 0.0651"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 976/1534 [==================>...........] - ETA: 1s - loss: 0.0081 - mean_absolute_error: 0.0651"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 991/1534 [==================>...........] - ETA: 1s - loss: 0.0081 - mean_absolute_error: 0.0652"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1006/1534 [==================>...........] - ETA: 1s - loss: 0.0081 - mean_absolute_error: 0.0652"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1021/1534 [==================>...........] - ETA: 1s - loss: 0.0081 - mean_absolute_error: 0.0651"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1037/1534 [===================>..........] - ETA: 1s - loss: 0.0081 - mean_absolute_error: 0.0651"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1053/1534 [===================>..........] - ETA: 1s - loss: 0.0081 - mean_absolute_error: 0.0650"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1069/1534 [===================>..........] - ETA: 1s - loss: 0.0081 - mean_absolute_error: 0.0651"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1085/1534 [====================>.........] - ETA: 1s - loss: 0.0081 - mean_absolute_error: 0.0649"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1101/1534 [====================>.........] - ETA: 1s - loss: 0.0080 - mean_absolute_error: 0.0649"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1117/1534 [====================>.........] - ETA: 1s - loss: 0.0080 - mean_absolute_error: 0.0649"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1133/1534 [=====================>........] - ETA: 1s - loss: 0.0080 - mean_absolute_error: 0.0648"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1148/1534 [=====================>........] - ETA: 1s - loss: 0.0080 - mean_absolute_error: 0.0649"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1163/1534 [=====================>........] - ETA: 1s - loss: 0.0081 - mean_absolute_error: 0.0650"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1178/1534 [======================>.......] - ETA: 1s - loss: 0.0081 - mean_absolute_error: 0.0650"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1193/1534 [======================>.......] - ETA: 1s - loss: 0.0081 - mean_absolute_error: 0.0650"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1208/1534 [======================>.......] - ETA: 1s - loss: 0.0080 - mean_absolute_error: 0.0650"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1223/1534 [======================>.......] - ETA: 1s - loss: 0.0080 - mean_absolute_error: 0.0649"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1238/1534 [=======================>......] - ETA: 0s - loss: 0.0080 - mean_absolute_error: 0.0649"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1253/1534 [=======================>......] - ETA: 0s - loss: 0.0080 - mean_absolute_error: 0.0649"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1269/1534 [=======================>......] - ETA: 0s - loss: 0.0080 - mean_absolute_error: 0.0648"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1284/1534 [========================>.....] - ETA: 0s - loss: 0.0080 - mean_absolute_error: 0.0647"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1300/1534 [========================>.....] - ETA: 0s - loss: 0.0080 - mean_absolute_error: 0.0648"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1316/1534 [========================>.....] - ETA: 0s - loss: 0.0080 - mean_absolute_error: 0.0647"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1332/1534 [=========================>....] - ETA: 0s - loss: 0.0079 - mean_absolute_error: 0.0646"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1348/1534 [=========================>....] - ETA: 0s - loss: 0.0080 - mean_absolute_error: 0.0647"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1363/1534 [=========================>....] - ETA: 0s - loss: 0.0079 - mean_absolute_error: 0.0646"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1378/1534 [=========================>....] - ETA: 0s - loss: 0.0079 - mean_absolute_error: 0.0646"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1393/1534 [==========================>...] - ETA: 0s - loss: 0.0079 - mean_absolute_error: 0.0646"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1409/1534 [==========================>...] - ETA: 0s - loss: 0.0079 - mean_absolute_error: 0.0646"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1424/1534 [==========================>...] - ETA: 0s - loss: 0.0079 - mean_absolute_error: 0.0646"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1439/1534 [===========================>..] - ETA: 0s - loss: 0.0079 - mean_absolute_error: 0.0647"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1454/1534 [===========================>..] - ETA: 0s - loss: 0.0079 - mean_absolute_error: 0.0647"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1470/1534 [===========================>..] - ETA: 0s - loss: 0.0079 - mean_absolute_error: 0.0646"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1485/1534 [============================>.] - ETA: 0s - loss: 0.0079 - mean_absolute_error: 0.0646"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1501/1534 [============================>.] - ETA: 0s - loss: 0.0079 - mean_absolute_error: 0.0646"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1517/1534 [============================>.] - ETA: 0s - loss: 0.0079 - mean_absolute_error: 0.0646"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1533/1534 [============================>.] - ETA: 0s - loss: 0.0079 - mean_absolute_error: 0.0645"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1534/1534 [==============================] - 6s 4ms/step - loss: 0.0079 - mean_absolute_error: 0.0645 - val_loss: 0.0075 - val_mean_absolute_error: 0.0638\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 3/20\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "   1/1534 [..............................] - ETA: 40s - loss: 0.0061 - mean_absolute_error: 0.0632"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  16/1534 [..............................] - ETA: 5s - loss: 0.0077 - mean_absolute_error: 0.0668 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  31/1534 [..............................] - ETA: 5s - loss: 0.0069 - mean_absolute_error: 0.0624"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  47/1534 [..............................] - ETA: 5s - loss: 0.0077 - mean_absolute_error: 0.0635"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  63/1534 [>.............................] - ETA: 4s - loss: 0.0078 - mean_absolute_error: 0.0641"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  78/1534 [>.............................] - ETA: 4s - loss: 0.0077 - mean_absolute_error: 0.0638"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  94/1534 [>.............................] - ETA: 4s - loss: 0.0078 - mean_absolute_error: 0.0632"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 111/1534 [=>............................] - ETA: 4s - loss: 0.0076 - mean_absolute_error: 0.0625"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 127/1534 [=>............................] - ETA: 4s - loss: 0.0076 - mean_absolute_error: 0.0625"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 143/1534 [=>............................] - ETA: 4s - loss: 0.0078 - mean_absolute_error: 0.0630"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 159/1534 [==>...........................] - ETA: 4s - loss: 0.0078 - mean_absolute_error: 0.0631"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 175/1534 [==>...........................] - ETA: 4s - loss: 0.0077 - mean_absolute_error: 0.0630"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 191/1534 [==>...........................] - ETA: 4s - loss: 0.0078 - mean_absolute_error: 0.0633"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 207/1534 [===>..........................] - ETA: 4s - loss: 0.0077 - mean_absolute_error: 0.0630"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 223/1534 [===>..........................] - ETA: 4s - loss: 0.0077 - mean_absolute_error: 0.0626"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 239/1534 [===>..........................] - ETA: 4s - loss: 0.0076 - mean_absolute_error: 0.0623"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 255/1534 [===>..........................] - ETA: 4s - loss: 0.0076 - mean_absolute_error: 0.0625"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 270/1534 [====>.........................] - ETA: 4s - loss: 0.0075 - mean_absolute_error: 0.0624"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 286/1534 [====>.........................] - ETA: 4s - loss: 0.0075 - mean_absolute_error: 0.0624"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 302/1534 [====>.........................] - ETA: 4s - loss: 0.0076 - mean_absolute_error: 0.0625"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 318/1534 [=====>........................] - ETA: 3s - loss: 0.0076 - mean_absolute_error: 0.0628"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 334/1534 [=====>........................] - ETA: 3s - loss: 0.0077 - mean_absolute_error: 0.0630"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 349/1534 [=====>........................] - ETA: 3s - loss: 0.0077 - mean_absolute_error: 0.0630"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 364/1534 [======>.......................] - ETA: 3s - loss: 0.0076 - mean_absolute_error: 0.0631"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 380/1534 [======>.......................] - ETA: 3s - loss: 0.0077 - mean_absolute_error: 0.0631"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 396/1534 [======>.......................] - ETA: 3s - loss: 0.0077 - mean_absolute_error: 0.0631"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 412/1534 [=======>......................] - ETA: 3s - loss: 0.0076 - mean_absolute_error: 0.0630"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 428/1534 [=======>......................] - ETA: 3s - loss: 0.0076 - mean_absolute_error: 0.0629"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 444/1534 [=======>......................] - ETA: 3s - loss: 0.0076 - mean_absolute_error: 0.0629"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 459/1534 [=======>......................] - ETA: 3s - loss: 0.0076 - mean_absolute_error: 0.0629"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 475/1534 [========>.....................] - ETA: 3s - loss: 0.0076 - mean_absolute_error: 0.0629"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 491/1534 [========>.....................] - ETA: 3s - loss: 0.0076 - mean_absolute_error: 0.0630"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 507/1534 [========>.....................] - ETA: 3s - loss: 0.0076 - mean_absolute_error: 0.0630"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 523/1534 [=========>....................] - ETA: 3s - loss: 0.0075 - mean_absolute_error: 0.0628"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 538/1534 [=========>....................] - ETA: 3s - loss: 0.0076 - mean_absolute_error: 0.0627"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 553/1534 [=========>....................] - ETA: 3s - loss: 0.0076 - mean_absolute_error: 0.0628"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 569/1534 [==========>...................] - ETA: 3s - loss: 0.0075 - mean_absolute_error: 0.0627"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 584/1534 [==========>...................] - ETA: 3s - loss: 0.0075 - mean_absolute_error: 0.0626"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 599/1534 [==========>...................] - ETA: 3s - loss: 0.0075 - mean_absolute_error: 0.0625"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 615/1534 [===========>..................] - ETA: 3s - loss: 0.0074 - mean_absolute_error: 0.0624"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 630/1534 [===========>..................] - ETA: 2s - loss: 0.0074 - mean_absolute_error: 0.0623"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 645/1534 [===========>..................] - ETA: 2s - loss: 0.0074 - mean_absolute_error: 0.0623"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 660/1534 [===========>..................] - ETA: 2s - loss: 0.0074 - mean_absolute_error: 0.0624"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 675/1534 [============>.................] - ETA: 2s - loss: 0.0074 - mean_absolute_error: 0.0624"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 690/1534 [============>.................] - ETA: 2s - loss: 0.0074 - mean_absolute_error: 0.0624"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 705/1534 [============>.................] - ETA: 2s - loss: 0.0075 - mean_absolute_error: 0.0624"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 721/1534 [=============>................] - ETA: 2s - loss: 0.0074 - mean_absolute_error: 0.0623"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 736/1534 [=============>................] - ETA: 2s - loss: 0.0075 - mean_absolute_error: 0.0624"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 751/1534 [=============>................] - ETA: 2s - loss: 0.0076 - mean_absolute_error: 0.0626"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 766/1534 [=============>................] - ETA: 2s - loss: 0.0076 - mean_absolute_error: 0.0626"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 781/1534 [==============>...............] - ETA: 2s - loss: 0.0076 - mean_absolute_error: 0.0627"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 796/1534 [==============>...............] - ETA: 2s - loss: 0.0076 - mean_absolute_error: 0.0628"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 811/1534 [==============>...............] - ETA: 2s - loss: 0.0076 - mean_absolute_error: 0.0628"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 826/1534 [===============>..............] - ETA: 2s - loss: 0.0076 - mean_absolute_error: 0.0628"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 841/1534 [===============>..............] - ETA: 2s - loss: 0.0076 - mean_absolute_error: 0.0627"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 856/1534 [===============>..............] - ETA: 2s - loss: 0.0076 - mean_absolute_error: 0.0627"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 871/1534 [================>.............] - ETA: 2s - loss: 0.0076 - mean_absolute_error: 0.0627"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 886/1534 [================>.............] - ETA: 2s - loss: 0.0076 - mean_absolute_error: 0.0627"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 901/1534 [================>.............] - ETA: 2s - loss: 0.0076 - mean_absolute_error: 0.0627"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 916/1534 [================>.............] - ETA: 2s - loss: 0.0076 - mean_absolute_error: 0.0627"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 931/1534 [=================>............] - ETA: 2s - loss: 0.0076 - mean_absolute_error: 0.0627"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 946/1534 [=================>............] - ETA: 1s - loss: 0.0076 - mean_absolute_error: 0.0628"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 961/1534 [=================>............] - ETA: 1s - loss: 0.0076 - mean_absolute_error: 0.0628"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 977/1534 [==================>...........] - ETA: 1s - loss: 0.0076 - mean_absolute_error: 0.0629"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 992/1534 [==================>...........] - ETA: 1s - loss: 0.0077 - mean_absolute_error: 0.0630"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1007/1534 [==================>...........] - ETA: 1s - loss: 0.0077 - mean_absolute_error: 0.0629"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1023/1534 [===================>..........] - ETA: 1s - loss: 0.0077 - mean_absolute_error: 0.0630"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1038/1534 [===================>..........] - ETA: 1s - loss: 0.0076 - mean_absolute_error: 0.0629"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1053/1534 [===================>..........] - ETA: 1s - loss: 0.0076 - mean_absolute_error: 0.0628"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1068/1534 [===================>..........] - ETA: 1s - loss: 0.0076 - mean_absolute_error: 0.0629"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1083/1534 [====================>.........] - ETA: 1s - loss: 0.0076 - mean_absolute_error: 0.0628"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1098/1534 [====================>.........] - ETA: 1s - loss: 0.0076 - mean_absolute_error: 0.0627"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1114/1534 [====================>.........] - ETA: 1s - loss: 0.0076 - mean_absolute_error: 0.0627"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1129/1534 [=====================>........] - ETA: 1s - loss: 0.0076 - mean_absolute_error: 0.0628"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1144/1534 [=====================>........] - ETA: 1s - loss: 0.0076 - mean_absolute_error: 0.0628"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1159/1534 [=====================>........] - ETA: 1s - loss: 0.0076 - mean_absolute_error: 0.0628"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1175/1534 [=====================>........] - ETA: 1s - loss: 0.0076 - mean_absolute_error: 0.0628"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1190/1534 [======================>.......] - ETA: 1s - loss: 0.0076 - mean_absolute_error: 0.0627"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1205/1534 [======================>.......] - ETA: 1s - loss: 0.0076 - mean_absolute_error: 0.0627"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1220/1534 [======================>.......] - ETA: 1s - loss: 0.0076 - mean_absolute_error: 0.0626"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1236/1534 [=======================>......] - ETA: 0s - loss: 0.0076 - mean_absolute_error: 0.0626"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1251/1534 [=======================>......] - ETA: 0s - loss: 0.0076 - mean_absolute_error: 0.0626"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1267/1534 [=======================>......] - ETA: 0s - loss: 0.0075 - mean_absolute_error: 0.0625"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1283/1534 [========================>.....] - ETA: 0s - loss: 0.0075 - mean_absolute_error: 0.0625"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1299/1534 [========================>.....] - ETA: 0s - loss: 0.0075 - mean_absolute_error: 0.0625"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1315/1534 [========================>.....] - ETA: 0s - loss: 0.0075 - mean_absolute_error: 0.0624"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1331/1534 [=========================>....] - ETA: 0s - loss: 0.0075 - mean_absolute_error: 0.0624"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1347/1534 [=========================>....] - ETA: 0s - loss: 0.0075 - mean_absolute_error: 0.0624"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1363/1534 [=========================>....] - ETA: 0s - loss: 0.0075 - mean_absolute_error: 0.0624"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1379/1534 [=========================>....] - ETA: 0s - loss: 0.0075 - mean_absolute_error: 0.0624"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1395/1534 [==========================>...] - ETA: 0s - loss: 0.0075 - mean_absolute_error: 0.0624"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1411/1534 [==========================>...] - ETA: 0s - loss: 0.0075 - mean_absolute_error: 0.0624"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1427/1534 [==========================>...] - ETA: 0s - loss: 0.0075 - mean_absolute_error: 0.0624"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1443/1534 [===========================>..] - ETA: 0s - loss: 0.0075 - mean_absolute_error: 0.0624"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1459/1534 [===========================>..] - ETA: 0s - loss: 0.0075 - mean_absolute_error: 0.0624"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1475/1534 [===========================>..] - ETA: 0s - loss: 0.0075 - mean_absolute_error: 0.0624"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1491/1534 [============================>.] - ETA: 0s - loss: 0.0075 - mean_absolute_error: 0.0624"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1507/1534 [============================>.] - ETA: 0s - loss: 0.0075 - mean_absolute_error: 0.0623"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1523/1534 [============================>.] - ETA: 0s - loss: 0.0075 - mean_absolute_error: 0.0623"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1534/1534 [==============================] - 6s 4ms/step - loss: 0.0075 - mean_absolute_error: 0.0623 - val_loss: 0.0077 - val_mean_absolute_error: 0.0618\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 4/20\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "   1/1534 [..............................] - ETA: 43s - loss: 0.0045 - mean_absolute_error: 0.0550"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  15/1534 [..............................] - ETA: 5s - loss: 0.0070 - mean_absolute_error: 0.0630 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  30/1534 [..............................] - ETA: 5s - loss: 0.0065 - mean_absolute_error: 0.0603"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  45/1534 [..............................] - ETA: 5s - loss: 0.0073 - mean_absolute_error: 0.0626"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  61/1534 [>.............................] - ETA: 5s - loss: 0.0075 - mean_absolute_error: 0.0628"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  76/1534 [>.............................] - ETA: 4s - loss: 0.0074 - mean_absolute_error: 0.0619"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  92/1534 [>.............................] - ETA: 4s - loss: 0.0074 - mean_absolute_error: 0.0617"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 109/1534 [=>............................] - ETA: 4s - loss: 0.0074 - mean_absolute_error: 0.0617"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 125/1534 [=>............................] - ETA: 4s - loss: 0.0074 - mean_absolute_error: 0.0618"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 141/1534 [=>............................] - ETA: 4s - loss: 0.0075 - mean_absolute_error: 0.0621"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 156/1534 [==>...........................] - ETA: 4s - loss: 0.0076 - mean_absolute_error: 0.0624"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 172/1534 [==>...........................] - ETA: 4s - loss: 0.0076 - mean_absolute_error: 0.0625"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 188/1534 [==>...........................] - ETA: 4s - loss: 0.0075 - mean_absolute_error: 0.0622"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 204/1534 [==>...........................] - ETA: 4s - loss: 0.0074 - mean_absolute_error: 0.0617"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 220/1534 [===>..........................] - ETA: 4s - loss: 0.0073 - mean_absolute_error: 0.0613"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 235/1534 [===>..........................] - ETA: 4s - loss: 0.0073 - mean_absolute_error: 0.0612"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 250/1534 [===>..........................] - ETA: 4s - loss: 0.0073 - mean_absolute_error: 0.0612"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 266/1534 [====>.........................] - ETA: 4s - loss: 0.0073 - mean_absolute_error: 0.0613"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 282/1534 [====>.........................] - ETA: 4s - loss: 0.0073 - mean_absolute_error: 0.0611"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 298/1534 [====>.........................] - ETA: 4s - loss: 0.0073 - mean_absolute_error: 0.0613"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 314/1534 [=====>........................] - ETA: 4s - loss: 0.0074 - mean_absolute_error: 0.0614"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 329/1534 [=====>........................] - ETA: 3s - loss: 0.0074 - mean_absolute_error: 0.0616"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 344/1534 [=====>........................] - ETA: 3s - loss: 0.0073 - mean_absolute_error: 0.0615"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 359/1534 [======>.......................] - ETA: 3s - loss: 0.0074 - mean_absolute_error: 0.0615"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 375/1534 [======>.......................] - ETA: 3s - loss: 0.0074 - mean_absolute_error: 0.0617"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 391/1534 [======>.......................] - ETA: 3s - loss: 0.0074 - mean_absolute_error: 0.0617"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 407/1534 [======>.......................] - ETA: 3s - loss: 0.0074 - mean_absolute_error: 0.0616"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 423/1534 [=======>......................] - ETA: 3s - loss: 0.0074 - mean_absolute_error: 0.0615"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 439/1534 [=======>......................] - ETA: 3s - loss: 0.0074 - mean_absolute_error: 0.0617"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 455/1534 [=======>......................] - ETA: 3s - loss: 0.0074 - mean_absolute_error: 0.0617"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 471/1534 [========>.....................] - ETA: 3s - loss: 0.0074 - mean_absolute_error: 0.0617"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 487/1534 [========>.....................] - ETA: 3s - loss: 0.0074 - mean_absolute_error: 0.0618"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 503/1534 [========>.....................] - ETA: 3s - loss: 0.0074 - mean_absolute_error: 0.0617"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 519/1534 [=========>....................] - ETA: 3s - loss: 0.0073 - mean_absolute_error: 0.0615"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 535/1534 [=========>....................] - ETA: 3s - loss: 0.0073 - mean_absolute_error: 0.0614"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 551/1534 [=========>....................] - ETA: 3s - loss: 0.0073 - mean_absolute_error: 0.0614"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 566/1534 [==========>...................] - ETA: 3s - loss: 0.0073 - mean_absolute_error: 0.0614"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 582/1534 [==========>...................] - ETA: 3s - loss: 0.0073 - mean_absolute_error: 0.0612"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 598/1534 [==========>...................] - ETA: 3s - loss: 0.0072 - mean_absolute_error: 0.0612"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 614/1534 [===========>..................] - ETA: 3s - loss: 0.0072 - mean_absolute_error: 0.0610"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 630/1534 [===========>..................] - ETA: 2s - loss: 0.0072 - mean_absolute_error: 0.0609"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 646/1534 [===========>..................] - ETA: 2s - loss: 0.0072 - mean_absolute_error: 0.0610"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 662/1534 [===========>..................] - ETA: 2s - loss: 0.0072 - mean_absolute_error: 0.0611"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 678/1534 [============>.................] - ETA: 2s - loss: 0.0072 - mean_absolute_error: 0.0610"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 694/1534 [============>.................] - ETA: 2s - loss: 0.0072 - mean_absolute_error: 0.0610"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 710/1534 [============>.................] - ETA: 2s - loss: 0.0072 - mean_absolute_error: 0.0611"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 726/1534 [=============>................] - ETA: 2s - loss: 0.0072 - mean_absolute_error: 0.0610"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 741/1534 [=============>................] - ETA: 2s - loss: 0.0073 - mean_absolute_error: 0.0611"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 757/1534 [=============>................] - ETA: 2s - loss: 0.0073 - mean_absolute_error: 0.0611"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 773/1534 [==============>...............] - ETA: 2s - loss: 0.0073 - mean_absolute_error: 0.0612"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 789/1534 [==============>...............] - ETA: 2s - loss: 0.0073 - mean_absolute_error: 0.0613"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 805/1534 [==============>...............] - ETA: 2s - loss: 0.0073 - mean_absolute_error: 0.0612"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 821/1534 [===============>..............] - ETA: 2s - loss: 0.0073 - mean_absolute_error: 0.0611"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 836/1534 [===============>..............] - ETA: 2s - loss: 0.0073 - mean_absolute_error: 0.0611"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 851/1534 [===============>..............] - ETA: 2s - loss: 0.0073 - mean_absolute_error: 0.0612"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 867/1534 [===============>..............] - ETA: 2s - loss: 0.0073 - mean_absolute_error: 0.0611"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 882/1534 [================>.............] - ETA: 2s - loss: 0.0073 - mean_absolute_error: 0.0611"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 897/1534 [================>.............] - ETA: 2s - loss: 0.0073 - mean_absolute_error: 0.0611"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 912/1534 [================>.............] - ETA: 2s - loss: 0.0073 - mean_absolute_error: 0.0611"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 927/1534 [=================>............] - ETA: 2s - loss: 0.0073 - mean_absolute_error: 0.0611"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 943/1534 [=================>............] - ETA: 1s - loss: 0.0073 - mean_absolute_error: 0.0611"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 958/1534 [=================>............] - ETA: 1s - loss: 0.0073 - mean_absolute_error: 0.0611"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 974/1534 [==================>...........] - ETA: 1s - loss: 0.0073 - mean_absolute_error: 0.0611"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 990/1534 [==================>...........] - ETA: 1s - loss: 0.0073 - mean_absolute_error: 0.0613"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1005/1534 [==================>...........] - ETA: 1s - loss: 0.0074 - mean_absolute_error: 0.0613"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1021/1534 [==================>...........] - ETA: 1s - loss: 0.0073 - mean_absolute_error: 0.0613"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1037/1534 [===================>..........] - ETA: 1s - loss: 0.0074 - mean_absolute_error: 0.0614"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1052/1534 [===================>..........] - ETA: 1s - loss: 0.0073 - mean_absolute_error: 0.0613"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1067/1534 [===================>..........] - ETA: 1s - loss: 0.0074 - mean_absolute_error: 0.0613"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1082/1534 [====================>.........] - ETA: 1s - loss: 0.0073 - mean_absolute_error: 0.0612"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1098/1534 [====================>.........] - ETA: 1s - loss: 0.0073 - mean_absolute_error: 0.0612"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1114/1534 [====================>.........] - ETA: 1s - loss: 0.0073 - mean_absolute_error: 0.0612"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1130/1534 [=====================>........] - ETA: 1s - loss: 0.0073 - mean_absolute_error: 0.0612"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1145/1534 [=====================>........] - ETA: 1s - loss: 0.0073 - mean_absolute_error: 0.0612"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1161/1534 [=====================>........] - ETA: 1s - loss: 0.0073 - mean_absolute_error: 0.0613"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1177/1534 [======================>.......] - ETA: 1s - loss: 0.0073 - mean_absolute_error: 0.0613"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1192/1534 [======================>.......] - ETA: 1s - loss: 0.0073 - mean_absolute_error: 0.0612"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1208/1534 [======================>.......] - ETA: 1s - loss: 0.0073 - mean_absolute_error: 0.0612"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1224/1534 [======================>.......] - ETA: 1s - loss: 0.0073 - mean_absolute_error: 0.0611"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1240/1534 [=======================>......] - ETA: 0s - loss: 0.0073 - mean_absolute_error: 0.0612"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1255/1534 [=======================>......] - ETA: 0s - loss: 0.0073 - mean_absolute_error: 0.0612"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1271/1534 [=======================>......] - ETA: 0s - loss: 0.0073 - mean_absolute_error: 0.0611"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1286/1534 [========================>.....] - ETA: 0s - loss: 0.0073 - mean_absolute_error: 0.0610"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1301/1534 [========================>.....] - ETA: 0s - loss: 0.0073 - mean_absolute_error: 0.0610"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1317/1534 [========================>.....] - ETA: 0s - loss: 0.0072 - mean_absolute_error: 0.0610"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1332/1534 [=========================>....] - ETA: 0s - loss: 0.0072 - mean_absolute_error: 0.0609"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1347/1534 [=========================>....] - ETA: 0s - loss: 0.0072 - mean_absolute_error: 0.0609"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1362/1534 [=========================>....] - ETA: 0s - loss: 0.0072 - mean_absolute_error: 0.0610"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1377/1534 [=========================>....] - ETA: 0s - loss: 0.0072 - mean_absolute_error: 0.0610"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1392/1534 [==========================>...] - ETA: 0s - loss: 0.0072 - mean_absolute_error: 0.0610"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1407/1534 [==========================>...] - ETA: 0s - loss: 0.0072 - mean_absolute_error: 0.0610"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1422/1534 [==========================>...] - ETA: 0s - loss: 0.0072 - mean_absolute_error: 0.0610"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1437/1534 [===========================>..] - ETA: 0s - loss: 0.0072 - mean_absolute_error: 0.0610"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1452/1534 [===========================>..] - ETA: 0s - loss: 0.0072 - mean_absolute_error: 0.0610"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1467/1534 [===========================>..] - ETA: 0s - loss: 0.0072 - mean_absolute_error: 0.0610"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1482/1534 [===========================>..] - ETA: 0s - loss: 0.0072 - mean_absolute_error: 0.0610"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1498/1534 [============================>.] - ETA: 0s - loss: 0.0072 - mean_absolute_error: 0.0610"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1513/1534 [============================>.] - ETA: 0s - loss: 0.0072 - mean_absolute_error: 0.0610"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1528/1534 [============================>.] - ETA: 0s - loss: 0.0072 - mean_absolute_error: 0.0610"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1534/1534 [==============================] - 6s 4ms/step - loss: 0.0072 - mean_absolute_error: 0.0610 - val_loss: 0.0072 - val_mean_absolute_error: 0.0620\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 5/20\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "   1/1534 [..............................] - ETA: 41s - loss: 0.0043 - mean_absolute_error: 0.0524"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  15/1534 [..............................] - ETA: 5s - loss: 0.0061 - mean_absolute_error: 0.0567 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  30/1534 [..............................] - ETA: 5s - loss: 0.0062 - mean_absolute_error: 0.0570"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  45/1534 [..............................] - ETA: 5s - loss: 0.0067 - mean_absolute_error: 0.0588"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  60/1534 [>.............................] - ETA: 5s - loss: 0.0068 - mean_absolute_error: 0.0587"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  75/1534 [>.............................] - ETA: 5s - loss: 0.0070 - mean_absolute_error: 0.0587"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  90/1534 [>.............................] - ETA: 4s - loss: 0.0070 - mean_absolute_error: 0.0588"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 106/1534 [=>............................] - ETA: 4s - loss: 0.0069 - mean_absolute_error: 0.0586"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 122/1534 [=>............................] - ETA: 4s - loss: 0.0069 - mean_absolute_error: 0.0584"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 138/1534 [=>............................] - ETA: 4s - loss: 0.0069 - mean_absolute_error: 0.0587"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 153/1534 [=>............................] - ETA: 4s - loss: 0.0071 - mean_absolute_error: 0.0593"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 168/1534 [==>...........................] - ETA: 4s - loss: 0.0072 - mean_absolute_error: 0.0596"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 183/1534 [==>...........................] - ETA: 4s - loss: 0.0072 - mean_absolute_error: 0.0596"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 198/1534 [==>...........................] - ETA: 4s - loss: 0.0071 - mean_absolute_error: 0.0593"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 213/1534 [===>..........................] - ETA: 4s - loss: 0.0070 - mean_absolute_error: 0.0588"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 228/1534 [===>..........................] - ETA: 4s - loss: 0.0068 - mean_absolute_error: 0.0583"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 243/1534 [===>..........................] - ETA: 4s - loss: 0.0069 - mean_absolute_error: 0.0584"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 258/1534 [====>.........................] - ETA: 4s - loss: 0.0069 - mean_absolute_error: 0.0588"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 273/1534 [====>.........................] - ETA: 4s - loss: 0.0069 - mean_absolute_error: 0.0588"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 288/1534 [====>.........................] - ETA: 4s - loss: 0.0069 - mean_absolute_error: 0.0589"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 303/1534 [====>.........................] - ETA: 4s - loss: 0.0069 - mean_absolute_error: 0.0590"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 318/1534 [=====>........................] - ETA: 4s - loss: 0.0070 - mean_absolute_error: 0.0592"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 333/1534 [=====>........................] - ETA: 4s - loss: 0.0070 - mean_absolute_error: 0.0593"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 348/1534 [=====>........................] - ETA: 4s - loss: 0.0070 - mean_absolute_error: 0.0594"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 363/1534 [======>.......................] - ETA: 3s - loss: 0.0070 - mean_absolute_error: 0.0594"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 378/1534 [======>.......................] - ETA: 3s - loss: 0.0070 - mean_absolute_error: 0.0596"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 393/1534 [======>.......................] - ETA: 3s - loss: 0.0070 - mean_absolute_error: 0.0596"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 409/1534 [======>.......................] - ETA: 3s - loss: 0.0070 - mean_absolute_error: 0.0596"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 425/1534 [=======>......................] - ETA: 3s - loss: 0.0070 - mean_absolute_error: 0.0595"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 440/1534 [=======>......................] - ETA: 3s - loss: 0.0070 - mean_absolute_error: 0.0595"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 455/1534 [=======>......................] - ETA: 3s - loss: 0.0070 - mean_absolute_error: 0.0596"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 471/1534 [========>.....................] - ETA: 3s - loss: 0.0070 - mean_absolute_error: 0.0597"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 487/1534 [========>.....................] - ETA: 3s - loss: 0.0070 - mean_absolute_error: 0.0597"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 502/1534 [========>.....................] - ETA: 3s - loss: 0.0070 - mean_absolute_error: 0.0596"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 518/1534 [=========>....................] - ETA: 3s - loss: 0.0070 - mean_absolute_error: 0.0596"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 534/1534 [=========>....................] - ETA: 3s - loss: 0.0070 - mean_absolute_error: 0.0596"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 550/1534 [=========>....................] - ETA: 3s - loss: 0.0070 - mean_absolute_error: 0.0595"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 566/1534 [==========>...................] - ETA: 3s - loss: 0.0069 - mean_absolute_error: 0.0595"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 581/1534 [==========>...................] - ETA: 3s - loss: 0.0070 - mean_absolute_error: 0.0595"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 597/1534 [==========>...................] - ETA: 3s - loss: 0.0069 - mean_absolute_error: 0.0594"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 613/1534 [==========>...................] - ETA: 3s - loss: 0.0069 - mean_absolute_error: 0.0593"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 629/1534 [===========>..................] - ETA: 3s - loss: 0.0069 - mean_absolute_error: 0.0592"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 645/1534 [===========>..................] - ETA: 2s - loss: 0.0069 - mean_absolute_error: 0.0593"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 661/1534 [===========>..................] - ETA: 2s - loss: 0.0069 - mean_absolute_error: 0.0593"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 676/1534 [============>.................] - ETA: 2s - loss: 0.0069 - mean_absolute_error: 0.0593"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 692/1534 [============>.................] - ETA: 2s - loss: 0.0069 - mean_absolute_error: 0.0592"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 707/1534 [============>.................] - ETA: 2s - loss: 0.0069 - mean_absolute_error: 0.0593"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 723/1534 [=============>................] - ETA: 2s - loss: 0.0069 - mean_absolute_error: 0.0594"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 739/1534 [=============>................] - ETA: 2s - loss: 0.0070 - mean_absolute_error: 0.0594"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 755/1534 [=============>................] - ETA: 2s - loss: 0.0070 - mean_absolute_error: 0.0596"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 771/1534 [==============>...............] - ETA: 2s - loss: 0.0070 - mean_absolute_error: 0.0597"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 786/1534 [==============>...............] - ETA: 2s - loss: 0.0071 - mean_absolute_error: 0.0598"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 801/1534 [==============>...............] - ETA: 2s - loss: 0.0070 - mean_absolute_error: 0.0597"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 817/1534 [==============>...............] - ETA: 2s - loss: 0.0070 - mean_absolute_error: 0.0597"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 833/1534 [===============>..............] - ETA: 2s - loss: 0.0070 - mean_absolute_error: 0.0598"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 849/1534 [===============>..............] - ETA: 2s - loss: 0.0070 - mean_absolute_error: 0.0597"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 864/1534 [===============>..............] - ETA: 2s - loss: 0.0070 - mean_absolute_error: 0.0598"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 879/1534 [================>.............] - ETA: 2s - loss: 0.0071 - mean_absolute_error: 0.0598"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 894/1534 [================>.............] - ETA: 2s - loss: 0.0071 - mean_absolute_error: 0.0598"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 909/1534 [================>.............] - ETA: 2s - loss: 0.0071 - mean_absolute_error: 0.0599"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 924/1534 [=================>............] - ETA: 2s - loss: 0.0071 - mean_absolute_error: 0.0599"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 939/1534 [=================>............] - ETA: 1s - loss: 0.0071 - mean_absolute_error: 0.0599"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 955/1534 [=================>............] - ETA: 1s - loss: 0.0071 - mean_absolute_error: 0.0599"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 971/1534 [=================>............] - ETA: 1s - loss: 0.0071 - mean_absolute_error: 0.0599"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 987/1534 [==================>...........] - ETA: 1s - loss: 0.0071 - mean_absolute_error: 0.0600"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1003/1534 [==================>...........] - ETA: 1s - loss: 0.0071 - mean_absolute_error: 0.0601"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1019/1534 [==================>...........] - ETA: 1s - loss: 0.0072 - mean_absolute_error: 0.0601"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1035/1534 [===================>..........] - ETA: 1s - loss: 0.0071 - mean_absolute_error: 0.0600"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1050/1534 [===================>..........] - ETA: 1s - loss: 0.0071 - mean_absolute_error: 0.0600"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1065/1534 [===================>..........] - ETA: 1s - loss: 0.0071 - mean_absolute_error: 0.0601"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1081/1534 [====================>.........] - ETA: 1s - loss: 0.0071 - mean_absolute_error: 0.0600"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1096/1534 [====================>.........] - ETA: 1s - loss: 0.0071 - mean_absolute_error: 0.0600"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1111/1534 [====================>.........] - ETA: 1s - loss: 0.0071 - mean_absolute_error: 0.0600"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1126/1534 [=====================>........] - ETA: 1s - loss: 0.0071 - mean_absolute_error: 0.0601"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1141/1534 [=====================>........] - ETA: 1s - loss: 0.0071 - mean_absolute_error: 0.0602"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1156/1534 [=====================>........] - ETA: 1s - loss: 0.0071 - mean_absolute_error: 0.0602"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1171/1534 [=====================>........] - ETA: 1s - loss: 0.0071 - mean_absolute_error: 0.0603"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1186/1534 [======================>.......] - ETA: 1s - loss: 0.0072 - mean_absolute_error: 0.0603"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1201/1534 [======================>.......] - ETA: 1s - loss: 0.0071 - mean_absolute_error: 0.0602"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1216/1534 [======================>.......] - ETA: 1s - loss: 0.0071 - mean_absolute_error: 0.0602"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1231/1534 [=======================>......] - ETA: 1s - loss: 0.0071 - mean_absolute_error: 0.0602"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1246/1534 [=======================>......] - ETA: 0s - loss: 0.0071 - mean_absolute_error: 0.0602"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1261/1534 [=======================>......] - ETA: 0s - loss: 0.0071 - mean_absolute_error: 0.0602"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1276/1534 [=======================>......] - ETA: 0s - loss: 0.0071 - mean_absolute_error: 0.0601"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1291/1534 [========================>.....] - ETA: 0s - loss: 0.0071 - mean_absolute_error: 0.0600"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1307/1534 [========================>.....] - ETA: 0s - loss: 0.0071 - mean_absolute_error: 0.0600"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1322/1534 [========================>.....] - ETA: 0s - loss: 0.0071 - mean_absolute_error: 0.0600"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1337/1534 [=========================>....] - ETA: 0s - loss: 0.0070 - mean_absolute_error: 0.0599"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1352/1534 [=========================>....] - ETA: 0s - loss: 0.0071 - mean_absolute_error: 0.0600"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1367/1534 [=========================>....] - ETA: 0s - loss: 0.0071 - mean_absolute_error: 0.0600"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1382/1534 [==========================>...] - ETA: 0s - loss: 0.0070 - mean_absolute_error: 0.0599"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1397/1534 [==========================>...] - ETA: 0s - loss: 0.0070 - mean_absolute_error: 0.0599"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1412/1534 [==========================>...] - ETA: 0s - loss: 0.0071 - mean_absolute_error: 0.0600"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1427/1534 [==========================>...] - ETA: 0s - loss: 0.0071 - mean_absolute_error: 0.0600"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1442/1534 [===========================>..] - ETA: 0s - loss: 0.0071 - mean_absolute_error: 0.0600"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1457/1534 [===========================>..] - ETA: 0s - loss: 0.0071 - mean_absolute_error: 0.0600"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1473/1534 [===========================>..] - ETA: 0s - loss: 0.0070 - mean_absolute_error: 0.0600"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1488/1534 [============================>.] - ETA: 0s - loss: 0.0070 - mean_absolute_error: 0.0600"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1503/1534 [============================>.] - ETA: 0s - loss: 0.0070 - mean_absolute_error: 0.0599"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1519/1534 [============================>.] - ETA: 0s - loss: 0.0070 - mean_absolute_error: 0.0599"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1534/1534 [==============================] - 6s 4ms/step - loss: 0.0070 - mean_absolute_error: 0.0599 - val_loss: 0.0070 - val_mean_absolute_error: 0.0600\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 6/20\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "   1/1534 [..............................] - ETA: 44s - loss: 0.0054 - mean_absolute_error: 0.0581"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  15/1534 [..............................] - ETA: 5s - loss: 0.0069 - mean_absolute_error: 0.0600 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  30/1534 [..............................] - ETA: 5s - loss: 0.0065 - mean_absolute_error: 0.0590"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  45/1534 [..............................] - ETA: 5s - loss: 0.0069 - mean_absolute_error: 0.0588"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  61/1534 [>.............................] - ETA: 5s - loss: 0.0069 - mean_absolute_error: 0.0588"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  77/1534 [>.............................] - ETA: 4s - loss: 0.0072 - mean_absolute_error: 0.0589"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  93/1534 [>.............................] - ETA: 4s - loss: 0.0071 - mean_absolute_error: 0.0593"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 110/1534 [=>............................] - ETA: 4s - loss: 0.0070 - mean_absolute_error: 0.0590"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 126/1534 [=>............................] - ETA: 4s - loss: 0.0070 - mean_absolute_error: 0.0588"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 142/1534 [=>............................] - ETA: 4s - loss: 0.0072 - mean_absolute_error: 0.0595"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 157/1534 [==>...........................] - ETA: 4s - loss: 0.0072 - mean_absolute_error: 0.0598"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 173/1534 [==>...........................] - ETA: 4s - loss: 0.0071 - mean_absolute_error: 0.0598"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 189/1534 [==>...........................] - ETA: 4s - loss: 0.0071 - mean_absolute_error: 0.0595"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 205/1534 [===>..........................] - ETA: 4s - loss: 0.0070 - mean_absolute_error: 0.0592"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 220/1534 [===>..........................] - ETA: 4s - loss: 0.0069 - mean_absolute_error: 0.0587"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 236/1534 [===>..........................] - ETA: 4s - loss: 0.0069 - mean_absolute_error: 0.0588"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 252/1534 [===>..........................] - ETA: 4s - loss: 0.0070 - mean_absolute_error: 0.0592"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 267/1534 [====>.........................] - ETA: 4s - loss: 0.0071 - mean_absolute_error: 0.0597"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 283/1534 [====>.........................] - ETA: 4s - loss: 0.0071 - mean_absolute_error: 0.0597"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 299/1534 [====>.........................] - ETA: 4s - loss: 0.0070 - mean_absolute_error: 0.0595"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 315/1534 [=====>........................] - ETA: 4s - loss: 0.0071 - mean_absolute_error: 0.0596"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 330/1534 [=====>........................] - ETA: 3s - loss: 0.0071 - mean_absolute_error: 0.0598"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 346/1534 [=====>........................] - ETA: 3s - loss: 0.0071 - mean_absolute_error: 0.0597"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 362/1534 [======>.......................] - ETA: 3s - loss: 0.0070 - mean_absolute_error: 0.0596"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 378/1534 [======>.......................] - ETA: 3s - loss: 0.0071 - mean_absolute_error: 0.0597"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 394/1534 [======>.......................] - ETA: 3s - loss: 0.0071 - mean_absolute_error: 0.0597"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 410/1534 [=======>......................] - ETA: 3s - loss: 0.0071 - mean_absolute_error: 0.0597"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 426/1534 [=======>......................] - ETA: 3s - loss: 0.0070 - mean_absolute_error: 0.0597"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 442/1534 [=======>......................] - ETA: 3s - loss: 0.0071 - mean_absolute_error: 0.0598"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 458/1534 [=======>......................] - ETA: 3s - loss: 0.0071 - mean_absolute_error: 0.0598"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 474/1534 [========>.....................] - ETA: 3s - loss: 0.0071 - mean_absolute_error: 0.0599"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 489/1534 [========>.....................] - ETA: 3s - loss: 0.0071 - mean_absolute_error: 0.0601"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 504/1534 [========>.....................] - ETA: 3s - loss: 0.0071 - mean_absolute_error: 0.0602"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 519/1534 [=========>....................] - ETA: 3s - loss: 0.0071 - mean_absolute_error: 0.0601"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 534/1534 [=========>....................] - ETA: 3s - loss: 0.0071 - mean_absolute_error: 0.0601"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 549/1534 [=========>....................] - ETA: 3s - loss: 0.0071 - mean_absolute_error: 0.0601"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 564/1534 [==========>...................] - ETA: 3s - loss: 0.0071 - mean_absolute_error: 0.0601"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 579/1534 [==========>...................] - ETA: 3s - loss: 0.0071 - mean_absolute_error: 0.0600"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 594/1534 [==========>...................] - ETA: 3s - loss: 0.0070 - mean_absolute_error: 0.0600"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 609/1534 [==========>...................] - ETA: 3s - loss: 0.0070 - mean_absolute_error: 0.0600"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 625/1534 [===========>..................] - ETA: 3s - loss: 0.0070 - mean_absolute_error: 0.0598"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 641/1534 [===========>..................] - ETA: 2s - loss: 0.0070 - mean_absolute_error: 0.0600"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 657/1534 [===========>..................] - ETA: 2s - loss: 0.0070 - mean_absolute_error: 0.0599"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 673/1534 [============>.................] - ETA: 2s - loss: 0.0070 - mean_absolute_error: 0.0598"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 689/1534 [============>.................] - ETA: 2s - loss: 0.0070 - mean_absolute_error: 0.0598"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 704/1534 [============>.................] - ETA: 2s - loss: 0.0070 - mean_absolute_error: 0.0598"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 719/1534 [=============>................] - ETA: 2s - loss: 0.0070 - mean_absolute_error: 0.0597"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 734/1534 [=============>................] - ETA: 2s - loss: 0.0070 - mean_absolute_error: 0.0598"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 750/1534 [=============>................] - ETA: 2s - loss: 0.0070 - mean_absolute_error: 0.0599"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 765/1534 [=============>................] - ETA: 2s - loss: 0.0070 - mean_absolute_error: 0.0600"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 780/1534 [==============>...............] - ETA: 2s - loss: 0.0071 - mean_absolute_error: 0.0600"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 796/1534 [==============>...............] - ETA: 2s - loss: 0.0071 - mean_absolute_error: 0.0601"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 811/1534 [==============>...............] - ETA: 2s - loss: 0.0071 - mean_absolute_error: 0.0600"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 827/1534 [===============>..............] - ETA: 2s - loss: 0.0071 - mean_absolute_error: 0.0600"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 843/1534 [===============>..............] - ETA: 2s - loss: 0.0071 - mean_absolute_error: 0.0600"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 858/1534 [===============>..............] - ETA: 2s - loss: 0.0071 - mean_absolute_error: 0.0600"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 874/1534 [================>.............] - ETA: 2s - loss: 0.0071 - mean_absolute_error: 0.0600"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 890/1534 [================>.............] - ETA: 2s - loss: 0.0071 - mean_absolute_error: 0.0600"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 906/1534 [================>.............] - ETA: 2s - loss: 0.0071 - mean_absolute_error: 0.0601"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 922/1534 [=================>............] - ETA: 2s - loss: 0.0071 - mean_absolute_error: 0.0602"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 938/1534 [=================>............] - ETA: 1s - loss: 0.0071 - mean_absolute_error: 0.0601"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 954/1534 [=================>............] - ETA: 1s - loss: 0.0071 - mean_absolute_error: 0.0601"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 970/1534 [=================>............] - ETA: 1s - loss: 0.0071 - mean_absolute_error: 0.0601"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 985/1534 [==================>...........] - ETA: 1s - loss: 0.0072 - mean_absolute_error: 0.0603"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1000/1534 [==================>...........] - ETA: 1s - loss: 0.0071 - mean_absolute_error: 0.0603"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1016/1534 [==================>...........] - ETA: 1s - loss: 0.0072 - mean_absolute_error: 0.0603"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1032/1534 [===================>..........] - ETA: 1s - loss: 0.0072 - mean_absolute_error: 0.0603"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1048/1534 [===================>..........] - ETA: 1s - loss: 0.0071 - mean_absolute_error: 0.0603"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1063/1534 [===================>..........] - ETA: 1s - loss: 0.0071 - mean_absolute_error: 0.0602"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1079/1534 [====================>.........] - ETA: 1s - loss: 0.0071 - mean_absolute_error: 0.0602"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1095/1534 [====================>.........] - ETA: 1s - loss: 0.0071 - mean_absolute_error: 0.0602"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1110/1534 [====================>.........] - ETA: 1s - loss: 0.0071 - mean_absolute_error: 0.0601"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1125/1534 [=====================>........] - ETA: 1s - loss: 0.0071 - mean_absolute_error: 0.0602"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1140/1534 [=====================>........] - ETA: 1s - loss: 0.0071 - mean_absolute_error: 0.0602"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1156/1534 [=====================>........] - ETA: 1s - loss: 0.0071 - mean_absolute_error: 0.0603"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1171/1534 [=====================>........] - ETA: 1s - loss: 0.0071 - mean_absolute_error: 0.0602"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1186/1534 [======================>.......] - ETA: 1s - loss: 0.0071 - mean_absolute_error: 0.0602"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1202/1534 [======================>.......] - ETA: 1s - loss: 0.0071 - mean_absolute_error: 0.0602"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1218/1534 [======================>.......] - ETA: 1s - loss: 0.0071 - mean_absolute_error: 0.0601"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1234/1534 [=======================>......] - ETA: 0s - loss: 0.0071 - mean_absolute_error: 0.0602"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1250/1534 [=======================>......] - ETA: 0s - loss: 0.0071 - mean_absolute_error: 0.0601"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1266/1534 [=======================>......] - ETA: 0s - loss: 0.0071 - mean_absolute_error: 0.0601"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1282/1534 [========================>.....] - ETA: 0s - loss: 0.0071 - mean_absolute_error: 0.0600"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1298/1534 [========================>.....] - ETA: 0s - loss: 0.0071 - mean_absolute_error: 0.0600"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1314/1534 [========================>.....] - ETA: 0s - loss: 0.0070 - mean_absolute_error: 0.0599"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1329/1534 [========================>.....] - ETA: 0s - loss: 0.0070 - mean_absolute_error: 0.0599"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1345/1534 [=========================>....] - ETA: 0s - loss: 0.0070 - mean_absolute_error: 0.0598"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1361/1534 [=========================>....] - ETA: 0s - loss: 0.0070 - mean_absolute_error: 0.0599"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1376/1534 [=========================>....] - ETA: 0s - loss: 0.0070 - mean_absolute_error: 0.0598"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1392/1534 [==========================>...] - ETA: 0s - loss: 0.0070 - mean_absolute_error: 0.0599"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1407/1534 [==========================>...] - ETA: 0s - loss: 0.0070 - mean_absolute_error: 0.0598"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1423/1534 [==========================>...] - ETA: 0s - loss: 0.0070 - mean_absolute_error: 0.0599"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1438/1534 [===========================>..] - ETA: 0s - loss: 0.0070 - mean_absolute_error: 0.0598"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1454/1534 [===========================>..] - ETA: 0s - loss: 0.0070 - mean_absolute_error: 0.0598"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1470/1534 [===========================>..] - ETA: 0s - loss: 0.0070 - mean_absolute_error: 0.0598"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1486/1534 [============================>.] - ETA: 0s - loss: 0.0070 - mean_absolute_error: 0.0597"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1502/1534 [============================>.] - ETA: 0s - loss: 0.0070 - mean_absolute_error: 0.0597"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1518/1534 [============================>.] - ETA: 0s - loss: 0.0070 - mean_absolute_error: 0.0597"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1534/1534 [==============================] - ETA: 0s - loss: 0.0070 - mean_absolute_error: 0.0597"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1534/1534 [==============================] - 6s 4ms/step - loss: 0.0070 - mean_absolute_error: 0.0597 - val_loss: 0.0067 - val_mean_absolute_error: 0.0583\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 7/20\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "   1/1534 [..............................] - ETA: 43s - loss: 0.0067 - mean_absolute_error: 0.0579"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  15/1534 [..............................] - ETA: 5s - loss: 0.0071 - mean_absolute_error: 0.0616 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  30/1534 [..............................] - ETA: 5s - loss: 0.0063 - mean_absolute_error: 0.0581"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  45/1534 [..............................] - ETA: 5s - loss: 0.0071 - mean_absolute_error: 0.0595"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  61/1534 [>.............................] - ETA: 5s - loss: 0.0072 - mean_absolute_error: 0.0600"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  77/1534 [>.............................] - ETA: 4s - loss: 0.0075 - mean_absolute_error: 0.0601"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  93/1534 [>.............................] - ETA: 4s - loss: 0.0073 - mean_absolute_error: 0.0595"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 110/1534 [=>............................] - ETA: 4s - loss: 0.0071 - mean_absolute_error: 0.0591"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 126/1534 [=>............................] - ETA: 4s - loss: 0.0072 - mean_absolute_error: 0.0589"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 141/1534 [=>............................] - ETA: 4s - loss: 0.0073 - mean_absolute_error: 0.0593"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 157/1534 [==>...........................] - ETA: 4s - loss: 0.0072 - mean_absolute_error: 0.0593"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 172/1534 [==>...........................] - ETA: 4s - loss: 0.0072 - mean_absolute_error: 0.0591"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 187/1534 [==>...........................] - ETA: 4s - loss: 0.0072 - mean_absolute_error: 0.0590"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 202/1534 [==>...........................] - ETA: 4s - loss: 0.0071 - mean_absolute_error: 0.0588"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 218/1534 [===>..........................] - ETA: 4s - loss: 0.0069 - mean_absolute_error: 0.0582"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 234/1534 [===>..........................] - ETA: 4s - loss: 0.0069 - mean_absolute_error: 0.0583"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 250/1534 [===>..........................] - ETA: 4s - loss: 0.0070 - mean_absolute_error: 0.0586"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 266/1534 [====>.........................] - ETA: 4s - loss: 0.0070 - mean_absolute_error: 0.0588"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 282/1534 [====>.........................] - ETA: 4s - loss: 0.0069 - mean_absolute_error: 0.0587"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 298/1534 [====>.........................] - ETA: 4s - loss: 0.0070 - mean_absolute_error: 0.0588"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 313/1534 [=====>........................] - ETA: 4s - loss: 0.0070 - mean_absolute_error: 0.0589"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 328/1534 [=====>........................] - ETA: 4s - loss: 0.0071 - mean_absolute_error: 0.0594"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 344/1534 [=====>........................] - ETA: 3s - loss: 0.0071 - mean_absolute_error: 0.0595"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 359/1534 [======>.......................] - ETA: 3s - loss: 0.0070 - mean_absolute_error: 0.0594"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 374/1534 [======>.......................] - ETA: 3s - loss: 0.0071 - mean_absolute_error: 0.0597"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 389/1534 [======>.......................] - ETA: 3s - loss: 0.0071 - mean_absolute_error: 0.0598"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 404/1534 [======>.......................] - ETA: 3s - loss: 0.0072 - mean_absolute_error: 0.0599"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 419/1534 [=======>......................] - ETA: 3s - loss: 0.0071 - mean_absolute_error: 0.0598"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 434/1534 [=======>......................] - ETA: 3s - loss: 0.0071 - mean_absolute_error: 0.0598"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 450/1534 [=======>......................] - ETA: 3s - loss: 0.0071 - mean_absolute_error: 0.0598"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 465/1534 [========>.....................] - ETA: 3s - loss: 0.0071 - mean_absolute_error: 0.0598"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 481/1534 [========>.....................] - ETA: 3s - loss: 0.0071 - mean_absolute_error: 0.0600"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 496/1534 [========>.....................] - ETA: 3s - loss: 0.0071 - mean_absolute_error: 0.0600"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 511/1534 [========>.....................] - ETA: 3s - loss: 0.0071 - mean_absolute_error: 0.0601"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 526/1534 [=========>....................] - ETA: 3s - loss: 0.0070 - mean_absolute_error: 0.0598"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 541/1534 [=========>....................] - ETA: 3s - loss: 0.0070 - mean_absolute_error: 0.0598"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 556/1534 [=========>....................] - ETA: 3s - loss: 0.0070 - mean_absolute_error: 0.0598"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 571/1534 [==========>...................] - ETA: 3s - loss: 0.0070 - mean_absolute_error: 0.0597"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 586/1534 [==========>...................] - ETA: 3s - loss: 0.0070 - mean_absolute_error: 0.0596"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 601/1534 [==========>...................] - ETA: 3s - loss: 0.0070 - mean_absolute_error: 0.0596"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 616/1534 [===========>..................] - ETA: 3s - loss: 0.0069 - mean_absolute_error: 0.0595"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 632/1534 [===========>..................] - ETA: 3s - loss: 0.0069 - mean_absolute_error: 0.0594"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 647/1534 [===========>..................] - ETA: 2s - loss: 0.0069 - mean_absolute_error: 0.0595"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 662/1534 [===========>..................] - ETA: 2s - loss: 0.0069 - mean_absolute_error: 0.0595"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 677/1534 [============>.................] - ETA: 2s - loss: 0.0069 - mean_absolute_error: 0.0595"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 692/1534 [============>.................] - ETA: 2s - loss: 0.0069 - mean_absolute_error: 0.0595"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 707/1534 [============>.................] - ETA: 2s - loss: 0.0069 - mean_absolute_error: 0.0594"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 722/1534 [=============>................] - ETA: 2s - loss: 0.0069 - mean_absolute_error: 0.0594"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 737/1534 [=============>................] - ETA: 2s - loss: 0.0069 - mean_absolute_error: 0.0595"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 752/1534 [=============>................] - ETA: 2s - loss: 0.0070 - mean_absolute_error: 0.0597"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 767/1534 [==============>...............] - ETA: 2s - loss: 0.0070 - mean_absolute_error: 0.0597"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 782/1534 [==============>...............] - ETA: 2s - loss: 0.0070 - mean_absolute_error: 0.0598"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 797/1534 [==============>...............] - ETA: 2s - loss: 0.0070 - mean_absolute_error: 0.0597"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 812/1534 [==============>...............] - ETA: 2s - loss: 0.0070 - mean_absolute_error: 0.0597"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 828/1534 [===============>..............] - ETA: 2s - loss: 0.0070 - mean_absolute_error: 0.0597"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 844/1534 [===============>..............] - ETA: 2s - loss: 0.0070 - mean_absolute_error: 0.0597"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 859/1534 [===============>..............] - ETA: 2s - loss: 0.0070 - mean_absolute_error: 0.0597"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 875/1534 [================>.............] - ETA: 2s - loss: 0.0070 - mean_absolute_error: 0.0596"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 890/1534 [================>.............] - ETA: 2s - loss: 0.0070 - mean_absolute_error: 0.0597"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 906/1534 [================>.............] - ETA: 2s - loss: 0.0070 - mean_absolute_error: 0.0597"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 922/1534 [=================>............] - ETA: 2s - loss: 0.0070 - mean_absolute_error: 0.0597"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 937/1534 [=================>............] - ETA: 2s - loss: 0.0070 - mean_absolute_error: 0.0598"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 953/1534 [=================>............] - ETA: 1s - loss: 0.0070 - mean_absolute_error: 0.0598"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 968/1534 [=================>............] - ETA: 1s - loss: 0.0070 - mean_absolute_error: 0.0597"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 983/1534 [==================>...........] - ETA: 1s - loss: 0.0071 - mean_absolute_error: 0.0599"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 998/1534 [==================>...........] - ETA: 1s - loss: 0.0071 - mean_absolute_error: 0.0600"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1014/1534 [==================>...........] - ETA: 1s - loss: 0.0071 - mean_absolute_error: 0.0601"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1029/1534 [===================>..........] - ETA: 1s - loss: 0.0071 - mean_absolute_error: 0.0601"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1045/1534 [===================>..........] - ETA: 1s - loss: 0.0071 - mean_absolute_error: 0.0600"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1060/1534 [===================>..........] - ETA: 1s - loss: 0.0071 - mean_absolute_error: 0.0600"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1075/1534 [====================>.........] - ETA: 1s - loss: 0.0071 - mean_absolute_error: 0.0599"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1090/1534 [====================>.........] - ETA: 1s - loss: 0.0071 - mean_absolute_error: 0.0599"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1105/1534 [====================>.........] - ETA: 1s - loss: 0.0071 - mean_absolute_error: 0.0599"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1120/1534 [====================>.........] - ETA: 1s - loss: 0.0071 - mean_absolute_error: 0.0599"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1136/1534 [=====================>........] - ETA: 1s - loss: 0.0070 - mean_absolute_error: 0.0599"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1152/1534 [=====================>........] - ETA: 1s - loss: 0.0071 - mean_absolute_error: 0.0599"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1167/1534 [=====================>........] - ETA: 1s - loss: 0.0071 - mean_absolute_error: 0.0599"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1183/1534 [======================>.......] - ETA: 1s - loss: 0.0071 - mean_absolute_error: 0.0598"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1198/1534 [======================>.......] - ETA: 1s - loss: 0.0070 - mean_absolute_error: 0.0598"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1213/1534 [======================>.......] - ETA: 1s - loss: 0.0070 - mean_absolute_error: 0.0597"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1228/1534 [=======================>......] - ETA: 1s - loss: 0.0070 - mean_absolute_error: 0.0597"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1243/1534 [=======================>......] - ETA: 0s - loss: 0.0070 - mean_absolute_error: 0.0597"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1258/1534 [=======================>......] - ETA: 0s - loss: 0.0070 - mean_absolute_error: 0.0597"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1273/1534 [=======================>......] - ETA: 0s - loss: 0.0070 - mean_absolute_error: 0.0596"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1288/1534 [========================>.....] - ETA: 0s - loss: 0.0070 - mean_absolute_error: 0.0596"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1303/1534 [========================>.....] - ETA: 0s - loss: 0.0070 - mean_absolute_error: 0.0596"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1318/1534 [========================>.....] - ETA: 0s - loss: 0.0070 - mean_absolute_error: 0.0595"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1333/1534 [=========================>....] - ETA: 0s - loss: 0.0070 - mean_absolute_error: 0.0595"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1348/1534 [=========================>....] - ETA: 0s - loss: 0.0069 - mean_absolute_error: 0.0595"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1363/1534 [=========================>....] - ETA: 0s - loss: 0.0069 - mean_absolute_error: 0.0595"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1379/1534 [=========================>....] - ETA: 0s - loss: 0.0069 - mean_absolute_error: 0.0595"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1394/1534 [==========================>...] - ETA: 0s - loss: 0.0069 - mean_absolute_error: 0.0594"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1409/1534 [==========================>...] - ETA: 0s - loss: 0.0069 - mean_absolute_error: 0.0594"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1425/1534 [==========================>...] - ETA: 0s - loss: 0.0070 - mean_absolute_error: 0.0594"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1441/1534 [===========================>..] - ETA: 0s - loss: 0.0069 - mean_absolute_error: 0.0594"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1457/1534 [===========================>..] - ETA: 0s - loss: 0.0069 - mean_absolute_error: 0.0594"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1473/1534 [===========================>..] - ETA: 0s - loss: 0.0069 - mean_absolute_error: 0.0594"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1488/1534 [============================>.] - ETA: 0s - loss: 0.0069 - mean_absolute_error: 0.0594"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1503/1534 [============================>.] - ETA: 0s - loss: 0.0069 - mean_absolute_error: 0.0593"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1518/1534 [============================>.] - ETA: 0s - loss: 0.0069 - mean_absolute_error: 0.0593"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1534/1534 [==============================] - ETA: 0s - loss: 0.0069 - mean_absolute_error: 0.0593"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1534/1534 [==============================] - 6s 4ms/step - loss: 0.0069 - mean_absolute_error: 0.0593 - val_loss: 0.0067 - val_mean_absolute_error: 0.0580\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 8/20\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "   1/1534 [..............................] - ETA: 45s - loss: 0.0041 - mean_absolute_error: 0.0529"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  15/1534 [..............................] - ETA: 5s - loss: 0.0064 - mean_absolute_error: 0.0602 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  29/1534 [..............................] - ETA: 5s - loss: 0.0063 - mean_absolute_error: 0.0585"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  44/1534 [..............................] - ETA: 5s - loss: 0.0069 - mean_absolute_error: 0.0588"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  59/1534 [>.............................] - ETA: 5s - loss: 0.0068 - mean_absolute_error: 0.0588"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  75/1534 [>.............................] - ETA: 5s - loss: 0.0067 - mean_absolute_error: 0.0580"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  90/1534 [>.............................] - ETA: 4s - loss: 0.0069 - mean_absolute_error: 0.0582"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 106/1534 [=>............................] - ETA: 4s - loss: 0.0068 - mean_absolute_error: 0.0581"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 121/1534 [=>............................] - ETA: 4s - loss: 0.0068 - mean_absolute_error: 0.0579"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 136/1534 [=>............................] - ETA: 4s - loss: 0.0070 - mean_absolute_error: 0.0585"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 151/1534 [=>............................] - ETA: 4s - loss: 0.0071 - mean_absolute_error: 0.0590"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 166/1534 [==>...........................] - ETA: 4s - loss: 0.0071 - mean_absolute_error: 0.0590"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 181/1534 [==>...........................] - ETA: 4s - loss: 0.0071 - mean_absolute_error: 0.0591"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 196/1534 [==>...........................] - ETA: 4s - loss: 0.0070 - mean_absolute_error: 0.0587"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 211/1534 [===>..........................] - ETA: 4s - loss: 0.0069 - mean_absolute_error: 0.0585"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 226/1534 [===>..........................] - ETA: 4s - loss: 0.0068 - mean_absolute_error: 0.0581"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 241/1534 [===>..........................] - ETA: 4s - loss: 0.0068 - mean_absolute_error: 0.0582"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 256/1534 [====>.........................] - ETA: 4s - loss: 0.0068 - mean_absolute_error: 0.0584"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 271/1534 [====>.........................] - ETA: 4s - loss: 0.0068 - mean_absolute_error: 0.0584"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 286/1534 [====>.........................] - ETA: 4s - loss: 0.0068 - mean_absolute_error: 0.0584"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 301/1534 [====>.........................] - ETA: 4s - loss: 0.0067 - mean_absolute_error: 0.0582"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 316/1534 [=====>........................] - ETA: 4s - loss: 0.0068 - mean_absolute_error: 0.0585"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 332/1534 [=====>........................] - ETA: 4s - loss: 0.0069 - mean_absolute_error: 0.0588"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 348/1534 [=====>........................] - ETA: 4s - loss: 0.0068 - mean_absolute_error: 0.0587"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 363/1534 [======>.......................] - ETA: 3s - loss: 0.0069 - mean_absolute_error: 0.0589"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 379/1534 [======>.......................] - ETA: 3s - loss: 0.0069 - mean_absolute_error: 0.0589"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 395/1534 [======>.......................] - ETA: 3s - loss: 0.0069 - mean_absolute_error: 0.0589"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 411/1534 [=======>......................] - ETA: 3s - loss: 0.0069 - mean_absolute_error: 0.0591"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 426/1534 [=======>......................] - ETA: 3s - loss: 0.0069 - mean_absolute_error: 0.0591"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 442/1534 [=======>......................] - ETA: 3s - loss: 0.0069 - mean_absolute_error: 0.0591"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 457/1534 [=======>......................] - ETA: 3s - loss: 0.0069 - mean_absolute_error: 0.0591"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 472/1534 [========>.....................] - ETA: 3s - loss: 0.0069 - mean_absolute_error: 0.0591"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 488/1534 [========>.....................] - ETA: 3s - loss: 0.0069 - mean_absolute_error: 0.0591"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 503/1534 [========>.....................] - ETA: 3s - loss: 0.0069 - mean_absolute_error: 0.0592"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 518/1534 [=========>....................] - ETA: 3s - loss: 0.0068 - mean_absolute_error: 0.0590"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 533/1534 [=========>....................] - ETA: 3s - loss: 0.0068 - mean_absolute_error: 0.0590"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 549/1534 [=========>....................] - ETA: 3s - loss: 0.0069 - mean_absolute_error: 0.0590"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 565/1534 [==========>...................] - ETA: 3s - loss: 0.0069 - mean_absolute_error: 0.0590"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 580/1534 [==========>...................] - ETA: 3s - loss: 0.0068 - mean_absolute_error: 0.0589"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 595/1534 [==========>...................] - ETA: 3s - loss: 0.0068 - mean_absolute_error: 0.0588"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 610/1534 [==========>...................] - ETA: 3s - loss: 0.0068 - mean_absolute_error: 0.0588"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 626/1534 [===========>..................] - ETA: 3s - loss: 0.0068 - mean_absolute_error: 0.0587"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 642/1534 [===========>..................] - ETA: 3s - loss: 0.0068 - mean_absolute_error: 0.0587"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 658/1534 [===========>..................] - ETA: 2s - loss: 0.0068 - mean_absolute_error: 0.0587"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 673/1534 [============>.................] - ETA: 2s - loss: 0.0068 - mean_absolute_error: 0.0587"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 688/1534 [============>.................] - ETA: 2s - loss: 0.0068 - mean_absolute_error: 0.0586"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 704/1534 [============>.................] - ETA: 2s - loss: 0.0068 - mean_absolute_error: 0.0586"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 719/1534 [=============>................] - ETA: 2s - loss: 0.0068 - mean_absolute_error: 0.0586"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 734/1534 [=============>................] - ETA: 2s - loss: 0.0068 - mean_absolute_error: 0.0586"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 750/1534 [=============>................] - ETA: 2s - loss: 0.0068 - mean_absolute_error: 0.0587"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 765/1534 [=============>................] - ETA: 2s - loss: 0.0069 - mean_absolute_error: 0.0588"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 780/1534 [==============>...............] - ETA: 2s - loss: 0.0069 - mean_absolute_error: 0.0589"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 796/1534 [==============>...............] - ETA: 2s - loss: 0.0069 - mean_absolute_error: 0.0589"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 812/1534 [==============>...............] - ETA: 2s - loss: 0.0069 - mean_absolute_error: 0.0588"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 828/1534 [===============>..............] - ETA: 2s - loss: 0.0068 - mean_absolute_error: 0.0587"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 844/1534 [===============>..............] - ETA: 2s - loss: 0.0068 - mean_absolute_error: 0.0587"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 860/1534 [===============>..............] - ETA: 2s - loss: 0.0068 - mean_absolute_error: 0.0587"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 876/1534 [================>.............] - ETA: 2s - loss: 0.0069 - mean_absolute_error: 0.0588"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 891/1534 [================>.............] - ETA: 2s - loss: 0.0068 - mean_absolute_error: 0.0587"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 906/1534 [================>.............] - ETA: 2s - loss: 0.0069 - mean_absolute_error: 0.0587"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 921/1534 [=================>............] - ETA: 2s - loss: 0.0069 - mean_absolute_error: 0.0587"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 936/1534 [=================>............] - ETA: 2s - loss: 0.0068 - mean_absolute_error: 0.0587"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 951/1534 [=================>............] - ETA: 1s - loss: 0.0069 - mean_absolute_error: 0.0588"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 967/1534 [=================>............] - ETA: 1s - loss: 0.0069 - mean_absolute_error: 0.0588"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 982/1534 [==================>...........] - ETA: 1s - loss: 0.0069 - mean_absolute_error: 0.0590"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 997/1534 [==================>...........] - ETA: 1s - loss: 0.0069 - mean_absolute_error: 0.0590"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1012/1534 [==================>...........] - ETA: 1s - loss: 0.0069 - mean_absolute_error: 0.0590"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1028/1534 [===================>..........] - ETA: 1s - loss: 0.0069 - mean_absolute_error: 0.0590"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1043/1534 [===================>..........] - ETA: 1s - loss: 0.0069 - mean_absolute_error: 0.0590"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1059/1534 [===================>..........] - ETA: 1s - loss: 0.0069 - mean_absolute_error: 0.0591"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1074/1534 [====================>.........] - ETA: 1s - loss: 0.0069 - mean_absolute_error: 0.0591"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1090/1534 [====================>.........] - ETA: 1s - loss: 0.0069 - mean_absolute_error: 0.0590"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1105/1534 [====================>.........] - ETA: 1s - loss: 0.0069 - mean_absolute_error: 0.0590"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1120/1534 [====================>.........] - ETA: 1s - loss: 0.0069 - mean_absolute_error: 0.0591"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1136/1534 [=====================>........] - ETA: 1s - loss: 0.0069 - mean_absolute_error: 0.0591"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1152/1534 [=====================>........] - ETA: 1s - loss: 0.0069 - mean_absolute_error: 0.0591"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1168/1534 [=====================>........] - ETA: 1s - loss: 0.0069 - mean_absolute_error: 0.0591"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1183/1534 [======================>.......] - ETA: 1s - loss: 0.0069 - mean_absolute_error: 0.0591"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1198/1534 [======================>.......] - ETA: 1s - loss: 0.0069 - mean_absolute_error: 0.0591"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1214/1534 [======================>.......] - ETA: 1s - loss: 0.0069 - mean_absolute_error: 0.0590"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1230/1534 [=======================>......] - ETA: 1s - loss: 0.0069 - mean_absolute_error: 0.0590"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1246/1534 [=======================>......] - ETA: 0s - loss: 0.0069 - mean_absolute_error: 0.0590"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1262/1534 [=======================>......] - ETA: 0s - loss: 0.0069 - mean_absolute_error: 0.0590"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1277/1534 [=======================>......] - ETA: 0s - loss: 0.0069 - mean_absolute_error: 0.0589"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1292/1534 [========================>.....] - ETA: 0s - loss: 0.0069 - mean_absolute_error: 0.0589"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1307/1534 [========================>.....] - ETA: 0s - loss: 0.0068 - mean_absolute_error: 0.0589"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1323/1534 [========================>.....] - ETA: 0s - loss: 0.0068 - mean_absolute_error: 0.0589"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1339/1534 [=========================>....] - ETA: 0s - loss: 0.0068 - mean_absolute_error: 0.0589"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1354/1534 [=========================>....] - ETA: 0s - loss: 0.0068 - mean_absolute_error: 0.0589"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1370/1534 [=========================>....] - ETA: 0s - loss: 0.0068 - mean_absolute_error: 0.0588"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1385/1534 [==========================>...] - ETA: 0s - loss: 0.0068 - mean_absolute_error: 0.0588"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1400/1534 [==========================>...] - ETA: 0s - loss: 0.0068 - mean_absolute_error: 0.0589"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1415/1534 [==========================>...] - ETA: 0s - loss: 0.0068 - mean_absolute_error: 0.0589"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1431/1534 [==========================>...] - ETA: 0s - loss: 0.0068 - mean_absolute_error: 0.0589"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1447/1534 [===========================>..] - ETA: 0s - loss: 0.0068 - mean_absolute_error: 0.0589"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1462/1534 [===========================>..] - ETA: 0s - loss: 0.0068 - mean_absolute_error: 0.0589"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1478/1534 [===========================>..] - ETA: 0s - loss: 0.0068 - mean_absolute_error: 0.0589"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1494/1534 [============================>.] - ETA: 0s - loss: 0.0068 - mean_absolute_error: 0.0588"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1510/1534 [============================>.] - ETA: 0s - loss: 0.0068 - mean_absolute_error: 0.0588"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1526/1534 [============================>.] - ETA: 0s - loss: 0.0068 - mean_absolute_error: 0.0587"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1534/1534 [==============================] - 6s 4ms/step - loss: 0.0068 - mean_absolute_error: 0.0587 - val_loss: 0.0068 - val_mean_absolute_error: 0.0578\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 9/20\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "   1/1534 [..............................] - ETA: 42s - loss: 0.0086 - mean_absolute_error: 0.0612"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  15/1534 [..............................] - ETA: 5s - loss: 0.0069 - mean_absolute_error: 0.0575 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  30/1534 [..............................] - ETA: 5s - loss: 0.0060 - mean_absolute_error: 0.0566"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  45/1534 [..............................] - ETA: 5s - loss: 0.0068 - mean_absolute_error: 0.0582"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  61/1534 [>.............................] - ETA: 5s - loss: 0.0070 - mean_absolute_error: 0.0588"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  76/1534 [>.............................] - ETA: 4s - loss: 0.0070 - mean_absolute_error: 0.0583"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  92/1534 [>.............................] - ETA: 4s - loss: 0.0069 - mean_absolute_error: 0.0582"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 109/1534 [=>............................] - ETA: 4s - loss: 0.0069 - mean_absolute_error: 0.0582"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 125/1534 [=>............................] - ETA: 4s - loss: 0.0071 - mean_absolute_error: 0.0587"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 140/1534 [=>............................] - ETA: 4s - loss: 0.0072 - mean_absolute_error: 0.0589"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 156/1534 [==>...........................] - ETA: 4s - loss: 0.0072 - mean_absolute_error: 0.0590"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 172/1534 [==>...........................] - ETA: 4s - loss: 0.0071 - mean_absolute_error: 0.0588"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 188/1534 [==>...........................] - ETA: 4s - loss: 0.0070 - mean_absolute_error: 0.0586"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 204/1534 [==>...........................] - ETA: 4s - loss: 0.0069 - mean_absolute_error: 0.0583"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 220/1534 [===>..........................] - ETA: 4s - loss: 0.0069 - mean_absolute_error: 0.0580"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 235/1534 [===>..........................] - ETA: 4s - loss: 0.0069 - mean_absolute_error: 0.0580"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 250/1534 [===>..........................] - ETA: 4s - loss: 0.0068 - mean_absolute_error: 0.0580"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 265/1534 [====>.........................] - ETA: 4s - loss: 0.0069 - mean_absolute_error: 0.0581"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 281/1534 [====>.........................] - ETA: 4s - loss: 0.0068 - mean_absolute_error: 0.0580"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 296/1534 [====>.........................] - ETA: 4s - loss: 0.0067 - mean_absolute_error: 0.0577"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 312/1534 [=====>........................] - ETA: 4s - loss: 0.0068 - mean_absolute_error: 0.0579"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 327/1534 [=====>........................] - ETA: 4s - loss: 0.0068 - mean_absolute_error: 0.0581"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 343/1534 [=====>........................] - ETA: 3s - loss: 0.0068 - mean_absolute_error: 0.0581"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 358/1534 [======>.......................] - ETA: 3s - loss: 0.0068 - mean_absolute_error: 0.0582"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 374/1534 [======>.......................] - ETA: 3s - loss: 0.0069 - mean_absolute_error: 0.0582"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 389/1534 [======>.......................] - ETA: 3s - loss: 0.0069 - mean_absolute_error: 0.0583"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 405/1534 [======>.......................] - ETA: 3s - loss: 0.0069 - mean_absolute_error: 0.0586"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 421/1534 [=======>......................] - ETA: 3s - loss: 0.0069 - mean_absolute_error: 0.0588"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 437/1534 [=======>......................] - ETA: 3s - loss: 0.0069 - mean_absolute_error: 0.0587"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 453/1534 [=======>......................] - ETA: 3s - loss: 0.0069 - mean_absolute_error: 0.0586"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 468/1534 [========>.....................] - ETA: 3s - loss: 0.0069 - mean_absolute_error: 0.0586"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 484/1534 [========>.....................] - ETA: 3s - loss: 0.0069 - mean_absolute_error: 0.0588"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 500/1534 [========>.....................] - ETA: 3s - loss: 0.0069 - mean_absolute_error: 0.0588"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 516/1534 [=========>....................] - ETA: 3s - loss: 0.0069 - mean_absolute_error: 0.0586"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 532/1534 [=========>....................] - ETA: 3s - loss: 0.0068 - mean_absolute_error: 0.0585"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 547/1534 [=========>....................] - ETA: 3s - loss: 0.0068 - mean_absolute_error: 0.0585"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 562/1534 [=========>....................] - ETA: 3s - loss: 0.0069 - mean_absolute_error: 0.0585"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 578/1534 [==========>...................] - ETA: 3s - loss: 0.0068 - mean_absolute_error: 0.0584"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 594/1534 [==========>...................] - ETA: 3s - loss: 0.0068 - mean_absolute_error: 0.0583"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 610/1534 [==========>...................] - ETA: 3s - loss: 0.0068 - mean_absolute_error: 0.0582"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 626/1534 [===========>..................] - ETA: 3s - loss: 0.0067 - mean_absolute_error: 0.0581"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 642/1534 [===========>..................] - ETA: 2s - loss: 0.0067 - mean_absolute_error: 0.0581"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 658/1534 [===========>..................] - ETA: 2s - loss: 0.0067 - mean_absolute_error: 0.0582"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 674/1534 [============>.................] - ETA: 2s - loss: 0.0067 - mean_absolute_error: 0.0581"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 690/1534 [============>.................] - ETA: 2s - loss: 0.0067 - mean_absolute_error: 0.0581"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 706/1534 [============>.................] - ETA: 2s - loss: 0.0068 - mean_absolute_error: 0.0582"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 722/1534 [=============>................] - ETA: 2s - loss: 0.0068 - mean_absolute_error: 0.0582"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 738/1534 [=============>................] - ETA: 2s - loss: 0.0068 - mean_absolute_error: 0.0582"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 753/1534 [=============>................] - ETA: 2s - loss: 0.0068 - mean_absolute_error: 0.0583"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 769/1534 [==============>...............] - ETA: 2s - loss: 0.0068 - mean_absolute_error: 0.0583"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 785/1534 [==============>...............] - ETA: 2s - loss: 0.0068 - mean_absolute_error: 0.0583"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 800/1534 [==============>...............] - ETA: 2s - loss: 0.0068 - mean_absolute_error: 0.0584"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 816/1534 [==============>...............] - ETA: 2s - loss: 0.0068 - mean_absolute_error: 0.0583"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 832/1534 [===============>..............] - ETA: 2s - loss: 0.0068 - mean_absolute_error: 0.0583"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 848/1534 [===============>..............] - ETA: 2s - loss: 0.0068 - mean_absolute_error: 0.0583"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 864/1534 [===============>..............] - ETA: 2s - loss: 0.0068 - mean_absolute_error: 0.0583"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 880/1534 [================>.............] - ETA: 2s - loss: 0.0068 - mean_absolute_error: 0.0582"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 896/1534 [================>.............] - ETA: 2s - loss: 0.0068 - mean_absolute_error: 0.0583"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 912/1534 [================>.............] - ETA: 2s - loss: 0.0068 - mean_absolute_error: 0.0583"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 928/1534 [=================>............] - ETA: 1s - loss: 0.0068 - mean_absolute_error: 0.0583"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 944/1534 [=================>............] - ETA: 1s - loss: 0.0068 - mean_absolute_error: 0.0583"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 960/1534 [=================>............] - ETA: 1s - loss: 0.0068 - mean_absolute_error: 0.0583"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 975/1534 [==================>...........] - ETA: 1s - loss: 0.0068 - mean_absolute_error: 0.0583"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 991/1534 [==================>...........] - ETA: 1s - loss: 0.0069 - mean_absolute_error: 0.0585"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1006/1534 [==================>...........] - ETA: 1s - loss: 0.0069 - mean_absolute_error: 0.0586"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1021/1534 [==================>...........] - ETA: 1s - loss: 0.0069 - mean_absolute_error: 0.0586"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1036/1534 [===================>..........] - ETA: 1s - loss: 0.0069 - mean_absolute_error: 0.0585"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1052/1534 [===================>..........] - ETA: 1s - loss: 0.0069 - mean_absolute_error: 0.0585"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1068/1534 [===================>..........] - ETA: 1s - loss: 0.0069 - mean_absolute_error: 0.0586"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1084/1534 [====================>.........] - ETA: 1s - loss: 0.0068 - mean_absolute_error: 0.0585"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1100/1534 [====================>.........] - ETA: 1s - loss: 0.0068 - mean_absolute_error: 0.0584"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1116/1534 [====================>.........] - ETA: 1s - loss: 0.0068 - mean_absolute_error: 0.0585"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1132/1534 [=====================>........] - ETA: 1s - loss: 0.0068 - mean_absolute_error: 0.0585"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1148/1534 [=====================>........] - ETA: 1s - loss: 0.0068 - mean_absolute_error: 0.0585"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1164/1534 [=====================>........] - ETA: 1s - loss: 0.0068 - mean_absolute_error: 0.0585"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1180/1534 [======================>.......] - ETA: 1s - loss: 0.0069 - mean_absolute_error: 0.0585"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1196/1534 [======================>.......] - ETA: 1s - loss: 0.0068 - mean_absolute_error: 0.0585"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1212/1534 [======================>.......] - ETA: 1s - loss: 0.0068 - mean_absolute_error: 0.0584"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1228/1534 [=======================>......] - ETA: 1s - loss: 0.0068 - mean_absolute_error: 0.0584"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1244/1534 [=======================>......] - ETA: 0s - loss: 0.0068 - mean_absolute_error: 0.0584"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1259/1534 [=======================>......] - ETA: 0s - loss: 0.0068 - mean_absolute_error: 0.0584"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1274/1534 [=======================>......] - ETA: 0s - loss: 0.0068 - mean_absolute_error: 0.0583"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1290/1534 [========================>.....] - ETA: 0s - loss: 0.0068 - mean_absolute_error: 0.0583"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1305/1534 [========================>.....] - ETA: 0s - loss: 0.0068 - mean_absolute_error: 0.0582"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1320/1534 [========================>.....] - ETA: 0s - loss: 0.0068 - mean_absolute_error: 0.0582"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1335/1534 [=========================>....] - ETA: 0s - loss: 0.0067 - mean_absolute_error: 0.0582"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1350/1534 [=========================>....] - ETA: 0s - loss: 0.0068 - mean_absolute_error: 0.0582"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1366/1534 [=========================>....] - ETA: 0s - loss: 0.0068 - mean_absolute_error: 0.0582"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1382/1534 [==========================>...] - ETA: 0s - loss: 0.0068 - mean_absolute_error: 0.0582"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1398/1534 [==========================>...] - ETA: 0s - loss: 0.0068 - mean_absolute_error: 0.0582"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1414/1534 [==========================>...] - ETA: 0s - loss: 0.0068 - mean_absolute_error: 0.0582"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1430/1534 [==========================>...] - ETA: 0s - loss: 0.0068 - mean_absolute_error: 0.0582"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1446/1534 [===========================>..] - ETA: 0s - loss: 0.0068 - mean_absolute_error: 0.0582"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1461/1534 [===========================>..] - ETA: 0s - loss: 0.0068 - mean_absolute_error: 0.0582"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1477/1534 [===========================>..] - ETA: 0s - loss: 0.0067 - mean_absolute_error: 0.0582"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1493/1534 [============================>.] - ETA: 0s - loss: 0.0067 - mean_absolute_error: 0.0582"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1509/1534 [============================>.] - ETA: 0s - loss: 0.0067 - mean_absolute_error: 0.0582"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1525/1534 [============================>.] - ETA: 0s - loss: 0.0067 - mean_absolute_error: 0.0581"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1534/1534 [==============================] - 6s 4ms/step - loss: 0.0067 - mean_absolute_error: 0.0581 - val_loss: 0.0065 - val_mean_absolute_error: 0.0578\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 10/20\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "   1/1534 [..............................] - ETA: 42s - loss: 0.0041 - mean_absolute_error: 0.0498"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  15/1534 [..............................] - ETA: 5s - loss: 0.0060 - mean_absolute_error: 0.0560 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  30/1534 [..............................] - ETA: 5s - loss: 0.0053 - mean_absolute_error: 0.0528"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  46/1534 [..............................] - ETA: 5s - loss: 0.0065 - mean_absolute_error: 0.0559"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  62/1534 [>.............................] - ETA: 5s - loss: 0.0066 - mean_absolute_error: 0.0569"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  78/1534 [>.............................] - ETA: 4s - loss: 0.0068 - mean_absolute_error: 0.0573"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  94/1534 [>.............................] - ETA: 4s - loss: 0.0069 - mean_absolute_error: 0.0581"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 111/1534 [=>............................] - ETA: 4s - loss: 0.0068 - mean_absolute_error: 0.0579"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 126/1534 [=>............................] - ETA: 4s - loss: 0.0069 - mean_absolute_error: 0.0580"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 141/1534 [=>............................] - ETA: 4s - loss: 0.0069 - mean_absolute_error: 0.0579"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 157/1534 [==>...........................] - ETA: 4s - loss: 0.0069 - mean_absolute_error: 0.0577"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 173/1534 [==>...........................] - ETA: 4s - loss: 0.0068 - mean_absolute_error: 0.0575"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 189/1534 [==>...........................] - ETA: 4s - loss: 0.0068 - mean_absolute_error: 0.0576"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 205/1534 [===>..........................] - ETA: 4s - loss: 0.0069 - mean_absolute_error: 0.0579"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 220/1534 [===>..........................] - ETA: 4s - loss: 0.0069 - mean_absolute_error: 0.0578"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 235/1534 [===>..........................] - ETA: 4s - loss: 0.0068 - mean_absolute_error: 0.0576"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 250/1534 [===>..........................] - ETA: 4s - loss: 0.0069 - mean_absolute_error: 0.0580"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 266/1534 [====>.........................] - ETA: 4s - loss: 0.0069 - mean_absolute_error: 0.0581"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 281/1534 [====>.........................] - ETA: 4s - loss: 0.0068 - mean_absolute_error: 0.0579"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 296/1534 [====>.........................] - ETA: 4s - loss: 0.0068 - mean_absolute_error: 0.0578"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 311/1534 [=====>........................] - ETA: 4s - loss: 0.0068 - mean_absolute_error: 0.0581"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 327/1534 [=====>........................] - ETA: 4s - loss: 0.0069 - mean_absolute_error: 0.0583"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 343/1534 [=====>........................] - ETA: 3s - loss: 0.0069 - mean_absolute_error: 0.0583"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 359/1534 [======>.......................] - ETA: 3s - loss: 0.0069 - mean_absolute_error: 0.0585"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 375/1534 [======>.......................] - ETA: 3s - loss: 0.0069 - mean_absolute_error: 0.0586"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 391/1534 [======>.......................] - ETA: 3s - loss: 0.0069 - mean_absolute_error: 0.0585"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 407/1534 [======>.......................] - ETA: 3s - loss: 0.0069 - mean_absolute_error: 0.0584"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 422/1534 [=======>......................] - ETA: 3s - loss: 0.0069 - mean_absolute_error: 0.0584"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 437/1534 [=======>......................] - ETA: 3s - loss: 0.0068 - mean_absolute_error: 0.0583"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 453/1534 [=======>......................] - ETA: 3s - loss: 0.0068 - mean_absolute_error: 0.0584"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 469/1534 [========>.....................] - ETA: 3s - loss: 0.0068 - mean_absolute_error: 0.0585"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 484/1534 [========>.....................] - ETA: 3s - loss: 0.0068 - mean_absolute_error: 0.0586"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 499/1534 [========>.....................] - ETA: 3s - loss: 0.0068 - mean_absolute_error: 0.0586"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 514/1534 [=========>....................] - ETA: 3s - loss: 0.0068 - mean_absolute_error: 0.0585"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 530/1534 [=========>....................] - ETA: 3s - loss: 0.0068 - mean_absolute_error: 0.0584"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 546/1534 [=========>....................] - ETA: 3s - loss: 0.0068 - mean_absolute_error: 0.0583"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 562/1534 [=========>....................] - ETA: 3s - loss: 0.0068 - mean_absolute_error: 0.0582"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 578/1534 [==========>...................] - ETA: 3s - loss: 0.0068 - mean_absolute_error: 0.0582"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 593/1534 [==========>...................] - ETA: 3s - loss: 0.0067 - mean_absolute_error: 0.0581"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 608/1534 [==========>...................] - ETA: 3s - loss: 0.0067 - mean_absolute_error: 0.0581"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 623/1534 [===========>..................] - ETA: 3s - loss: 0.0067 - mean_absolute_error: 0.0580"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 639/1534 [===========>..................] - ETA: 2s - loss: 0.0067 - mean_absolute_error: 0.0580"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 654/1534 [===========>..................] - ETA: 2s - loss: 0.0067 - mean_absolute_error: 0.0581"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 670/1534 [============>.................] - ETA: 2s - loss: 0.0067 - mean_absolute_error: 0.0580"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 686/1534 [============>.................] - ETA: 2s - loss: 0.0067 - mean_absolute_error: 0.0580"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 702/1534 [============>.................] - ETA: 2s - loss: 0.0067 - mean_absolute_error: 0.0580"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 717/1534 [=============>................] - ETA: 2s - loss: 0.0067 - mean_absolute_error: 0.0581"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 733/1534 [=============>................] - ETA: 2s - loss: 0.0067 - mean_absolute_error: 0.0581"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 748/1534 [=============>................] - ETA: 2s - loss: 0.0068 - mean_absolute_error: 0.0583"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 763/1534 [=============>................] - ETA: 2s - loss: 0.0067 - mean_absolute_error: 0.0582"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 778/1534 [==============>...............] - ETA: 2s - loss: 0.0068 - mean_absolute_error: 0.0583"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 793/1534 [==============>...............] - ETA: 2s - loss: 0.0068 - mean_absolute_error: 0.0583"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 808/1534 [==============>...............] - ETA: 2s - loss: 0.0068 - mean_absolute_error: 0.0583"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 824/1534 [===============>..............] - ETA: 2s - loss: 0.0068 - mean_absolute_error: 0.0582"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 840/1534 [===============>..............] - ETA: 2s - loss: 0.0067 - mean_absolute_error: 0.0582"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 855/1534 [===============>..............] - ETA: 2s - loss: 0.0068 - mean_absolute_error: 0.0581"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 870/1534 [================>.............] - ETA: 2s - loss: 0.0067 - mean_absolute_error: 0.0581"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 885/1534 [================>.............] - ETA: 2s - loss: 0.0068 - mean_absolute_error: 0.0581"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 900/1534 [================>.............] - ETA: 2s - loss: 0.0068 - mean_absolute_error: 0.0582"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 915/1534 [================>.............] - ETA: 2s - loss: 0.0068 - mean_absolute_error: 0.0582"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 930/1534 [=================>............] - ETA: 2s - loss: 0.0068 - mean_absolute_error: 0.0581"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 946/1534 [=================>............] - ETA: 1s - loss: 0.0068 - mean_absolute_error: 0.0582"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 961/1534 [=================>............] - ETA: 1s - loss: 0.0068 - mean_absolute_error: 0.0582"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 976/1534 [==================>...........] - ETA: 1s - loss: 0.0068 - mean_absolute_error: 0.0582"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 991/1534 [==================>...........] - ETA: 1s - loss: 0.0068 - mean_absolute_error: 0.0582"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1006/1534 [==================>...........] - ETA: 1s - loss: 0.0068 - mean_absolute_error: 0.0583"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1021/1534 [==================>...........] - ETA: 1s - loss: 0.0068 - mean_absolute_error: 0.0583"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1036/1534 [===================>..........] - ETA: 1s - loss: 0.0068 - mean_absolute_error: 0.0582"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1051/1534 [===================>..........] - ETA: 1s - loss: 0.0068 - mean_absolute_error: 0.0582"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1067/1534 [===================>..........] - ETA: 1s - loss: 0.0068 - mean_absolute_error: 0.0583"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1083/1534 [====================>.........] - ETA: 1s - loss: 0.0068 - mean_absolute_error: 0.0583"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1099/1534 [====================>.........] - ETA: 1s - loss: 0.0068 - mean_absolute_error: 0.0582"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1114/1534 [====================>.........] - ETA: 1s - loss: 0.0067 - mean_absolute_error: 0.0582"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1130/1534 [=====================>........] - ETA: 1s - loss: 0.0068 - mean_absolute_error: 0.0583"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1145/1534 [=====================>........] - ETA: 1s - loss: 0.0068 - mean_absolute_error: 0.0583"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1160/1534 [=====================>........] - ETA: 1s - loss: 0.0068 - mean_absolute_error: 0.0584"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1175/1534 [=====================>........] - ETA: 1s - loss: 0.0068 - mean_absolute_error: 0.0583"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1190/1534 [======================>.......] - ETA: 1s - loss: 0.0068 - mean_absolute_error: 0.0583"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1205/1534 [======================>.......] - ETA: 1s - loss: 0.0068 - mean_absolute_error: 0.0582"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1220/1534 [======================>.......] - ETA: 1s - loss: 0.0067 - mean_absolute_error: 0.0582"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1236/1534 [=======================>......] - ETA: 0s - loss: 0.0067 - mean_absolute_error: 0.0582"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1251/1534 [=======================>......] - ETA: 0s - loss: 0.0067 - mean_absolute_error: 0.0582"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1267/1534 [=======================>......] - ETA: 0s - loss: 0.0067 - mean_absolute_error: 0.0582"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1283/1534 [========================>.....] - ETA: 0s - loss: 0.0067 - mean_absolute_error: 0.0581"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1299/1534 [========================>.....] - ETA: 0s - loss: 0.0067 - mean_absolute_error: 0.0580"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1314/1534 [========================>.....] - ETA: 0s - loss: 0.0067 - mean_absolute_error: 0.0580"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1329/1534 [========================>.....] - ETA: 0s - loss: 0.0067 - mean_absolute_error: 0.0580"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1344/1534 [=========================>....] - ETA: 0s - loss: 0.0067 - mean_absolute_error: 0.0580"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1359/1534 [=========================>....] - ETA: 0s - loss: 0.0067 - mean_absolute_error: 0.0580"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1374/1534 [=========================>....] - ETA: 0s - loss: 0.0067 - mean_absolute_error: 0.0579"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1390/1534 [==========================>...] - ETA: 0s - loss: 0.0067 - mean_absolute_error: 0.0580"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1405/1534 [==========================>...] - ETA: 0s - loss: 0.0067 - mean_absolute_error: 0.0580"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1420/1534 [==========================>...] - ETA: 0s - loss: 0.0067 - mean_absolute_error: 0.0580"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1436/1534 [===========================>..] - ETA: 0s - loss: 0.0067 - mean_absolute_error: 0.0580"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1451/1534 [===========================>..] - ETA: 0s - loss: 0.0067 - mean_absolute_error: 0.0580"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1466/1534 [===========================>..] - ETA: 0s - loss: 0.0067 - mean_absolute_error: 0.0580"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1481/1534 [===========================>..] - ETA: 0s - loss: 0.0067 - mean_absolute_error: 0.0580"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1497/1534 [============================>.] - ETA: 0s - loss: 0.0067 - mean_absolute_error: 0.0580"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1512/1534 [============================>.] - ETA: 0s - loss: 0.0067 - mean_absolute_error: 0.0580"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1528/1534 [============================>.] - ETA: 0s - loss: 0.0067 - mean_absolute_error: 0.0580"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1534/1534 [==============================] - 6s 4ms/step - loss: 0.0067 - mean_absolute_error: 0.0580 - val_loss: 0.0067 - val_mean_absolute_error: 0.0591\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 11/20\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "   1/1534 [..............................] - ETA: 43s - loss: 0.0091 - mean_absolute_error: 0.0662"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  15/1534 [..............................] - ETA: 5s - loss: 0.0057 - mean_absolute_error: 0.0555 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  30/1534 [..............................] - ETA: 5s - loss: 0.0056 - mean_absolute_error: 0.0547"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  45/1534 [..............................] - ETA: 5s - loss: 0.0067 - mean_absolute_error: 0.0572"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  60/1534 [>.............................] - ETA: 5s - loss: 0.0066 - mean_absolute_error: 0.0578"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  74/1534 [>.............................] - ETA: 5s - loss: 0.0070 - mean_absolute_error: 0.0581"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  90/1534 [>.............................] - ETA: 5s - loss: 0.0069 - mean_absolute_error: 0.0576"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 105/1534 [=>............................] - ETA: 4s - loss: 0.0068 - mean_absolute_error: 0.0576"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 121/1534 [=>............................] - ETA: 4s - loss: 0.0068 - mean_absolute_error: 0.0575"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 136/1534 [=>............................] - ETA: 4s - loss: 0.0069 - mean_absolute_error: 0.0578"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 151/1534 [=>............................] - ETA: 4s - loss: 0.0070 - mean_absolute_error: 0.0580"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 166/1534 [==>...........................] - ETA: 4s - loss: 0.0069 - mean_absolute_error: 0.0578"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 181/1534 [==>...........................] - ETA: 4s - loss: 0.0068 - mean_absolute_error: 0.0573"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 196/1534 [==>...........................] - ETA: 4s - loss: 0.0068 - mean_absolute_error: 0.0573"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 211/1534 [===>..........................] - ETA: 4s - loss: 0.0067 - mean_absolute_error: 0.0569"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 226/1534 [===>..........................] - ETA: 4s - loss: 0.0066 - mean_absolute_error: 0.0565"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 241/1534 [===>..........................] - ETA: 4s - loss: 0.0067 - mean_absolute_error: 0.0569"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 256/1534 [====>.........................] - ETA: 4s - loss: 0.0067 - mean_absolute_error: 0.0574"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 271/1534 [====>.........................] - ETA: 4s - loss: 0.0066 - mean_absolute_error: 0.0571"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 286/1534 [====>.........................] - ETA: 4s - loss: 0.0066 - mean_absolute_error: 0.0571"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 301/1534 [====>.........................] - ETA: 4s - loss: 0.0066 - mean_absolute_error: 0.0573"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 317/1534 [=====>........................] - ETA: 4s - loss: 0.0066 - mean_absolute_error: 0.0573"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 332/1534 [=====>........................] - ETA: 4s - loss: 0.0066 - mean_absolute_error: 0.0573"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 347/1534 [=====>........................] - ETA: 4s - loss: 0.0066 - mean_absolute_error: 0.0574"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 363/1534 [======>.......................] - ETA: 4s - loss: 0.0067 - mean_absolute_error: 0.0575"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 378/1534 [======>.......................] - ETA: 3s - loss: 0.0068 - mean_absolute_error: 0.0578"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 394/1534 [======>.......................] - ETA: 3s - loss: 0.0067 - mean_absolute_error: 0.0579"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 409/1534 [======>.......................] - ETA: 3s - loss: 0.0068 - mean_absolute_error: 0.0578"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 424/1534 [=======>......................] - ETA: 3s - loss: 0.0067 - mean_absolute_error: 0.0577"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 440/1534 [=======>......................] - ETA: 3s - loss: 0.0067 - mean_absolute_error: 0.0576"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 455/1534 [=======>......................] - ETA: 3s - loss: 0.0067 - mean_absolute_error: 0.0577"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 470/1534 [========>.....................] - ETA: 3s - loss: 0.0067 - mean_absolute_error: 0.0578"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 485/1534 [========>.....................] - ETA: 3s - loss: 0.0067 - mean_absolute_error: 0.0579"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 500/1534 [========>.....................] - ETA: 3s - loss: 0.0067 - mean_absolute_error: 0.0578"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 515/1534 [=========>....................] - ETA: 3s - loss: 0.0067 - mean_absolute_error: 0.0577"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 530/1534 [=========>....................] - ETA: 3s - loss: 0.0066 - mean_absolute_error: 0.0576"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 546/1534 [=========>....................] - ETA: 3s - loss: 0.0067 - mean_absolute_error: 0.0576"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 561/1534 [=========>....................] - ETA: 3s - loss: 0.0066 - mean_absolute_error: 0.0576"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 576/1534 [==========>...................] - ETA: 3s - loss: 0.0066 - mean_absolute_error: 0.0576"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 591/1534 [==========>...................] - ETA: 3s - loss: 0.0066 - mean_absolute_error: 0.0575"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 606/1534 [==========>...................] - ETA: 3s - loss: 0.0066 - mean_absolute_error: 0.0575"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 621/1534 [===========>..................] - ETA: 3s - loss: 0.0066 - mean_absolute_error: 0.0574"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 636/1534 [===========>..................] - ETA: 3s - loss: 0.0065 - mean_absolute_error: 0.0574"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 651/1534 [===========>..................] - ETA: 3s - loss: 0.0065 - mean_absolute_error: 0.0574"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 666/1534 [============>.................] - ETA: 2s - loss: 0.0065 - mean_absolute_error: 0.0574"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 681/1534 [============>.................] - ETA: 2s - loss: 0.0066 - mean_absolute_error: 0.0574"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 696/1534 [============>.................] - ETA: 2s - loss: 0.0065 - mean_absolute_error: 0.0573"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 712/1534 [============>.................] - ETA: 2s - loss: 0.0066 - mean_absolute_error: 0.0574"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 727/1534 [=============>................] - ETA: 2s - loss: 0.0066 - mean_absolute_error: 0.0573"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 742/1534 [=============>................] - ETA: 2s - loss: 0.0066 - mean_absolute_error: 0.0575"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 757/1534 [=============>................] - ETA: 2s - loss: 0.0066 - mean_absolute_error: 0.0574"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 773/1534 [==============>...............] - ETA: 2s - loss: 0.0066 - mean_absolute_error: 0.0575"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 788/1534 [==============>...............] - ETA: 2s - loss: 0.0067 - mean_absolute_error: 0.0576"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 803/1534 [==============>...............] - ETA: 2s - loss: 0.0066 - mean_absolute_error: 0.0575"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 818/1534 [==============>...............] - ETA: 2s - loss: 0.0066 - mean_absolute_error: 0.0575"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 834/1534 [===============>..............] - ETA: 2s - loss: 0.0066 - mean_absolute_error: 0.0575"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 850/1534 [===============>..............] - ETA: 2s - loss: 0.0066 - mean_absolute_error: 0.0575"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 865/1534 [===============>..............] - ETA: 2s - loss: 0.0066 - mean_absolute_error: 0.0575"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 881/1534 [================>.............] - ETA: 2s - loss: 0.0066 - mean_absolute_error: 0.0575"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 896/1534 [================>.............] - ETA: 2s - loss: 0.0066 - mean_absolute_error: 0.0575"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 912/1534 [================>.............] - ETA: 2s - loss: 0.0066 - mean_absolute_error: 0.0575"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 928/1534 [=================>............] - ETA: 2s - loss: 0.0066 - mean_absolute_error: 0.0575"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 943/1534 [=================>............] - ETA: 2s - loss: 0.0066 - mean_absolute_error: 0.0575"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 959/1534 [=================>............] - ETA: 1s - loss: 0.0066 - mean_absolute_error: 0.0575"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 975/1534 [==================>...........] - ETA: 1s - loss: 0.0067 - mean_absolute_error: 0.0577"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 990/1534 [==================>...........] - ETA: 1s - loss: 0.0067 - mean_absolute_error: 0.0578"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1006/1534 [==================>...........] - ETA: 1s - loss: 0.0067 - mean_absolute_error: 0.0578"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1021/1534 [==================>...........] - ETA: 1s - loss: 0.0067 - mean_absolute_error: 0.0578"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1036/1534 [===================>..........] - ETA: 1s - loss: 0.0067 - mean_absolute_error: 0.0578"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1051/1534 [===================>..........] - ETA: 1s - loss: 0.0067 - mean_absolute_error: 0.0577"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1067/1534 [===================>..........] - ETA: 1s - loss: 0.0067 - mean_absolute_error: 0.0578"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1082/1534 [====================>.........] - ETA: 1s - loss: 0.0067 - mean_absolute_error: 0.0578"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1097/1534 [====================>.........] - ETA: 1s - loss: 0.0067 - mean_absolute_error: 0.0578"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1112/1534 [====================>.........] - ETA: 1s - loss: 0.0067 - mean_absolute_error: 0.0577"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1127/1534 [=====================>........] - ETA: 1s - loss: 0.0067 - mean_absolute_error: 0.0578"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1143/1534 [=====================>........] - ETA: 1s - loss: 0.0067 - mean_absolute_error: 0.0578"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1158/1534 [=====================>........] - ETA: 1s - loss: 0.0067 - mean_absolute_error: 0.0578"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1173/1534 [=====================>........] - ETA: 1s - loss: 0.0067 - mean_absolute_error: 0.0578"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1188/1534 [======================>.......] - ETA: 1s - loss: 0.0067 - mean_absolute_error: 0.0578"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1203/1534 [======================>.......] - ETA: 1s - loss: 0.0067 - mean_absolute_error: 0.0578"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1219/1534 [======================>.......] - ETA: 1s - loss: 0.0067 - mean_absolute_error: 0.0577"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1234/1534 [=======================>......] - ETA: 1s - loss: 0.0067 - mean_absolute_error: 0.0578"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1249/1534 [=======================>......] - ETA: 0s - loss: 0.0067 - mean_absolute_error: 0.0578"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1264/1534 [=======================>......] - ETA: 0s - loss: 0.0067 - mean_absolute_error: 0.0578"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1279/1534 [========================>.....] - ETA: 0s - loss: 0.0066 - mean_absolute_error: 0.0577"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1295/1534 [========================>.....] - ETA: 0s - loss: 0.0066 - mean_absolute_error: 0.0577"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1311/1534 [========================>.....] - ETA: 0s - loss: 0.0066 - mean_absolute_error: 0.0577"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1326/1534 [========================>.....] - ETA: 0s - loss: 0.0066 - mean_absolute_error: 0.0577"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1342/1534 [=========================>....] - ETA: 0s - loss: 0.0066 - mean_absolute_error: 0.0577"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1358/1534 [=========================>....] - ETA: 0s - loss: 0.0066 - mean_absolute_error: 0.0576"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1373/1534 [=========================>....] - ETA: 0s - loss: 0.0066 - mean_absolute_error: 0.0577"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1388/1534 [==========================>...] - ETA: 0s - loss: 0.0066 - mean_absolute_error: 0.0577"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1404/1534 [==========================>...] - ETA: 0s - loss: 0.0066 - mean_absolute_error: 0.0576"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1420/1534 [==========================>...] - ETA: 0s - loss: 0.0066 - mean_absolute_error: 0.0577"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1436/1534 [===========================>..] - ETA: 0s - loss: 0.0066 - mean_absolute_error: 0.0576"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1452/1534 [===========================>..] - ETA: 0s - loss: 0.0066 - mean_absolute_error: 0.0577"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1467/1534 [===========================>..] - ETA: 0s - loss: 0.0066 - mean_absolute_error: 0.0577"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1482/1534 [===========================>..] - ETA: 0s - loss: 0.0066 - mean_absolute_error: 0.0577"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1498/1534 [============================>.] - ETA: 0s - loss: 0.0066 - mean_absolute_error: 0.0576"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1513/1534 [============================>.] - ETA: 0s - loss: 0.0066 - mean_absolute_error: 0.0576"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1529/1534 [============================>.] - ETA: 0s - loss: 0.0066 - mean_absolute_error: 0.0576"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1534/1534 [==============================] - 6s 4ms/step - loss: 0.0066 - mean_absolute_error: 0.0576 - val_loss: 0.0065 - val_mean_absolute_error: 0.0575\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 12/20\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "   1/1534 [..............................] - ETA: 42s - loss: 0.0043 - mean_absolute_error: 0.0539"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  16/1534 [..............................] - ETA: 5s - loss: 0.0061 - mean_absolute_error: 0.0552 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  31/1534 [..............................] - ETA: 5s - loss: 0.0057 - mean_absolute_error: 0.0546"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  47/1534 [..............................] - ETA: 5s - loss: 0.0063 - mean_absolute_error: 0.0563"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  62/1534 [>.............................] - ETA: 4s - loss: 0.0065 - mean_absolute_error: 0.0568"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  77/1534 [>.............................] - ETA: 4s - loss: 0.0067 - mean_absolute_error: 0.0570"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  92/1534 [>.............................] - ETA: 4s - loss: 0.0068 - mean_absolute_error: 0.0578"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 107/1534 [=>............................] - ETA: 4s - loss: 0.0068 - mean_absolute_error: 0.0585"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 122/1534 [=>............................] - ETA: 4s - loss: 0.0068 - mean_absolute_error: 0.0585"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 137/1534 [=>............................] - ETA: 4s - loss: 0.0069 - mean_absolute_error: 0.0586"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 152/1534 [=>............................] - ETA: 4s - loss: 0.0070 - mean_absolute_error: 0.0586"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 167/1534 [==>...........................] - ETA: 4s - loss: 0.0069 - mean_absolute_error: 0.0583"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 182/1534 [==>...........................] - ETA: 4s - loss: 0.0069 - mean_absolute_error: 0.0582"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 198/1534 [==>...........................] - ETA: 4s - loss: 0.0068 - mean_absolute_error: 0.0578"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 214/1534 [===>..........................] - ETA: 4s - loss: 0.0067 - mean_absolute_error: 0.0575"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 229/1534 [===>..........................] - ETA: 4s - loss: 0.0067 - mean_absolute_error: 0.0571"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 244/1534 [===>..........................] - ETA: 4s - loss: 0.0066 - mean_absolute_error: 0.0571"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 259/1534 [====>.........................] - ETA: 4s - loss: 0.0066 - mean_absolute_error: 0.0571"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 274/1534 [====>.........................] - ETA: 4s - loss: 0.0066 - mean_absolute_error: 0.0574"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 289/1534 [====>.........................] - ETA: 4s - loss: 0.0066 - mean_absolute_error: 0.0573"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 305/1534 [====>.........................] - ETA: 4s - loss: 0.0067 - mean_absolute_error: 0.0574"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 320/1534 [=====>........................] - ETA: 4s - loss: 0.0067 - mean_absolute_error: 0.0575"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 336/1534 [=====>........................] - ETA: 4s - loss: 0.0067 - mean_absolute_error: 0.0574"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 351/1534 [=====>........................] - ETA: 4s - loss: 0.0067 - mean_absolute_error: 0.0576"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 366/1534 [======>.......................] - ETA: 3s - loss: 0.0067 - mean_absolute_error: 0.0577"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 381/1534 [======>.......................] - ETA: 3s - loss: 0.0067 - mean_absolute_error: 0.0577"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 396/1534 [======>.......................] - ETA: 3s - loss: 0.0067 - mean_absolute_error: 0.0578"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 412/1534 [=======>......................] - ETA: 3s - loss: 0.0067 - mean_absolute_error: 0.0577"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 428/1534 [=======>......................] - ETA: 3s - loss: 0.0067 - mean_absolute_error: 0.0577"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 443/1534 [=======>......................] - ETA: 3s - loss: 0.0067 - mean_absolute_error: 0.0577"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 459/1534 [=======>......................] - ETA: 3s - loss: 0.0067 - mean_absolute_error: 0.0578"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 475/1534 [========>.....................] - ETA: 3s - loss: 0.0067 - mean_absolute_error: 0.0577"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 491/1534 [========>.....................] - ETA: 3s - loss: 0.0067 - mean_absolute_error: 0.0577"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 507/1534 [========>.....................] - ETA: 3s - loss: 0.0067 - mean_absolute_error: 0.0577"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 522/1534 [=========>....................] - ETA: 3s - loss: 0.0066 - mean_absolute_error: 0.0575"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 537/1534 [=========>....................] - ETA: 3s - loss: 0.0066 - mean_absolute_error: 0.0574"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 553/1534 [=========>....................] - ETA: 3s - loss: 0.0066 - mean_absolute_error: 0.0574"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 568/1534 [==========>...................] - ETA: 3s - loss: 0.0066 - mean_absolute_error: 0.0573"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 583/1534 [==========>...................] - ETA: 3s - loss: 0.0066 - mean_absolute_error: 0.0573"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 599/1534 [==========>...................] - ETA: 3s - loss: 0.0066 - mean_absolute_error: 0.0573"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 614/1534 [===========>..................] - ETA: 3s - loss: 0.0066 - mean_absolute_error: 0.0573"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 629/1534 [===========>..................] - ETA: 3s - loss: 0.0065 - mean_absolute_error: 0.0572"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 645/1534 [===========>..................] - ETA: 2s - loss: 0.0065 - mean_absolute_error: 0.0572"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 660/1534 [===========>..................] - ETA: 2s - loss: 0.0065 - mean_absolute_error: 0.0572"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 675/1534 [============>.................] - ETA: 2s - loss: 0.0065 - mean_absolute_error: 0.0573"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 690/1534 [============>.................] - ETA: 2s - loss: 0.0065 - mean_absolute_error: 0.0572"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 705/1534 [============>.................] - ETA: 2s - loss: 0.0066 - mean_absolute_error: 0.0573"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 720/1534 [=============>................] - ETA: 2s - loss: 0.0066 - mean_absolute_error: 0.0573"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 735/1534 [=============>................] - ETA: 2s - loss: 0.0066 - mean_absolute_error: 0.0573"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 751/1534 [=============>................] - ETA: 2s - loss: 0.0066 - mean_absolute_error: 0.0574"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 766/1534 [=============>................] - ETA: 2s - loss: 0.0066 - mean_absolute_error: 0.0574"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 781/1534 [==============>...............] - ETA: 2s - loss: 0.0066 - mean_absolute_error: 0.0575"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 796/1534 [==============>...............] - ETA: 2s - loss: 0.0066 - mean_absolute_error: 0.0575"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 811/1534 [==============>...............] - ETA: 2s - loss: 0.0066 - mean_absolute_error: 0.0575"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 827/1534 [===============>..............] - ETA: 2s - loss: 0.0066 - mean_absolute_error: 0.0574"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 842/1534 [===============>..............] - ETA: 2s - loss: 0.0066 - mean_absolute_error: 0.0574"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 857/1534 [===============>..............] - ETA: 2s - loss: 0.0066 - mean_absolute_error: 0.0574"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 872/1534 [================>.............] - ETA: 2s - loss: 0.0066 - mean_absolute_error: 0.0573"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 887/1534 [================>.............] - ETA: 2s - loss: 0.0066 - mean_absolute_error: 0.0573"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 902/1534 [================>.............] - ETA: 2s - loss: 0.0066 - mean_absolute_error: 0.0574"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 917/1534 [================>.............] - ETA: 2s - loss: 0.0066 - mean_absolute_error: 0.0574"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 932/1534 [=================>............] - ETA: 2s - loss: 0.0066 - mean_absolute_error: 0.0573"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 947/1534 [=================>............] - ETA: 1s - loss: 0.0066 - mean_absolute_error: 0.0574"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 962/1534 [=================>............] - ETA: 1s - loss: 0.0066 - mean_absolute_error: 0.0574"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 977/1534 [==================>...........] - ETA: 1s - loss: 0.0066 - mean_absolute_error: 0.0575"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 992/1534 [==================>...........] - ETA: 1s - loss: 0.0067 - mean_absolute_error: 0.0576"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1007/1534 [==================>...........] - ETA: 1s - loss: 0.0067 - mean_absolute_error: 0.0576"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1022/1534 [==================>...........] - ETA: 1s - loss: 0.0067 - mean_absolute_error: 0.0577"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1037/1534 [===================>..........] - ETA: 1s - loss: 0.0067 - mean_absolute_error: 0.0576"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1053/1534 [===================>..........] - ETA: 1s - loss: 0.0067 - mean_absolute_error: 0.0576"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1068/1534 [===================>..........] - ETA: 1s - loss: 0.0067 - mean_absolute_error: 0.0576"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1084/1534 [====================>.........] - ETA: 1s - loss: 0.0067 - mean_absolute_error: 0.0576"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1099/1534 [====================>.........] - ETA: 1s - loss: 0.0066 - mean_absolute_error: 0.0575"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1115/1534 [====================>.........] - ETA: 1s - loss: 0.0066 - mean_absolute_error: 0.0576"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1131/1534 [=====================>........] - ETA: 1s - loss: 0.0066 - mean_absolute_error: 0.0576"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1146/1534 [=====================>........] - ETA: 1s - loss: 0.0066 - mean_absolute_error: 0.0576"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1161/1534 [=====================>........] - ETA: 1s - loss: 0.0067 - mean_absolute_error: 0.0576"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1176/1534 [=====================>........] - ETA: 1s - loss: 0.0066 - mean_absolute_error: 0.0576"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1191/1534 [======================>.......] - ETA: 1s - loss: 0.0067 - mean_absolute_error: 0.0576"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1206/1534 [======================>.......] - ETA: 1s - loss: 0.0066 - mean_absolute_error: 0.0576"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1222/1534 [======================>.......] - ETA: 1s - loss: 0.0066 - mean_absolute_error: 0.0575"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1237/1534 [=======================>......] - ETA: 0s - loss: 0.0066 - mean_absolute_error: 0.0575"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1252/1534 [=======================>......] - ETA: 0s - loss: 0.0066 - mean_absolute_error: 0.0575"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1267/1534 [=======================>......] - ETA: 0s - loss: 0.0066 - mean_absolute_error: 0.0575"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1282/1534 [========================>.....] - ETA: 0s - loss: 0.0066 - mean_absolute_error: 0.0574"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1297/1534 [========================>.....] - ETA: 0s - loss: 0.0066 - mean_absolute_error: 0.0574"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1313/1534 [========================>.....] - ETA: 0s - loss: 0.0066 - mean_absolute_error: 0.0573"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1328/1534 [========================>.....] - ETA: 0s - loss: 0.0066 - mean_absolute_error: 0.0573"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1343/1534 [=========================>....] - ETA: 0s - loss: 0.0066 - mean_absolute_error: 0.0573"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1358/1534 [=========================>....] - ETA: 0s - loss: 0.0066 - mean_absolute_error: 0.0574"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1373/1534 [=========================>....] - ETA: 0s - loss: 0.0066 - mean_absolute_error: 0.0573"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1389/1534 [==========================>...] - ETA: 0s - loss: 0.0066 - mean_absolute_error: 0.0573"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1404/1534 [==========================>...] - ETA: 0s - loss: 0.0066 - mean_absolute_error: 0.0574"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1420/1534 [==========================>...] - ETA: 0s - loss: 0.0066 - mean_absolute_error: 0.0574"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1436/1534 [===========================>..] - ETA: 0s - loss: 0.0066 - mean_absolute_error: 0.0574"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1452/1534 [===========================>..] - ETA: 0s - loss: 0.0066 - mean_absolute_error: 0.0574"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1467/1534 [===========================>..] - ETA: 0s - loss: 0.0066 - mean_absolute_error: 0.0574"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1482/1534 [===========================>..] - ETA: 0s - loss: 0.0066 - mean_absolute_error: 0.0574"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1497/1534 [============================>.] - ETA: 0s - loss: 0.0066 - mean_absolute_error: 0.0574"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1512/1534 [============================>.] - ETA: 0s - loss: 0.0066 - mean_absolute_error: 0.0573"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1528/1534 [============================>.] - ETA: 0s - loss: 0.0066 - mean_absolute_error: 0.0573"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1534/1534 [==============================] - 6s 4ms/step - loss: 0.0066 - mean_absolute_error: 0.0574 - val_loss: 0.0067 - val_mean_absolute_error: 0.0593\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 13/20\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "   1/1534 [..............................] - ETA: 45s - loss: 0.0080 - mean_absolute_error: 0.0676"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  15/1534 [..............................] - ETA: 5s - loss: 0.0060 - mean_absolute_error: 0.0558 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  30/1534 [..............................] - ETA: 5s - loss: 0.0055 - mean_absolute_error: 0.0542"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  46/1534 [..............................] - ETA: 5s - loss: 0.0063 - mean_absolute_error: 0.0558"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  62/1534 [>.............................] - ETA: 5s - loss: 0.0063 - mean_absolute_error: 0.0559"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  78/1534 [>.............................] - ETA: 4s - loss: 0.0062 - mean_absolute_error: 0.0559"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  94/1534 [>.............................] - ETA: 4s - loss: 0.0065 - mean_absolute_error: 0.0564"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 110/1534 [=>............................] - ETA: 4s - loss: 0.0065 - mean_absolute_error: 0.0562"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 126/1534 [=>............................] - ETA: 4s - loss: 0.0066 - mean_absolute_error: 0.0566"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 141/1534 [=>............................] - ETA: 4s - loss: 0.0066 - mean_absolute_error: 0.0567"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 156/1534 [==>...........................] - ETA: 4s - loss: 0.0067 - mean_absolute_error: 0.0572"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 172/1534 [==>...........................] - ETA: 4s - loss: 0.0067 - mean_absolute_error: 0.0573"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 187/1534 [==>...........................] - ETA: 4s - loss: 0.0066 - mean_absolute_error: 0.0570"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 203/1534 [==>...........................] - ETA: 4s - loss: 0.0065 - mean_absolute_error: 0.0568"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 219/1534 [===>..........................] - ETA: 4s - loss: 0.0065 - mean_absolute_error: 0.0567"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 234/1534 [===>..........................] - ETA: 4s - loss: 0.0065 - mean_absolute_error: 0.0564"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 249/1534 [===>..........................] - ETA: 4s - loss: 0.0065 - mean_absolute_error: 0.0565"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 264/1534 [====>.........................] - ETA: 4s - loss: 0.0065 - mean_absolute_error: 0.0567"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 280/1534 [====>.........................] - ETA: 4s - loss: 0.0064 - mean_absolute_error: 0.0563"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 295/1534 [====>.........................] - ETA: 4s - loss: 0.0064 - mean_absolute_error: 0.0562"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 311/1534 [=====>........................] - ETA: 4s - loss: 0.0065 - mean_absolute_error: 0.0565"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 326/1534 [=====>........................] - ETA: 4s - loss: 0.0065 - mean_absolute_error: 0.0567"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 342/1534 [=====>........................] - ETA: 3s - loss: 0.0065 - mean_absolute_error: 0.0569"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 357/1534 [=====>........................] - ETA: 3s - loss: 0.0065 - mean_absolute_error: 0.0568"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 372/1534 [======>.......................] - ETA: 3s - loss: 0.0065 - mean_absolute_error: 0.0568"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 387/1534 [======>.......................] - ETA: 3s - loss: 0.0066 - mean_absolute_error: 0.0571"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 403/1534 [======>.......................] - ETA: 3s - loss: 0.0066 - mean_absolute_error: 0.0570"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 418/1534 [=======>......................] - ETA: 3s - loss: 0.0066 - mean_absolute_error: 0.0570"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 434/1534 [=======>......................] - ETA: 3s - loss: 0.0065 - mean_absolute_error: 0.0569"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 449/1534 [=======>......................] - ETA: 3s - loss: 0.0065 - mean_absolute_error: 0.0569"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 465/1534 [========>.....................] - ETA: 3s - loss: 0.0065 - mean_absolute_error: 0.0570"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 481/1534 [========>.....................] - ETA: 3s - loss: 0.0066 - mean_absolute_error: 0.0571"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 496/1534 [========>.....................] - ETA: 3s - loss: 0.0065 - mean_absolute_error: 0.0571"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 512/1534 [=========>....................] - ETA: 3s - loss: 0.0065 - mean_absolute_error: 0.0569"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 528/1534 [=========>....................] - ETA: 3s - loss: 0.0065 - mean_absolute_error: 0.0568"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 543/1534 [=========>....................] - ETA: 3s - loss: 0.0065 - mean_absolute_error: 0.0568"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 558/1534 [=========>....................] - ETA: 3s - loss: 0.0065 - mean_absolute_error: 0.0568"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 574/1534 [==========>...................] - ETA: 3s - loss: 0.0065 - mean_absolute_error: 0.0567"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 590/1534 [==========>...................] - ETA: 3s - loss: 0.0064 - mean_absolute_error: 0.0566"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 605/1534 [==========>...................] - ETA: 3s - loss: 0.0064 - mean_absolute_error: 0.0565"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 621/1534 [===========>..................] - ETA: 3s - loss: 0.0064 - mean_absolute_error: 0.0565"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 636/1534 [===========>..................] - ETA: 2s - loss: 0.0064 - mean_absolute_error: 0.0565"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 651/1534 [===========>..................] - ETA: 2s - loss: 0.0064 - mean_absolute_error: 0.0566"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 666/1534 [============>.................] - ETA: 2s - loss: 0.0064 - mean_absolute_error: 0.0566"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 681/1534 [============>.................] - ETA: 2s - loss: 0.0064 - mean_absolute_error: 0.0566"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 697/1534 [============>.................] - ETA: 2s - loss: 0.0064 - mean_absolute_error: 0.0566"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 712/1534 [============>.................] - ETA: 2s - loss: 0.0064 - mean_absolute_error: 0.0566"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 728/1534 [=============>................] - ETA: 2s - loss: 0.0064 - mean_absolute_error: 0.0566"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 743/1534 [=============>................] - ETA: 2s - loss: 0.0065 - mean_absolute_error: 0.0567"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 758/1534 [=============>................] - ETA: 2s - loss: 0.0065 - mean_absolute_error: 0.0568"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 773/1534 [==============>...............] - ETA: 2s - loss: 0.0065 - mean_absolute_error: 0.0569"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 789/1534 [==============>...............] - ETA: 2s - loss: 0.0065 - mean_absolute_error: 0.0570"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 804/1534 [==============>...............] - ETA: 2s - loss: 0.0065 - mean_absolute_error: 0.0569"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 819/1534 [===============>..............] - ETA: 2s - loss: 0.0065 - mean_absolute_error: 0.0569"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 835/1534 [===============>..............] - ETA: 2s - loss: 0.0065 - mean_absolute_error: 0.0569"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 851/1534 [===============>..............] - ETA: 2s - loss: 0.0065 - mean_absolute_error: 0.0568"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 866/1534 [===============>..............] - ETA: 2s - loss: 0.0065 - mean_absolute_error: 0.0568"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 882/1534 [================>.............] - ETA: 2s - loss: 0.0065 - mean_absolute_error: 0.0568"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 898/1534 [================>.............] - ETA: 2s - loss: 0.0065 - mean_absolute_error: 0.0569"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 914/1534 [================>.............] - ETA: 2s - loss: 0.0065 - mean_absolute_error: 0.0569"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 930/1534 [=================>............] - ETA: 2s - loss: 0.0065 - mean_absolute_error: 0.0569"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 946/1534 [=================>............] - ETA: 1s - loss: 0.0065 - mean_absolute_error: 0.0569"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 962/1534 [=================>............] - ETA: 1s - loss: 0.0065 - mean_absolute_error: 0.0570"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 978/1534 [==================>...........] - ETA: 1s - loss: 0.0066 - mean_absolute_error: 0.0570"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 994/1534 [==================>...........] - ETA: 1s - loss: 0.0066 - mean_absolute_error: 0.0571"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1010/1534 [==================>...........] - ETA: 1s - loss: 0.0066 - mean_absolute_error: 0.0572"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1026/1534 [===================>..........] - ETA: 1s - loss: 0.0066 - mean_absolute_error: 0.0572"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1042/1534 [===================>..........] - ETA: 1s - loss: 0.0066 - mean_absolute_error: 0.0572"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1057/1534 [===================>..........] - ETA: 1s - loss: 0.0066 - mean_absolute_error: 0.0572"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1072/1534 [===================>..........] - ETA: 1s - loss: 0.0066 - mean_absolute_error: 0.0572"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1087/1534 [====================>.........] - ETA: 1s - loss: 0.0066 - mean_absolute_error: 0.0572"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1103/1534 [====================>.........] - ETA: 1s - loss: 0.0066 - mean_absolute_error: 0.0571"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1118/1534 [====================>.........] - ETA: 1s - loss: 0.0065 - mean_absolute_error: 0.0571"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1134/1534 [=====================>........] - ETA: 1s - loss: 0.0065 - mean_absolute_error: 0.0572"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1150/1534 [=====================>........] - ETA: 1s - loss: 0.0066 - mean_absolute_error: 0.0572"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1166/1534 [=====================>........] - ETA: 1s - loss: 0.0066 - mean_absolute_error: 0.0572"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1181/1534 [======================>.......] - ETA: 1s - loss: 0.0066 - mean_absolute_error: 0.0572"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1197/1534 [======================>.......] - ETA: 1s - loss: 0.0066 - mean_absolute_error: 0.0572"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1212/1534 [======================>.......] - ETA: 1s - loss: 0.0066 - mean_absolute_error: 0.0572"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1228/1534 [=======================>......] - ETA: 1s - loss: 0.0066 - mean_absolute_error: 0.0572"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1244/1534 [=======================>......] - ETA: 0s - loss: 0.0066 - mean_absolute_error: 0.0572"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1260/1534 [=======================>......] - ETA: 0s - loss: 0.0066 - mean_absolute_error: 0.0572"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1276/1534 [=======================>......] - ETA: 0s - loss: 0.0065 - mean_absolute_error: 0.0571"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1292/1534 [========================>.....] - ETA: 0s - loss: 0.0065 - mean_absolute_error: 0.0571"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1307/1534 [========================>.....] - ETA: 0s - loss: 0.0065 - mean_absolute_error: 0.0570"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1322/1534 [========================>.....] - ETA: 0s - loss: 0.0065 - mean_absolute_error: 0.0570"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1337/1534 [=========================>....] - ETA: 0s - loss: 0.0065 - mean_absolute_error: 0.0570"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1352/1534 [=========================>....] - ETA: 0s - loss: 0.0065 - mean_absolute_error: 0.0569"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1367/1534 [=========================>....] - ETA: 0s - loss: 0.0065 - mean_absolute_error: 0.0570"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1382/1534 [==========================>...] - ETA: 0s - loss: 0.0065 - mean_absolute_error: 0.0570"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1398/1534 [==========================>...] - ETA: 0s - loss: 0.0065 - mean_absolute_error: 0.0569"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1413/1534 [==========================>...] - ETA: 0s - loss: 0.0065 - mean_absolute_error: 0.0570"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1429/1534 [==========================>...] - ETA: 0s - loss: 0.0065 - mean_absolute_error: 0.0570"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1445/1534 [===========================>..] - ETA: 0s - loss: 0.0065 - mean_absolute_error: 0.0570"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1461/1534 [===========================>..] - ETA: 0s - loss: 0.0065 - mean_absolute_error: 0.0570"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1477/1534 [===========================>..] - ETA: 0s - loss: 0.0065 - mean_absolute_error: 0.0569"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1493/1534 [============================>.] - ETA: 0s - loss: 0.0065 - mean_absolute_error: 0.0569"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1509/1534 [============================>.] - ETA: 0s - loss: 0.0065 - mean_absolute_error: 0.0568"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1524/1534 [============================>.] - ETA: 0s - loss: 0.0065 - mean_absolute_error: 0.0569"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "1534/1534 [==============================] - 6s 4ms/step - loss: 0.0065 - mean_absolute_error: 0.0569 - val_loss: 0.0066 - val_mean_absolute_error: 0.0566\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/439 [..............................] - ETA: 32s - loss: 0.0027 - mean_absolute_error: 0.0407"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 19/439 [>.............................] - ETA: 1s - loss: 0.0062 - mean_absolute_error: 0.0532 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 38/439 [=>............................] - ETA: 1s - loss: 0.0067 - mean_absolute_error: 0.0557"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 59/439 [===>..........................] - ETA: 0s - loss: 0.0067 - mean_absolute_error: 0.0565"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 79/439 [====>.........................] - ETA: 0s - loss: 0.0070 - mean_absolute_error: 0.0571"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    },
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     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
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     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "241/439 [===============>..............] - ETA: 0s - loss: 0.0066 - mean_absolute_error: 0.0569"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "261/439 [================>.............] - ETA: 0s - loss: 0.0066 - mean_absolute_error: 0.0566"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "280/439 [==================>...........] - ETA: 0s - loss: 0.0067 - mean_absolute_error: 0.0568"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "439/439 [==============================] - ETA: 0s - loss: 0.0066 - mean_absolute_error: 0.0566"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "439/439 [==============================] - 1s 3ms/step - loss: 0.0066 - mean_absolute_error: 0.0566\n"
     ]
    }
   ],
   "source": [
    "dense = tf.keras.Sequential([\n",
    "    tf.keras.layers.Dense(units=64, activation='relu'),\n",
    "    tf.keras.layers.Dense(units=64, activation='relu'),\n",
    "    tf.keras.layers.Dense(units=1)\n",
    "])\n",
    "\n",
    "history = compile_and_fit(dense, single_step_window)\n",
    "\n",
    "val_performance['Dense'] = dense.evaluate(single_step_window.val)\n",
    "performance['Dense'] = dense.evaluate(single_step_window.test, verbose=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "j5dv_whJdswH"
   },
   "source": [
    "### 다중 스텝 밀집\n",
    "\n",
    "단일 타임스텝 모델에는 입력의 현재 값에 대한 컨텍스트가 없습니다. 시간에 따라 입력 특성이 어떻게 변하는지 볼 수 없습니다. 이 문제를 해결하려면 모델이 예측을 수행할 때 여러 타임스텝에 액세스해야 합니다.\n",
    "\n",
    "![Three time steps are used for each prediction.](images/conv_window.png)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Zac-ti8agbJ7"
   },
   "source": [
    "`baseline` , `linear` 및 `dense` 모델은 각 타임스텝을 독립적으로 처리했습니다. 여기서 모델은 단일 출력을 생성하기 위해 여러 타임스텝을 입력으로 사용합니다.\n",
    "\n",
    "3시간의 입력과 1시간의 레이블 배치를 생성하는 `WindowGenerator`를 만듭니다."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "gtN4BwZ37niR"
   },
   "source": [
    "`Window`의 `shift` 매개변수는 두 창의 끝에 상대적입니다.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:57:26.459948Z",
     "iopub.status.busy": "2022-12-14T22:57:26.459346Z",
     "iopub.status.idle": "2022-12-14T22:57:26.466238Z",
     "shell.execute_reply": "2022-12-14T22:57:26.465344Z"
    },
    "id": "lBh0j5djUKY2"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Total window size: 4\n",
       "Input indices: [0 1 2]\n",
       "Label indices: [3]\n",
       "Label column name(s): ['T (degC)']"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "CONV_WIDTH = 3\n",
    "conv_window = WindowGenerator(\n",
    "    input_width=CONV_WIDTH,\n",
    "    label_width=1,\n",
    "    shift=1,\n",
    "    label_columns=['T (degC)'])\n",
    "\n",
    "conv_window"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:57:26.469939Z",
     "iopub.status.busy": "2022-12-14T22:57:26.469376Z",
     "iopub.status.idle": "2022-12-14T22:57:27.049764Z",
     "shell.execute_reply": "2022-12-14T22:57:27.048731Z"
    },
    "id": "dCQ5gvs68Xkd"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Given 3 hours of inputs, predict 1 hour into the future.')"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x800 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "conv_window.plot()\n",
    "plt.title(\"Given 3 hours of inputs, predict 1 hour into the future.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "We0HdMxKeqB_"
   },
   "source": [
    "`tf.keras.layers.Flatten`을 모델의 첫 번째 레이어로 추가하여 다중 입력 스텝 창에서 `dense` 모델을 훈련할 수 있습니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:57:27.054565Z",
     "iopub.status.busy": "2022-12-14T22:57:27.053920Z",
     "iopub.status.idle": "2022-12-14T22:57:27.066429Z",
     "shell.execute_reply": "2022-12-14T22:57:27.065766Z"
    },
    "id": "oNQnUOkOnC1G"
   },
   "outputs": [],
   "source": [
    "multi_step_dense = tf.keras.Sequential([\n",
    "    # Shape: (time, features) => (time*features)\n",
    "    tf.keras.layers.Flatten(),\n",
    "    tf.keras.layers.Dense(units=32, activation='relu'),\n",
    "    tf.keras.layers.Dense(units=32, activation='relu'),\n",
    "    tf.keras.layers.Dense(units=1),\n",
    "    # Add back the time dimension.\n",
    "    # Shape: (outputs) => (1, outputs)\n",
    "    tf.keras.layers.Reshape([1, -1]),\n",
    "])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:57:27.070354Z",
     "iopub.status.busy": "2022-12-14T22:57:27.069644Z",
     "iopub.status.idle": "2022-12-14T22:57:27.133773Z",
     "shell.execute_reply": "2022-12-14T22:57:27.132797Z"
    },
    "id": "cayD74luo4Vq"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Input shape: (32, 3, 19)\n",
      "Output shape: (32, 1, 1)\n"
     ]
    }
   ],
   "source": [
    "print('Input shape:', conv_window.example[0].shape)\n",
    "print('Output shape:', multi_step_dense(conv_window.example[0]).shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:57:27.137797Z",
     "iopub.status.busy": "2022-12-14T22:57:27.137076Z",
     "iopub.status.idle": "2022-12-14T22:58:04.787715Z",
     "shell.execute_reply": "2022-12-14T22:58:04.786824Z"
    },
    "id": "fu91yEbRo9-J"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/438 [..............................] - ETA: 32s - loss: 0.0074 - mean_absolute_error: 0.0643"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 24/438 [>.............................] - ETA: 0s - loss: 0.0072 - mean_absolute_error: 0.0635 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 50/438 [==>...........................] - ETA: 0s - loss: 0.0069 - mean_absolute_error: 0.0611"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 77/438 [====>.........................] - ETA: 0s - loss: 0.0067 - mean_absolute_error: 0.0611"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "103/438 [======>.......................] - ETA: 0s - loss: 0.0067 - mean_absolute_error: 0.0611"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "129/438 [=======>......................] - ETA: 0s - loss: 0.0067 - mean_absolute_error: 0.0606"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "156/438 [=========>....................] - ETA: 0s - loss: 0.0070 - mean_absolute_error: 0.0614"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "184/438 [===========>..................] - ETA: 0s - loss: 0.0070 - mean_absolute_error: 0.0612"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "209/438 [=============>................] - ETA: 0s - loss: 0.0071 - mean_absolute_error: 0.0616"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "234/438 [===============>..............] - ETA: 0s - loss: 0.0070 - mean_absolute_error: 0.0612"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "260/438 [================>.............] - ETA: 0s - loss: 0.0071 - mean_absolute_error: 0.0613"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "285/438 [==================>...........] - ETA: 0s - loss: 0.0072 - mean_absolute_error: 0.0616"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "311/438 [====================>.........] - ETA: 0s - loss: 0.0071 - mean_absolute_error: 0.0613"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "337/438 [======================>.......] - ETA: 0s - loss: 0.0071 - mean_absolute_error: 0.0614"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "362/438 [=======================>......] - ETA: 0s - loss: 0.0071 - mean_absolute_error: 0.0611"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "388/438 [=========================>....] - ETA: 0s - loss: 0.0072 - mean_absolute_error: 0.0613"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "414/438 [===========================>..] - ETA: 0s - loss: 0.0072 - mean_absolute_error: 0.0614"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "438/438 [==============================] - 1s 2ms/step - loss: 0.0072 - mean_absolute_error: 0.0614\n"
     ]
    }
   ],
   "source": [
    "history = compile_and_fit(multi_step_dense, conv_window)\n",
    "\n",
    "IPython.display.clear_output()\n",
    "val_performance['Multi step dense'] = multi_step_dense.evaluate(conv_window.val)\n",
    "performance['Multi step dense'] = multi_step_dense.evaluate(conv_window.test, verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:58:04.792197Z",
     "iopub.status.busy": "2022-12-14T22:58:04.791485Z",
     "iopub.status.idle": "2022-12-14T22:58:05.265239Z",
     "shell.execute_reply": "2022-12-14T22:58:05.264508Z"
    },
    "id": "tnqdXYT6pkEh"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x800 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "conv_window.plot(multi_step_dense)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "gWfrsP8mq8lV"
   },
   "source": [
    "이 접근법의 주된 단점은 결과적인 모델이 정확히 이 형상의 입력 창에서만 실행될 수 있다는 것입니다. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:58:05.269473Z",
     "iopub.status.busy": "2022-12-14T22:58:05.268904Z",
     "iopub.status.idle": "2022-12-14T22:58:05.303601Z",
     "shell.execute_reply": "2022-12-14T22:58:05.302693Z"
    },
    "id": "j-q6tz5Yq8Jk"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Input shape: (32, 24, 19)\n",
      "\n",
      "ValueError:Exception encountered when calling layer 'sequential_2' (type Sequential).\n",
      "\n",
      "Input 0 of layer \"dense_4\" is incompatible with the layer: expected axis -1 of input shape to have value 57, but received input with shape (32, 456)\n",
      "\n",
      "Call arguments received by layer 'sequential_2' (type Sequential):\n",
      "  • inputs=tf.Tensor(shape=(32, 24, 19), dtype=float32)\n",
      "  • training=None\n",
      "  • mask=None\n"
     ]
    }
   ],
   "source": [
    "print('Input shape:', wide_window.example[0].shape)\n",
    "try:\n",
    "  print('Output shape:', multi_step_dense(wide_window.example[0]).shape)\n",
    "except Exception as e:\n",
    "  print(f'\\n{type(e).__name__}:{e}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "bvvajm3ip_8V"
   },
   "source": [
    "다음 섹션의 컨볼루셔널 모델은 이 문제를 해결합니다."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "CrpU6gwSJome"
   },
   "source": [
    "### 컨볼루션 신경망\n",
    "\n",
    "컨볼루션 레이어(`tf.keras.layers.Conv1D`)도 각 예측에 대한 입력으로 여러 타임스텝을 사용합니다."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "cdLBwoaHmsWb"
   },
   "source": [
    "다음은 컨볼루션으로 다시 작성한 `multi_step_dense`와 **동일한** 모델입니다.\n",
    "\n",
    "다음 변경 사항에 주목하세요.\n",
    "\n",
    "- `tf.keras.layers.Flatten`과 첫 번째 `tf.keras.layers.Dense`는 `tf.keras.layers.Conv1D`로 대체됩니다.\n",
    "- 컨볼루션이 출력에서 시간 축을 유지하므로 `tf.keras.layers.Reshape`는 이 더 이상 필요하지 않습니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:58:05.307237Z",
     "iopub.status.busy": "2022-12-14T22:58:05.306674Z",
     "iopub.status.idle": "2022-12-14T22:58:05.315903Z",
     "shell.execute_reply": "2022-12-14T22:58:05.315296Z"
    },
    "id": "5azaMBj4ac9t"
   },
   "outputs": [],
   "source": [
    "conv_model = tf.keras.Sequential([\n",
    "    tf.keras.layers.Conv1D(filters=32,\n",
    "                           kernel_size=(CONV_WIDTH,),\n",
    "                           activation='relu'),\n",
    "    tf.keras.layers.Dense(units=32, activation='relu'),\n",
    "    tf.keras.layers.Dense(units=1),\n",
    "])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "ftaH6B5ECRiK"
   },
   "source": [
    "예제 배치에서 실행하여 모델이 예상한 형상으로 출력을 생성하는지 확인합니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:58:05.319448Z",
     "iopub.status.busy": "2022-12-14T22:58:05.318918Z",
     "iopub.status.idle": "2022-12-14T22:58:05.367988Z",
     "shell.execute_reply": "2022-12-14T22:58:05.367189Z"
    },
    "id": "5YNgt1-e98lH"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Conv model on `conv_window`\n",
      "Input shape: (32, 3, 19)\n",
      "Output shape: (32, 1, 1)\n"
     ]
    }
   ],
   "source": [
    "print(\"Conv model on `conv_window`\")\n",
    "print('Input shape:', conv_window.example[0].shape)\n",
    "print('Output shape:', conv_model(conv_window.example[0]).shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "5m4kC-jGCY3x"
   },
   "source": [
    "`conv_window`에서 훈련하고 평가하면 `multi_step_dense` 모델과 유사한 성능을 제공해야 합니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:58:05.371576Z",
     "iopub.status.busy": "2022-12-14T22:58:05.370912Z",
     "iopub.status.idle": "2022-12-14T22:59:38.773563Z",
     "shell.execute_reply": "2022-12-14T22:59:38.772693Z"
    },
    "id": "QDVWdm4paUW7"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/438 [..............................] - ETA: 32s - loss: 0.0062 - mean_absolute_error: 0.0545"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 20/438 [>.............................] - ETA: 1s - loss: 0.0052 - mean_absolute_error: 0.0526 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 40/438 [=>............................] - ETA: 1s - loss: 0.0055 - mean_absolute_error: 0.0529"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 60/438 [===>..........................] - ETA: 0s - loss: 0.0058 - mean_absolute_error: 0.0541"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 79/438 [====>.........................] - ETA: 0s - loss: 0.0056 - mean_absolute_error: 0.0536"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 99/438 [=====>........................] - ETA: 0s - loss: 0.0056 - mean_absolute_error: 0.0534"
     ]
    },
    {
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     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
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     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
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     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
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     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
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     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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    },
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "415/438 [===========================>..] - ETA: 0s - loss: 0.0062 - mean_absolute_error: 0.0544"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "435/438 [============================>.] - ETA: 0s - loss: 0.0062 - mean_absolute_error: 0.0543"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "438/438 [==============================] - 1s 3ms/step - loss: 0.0062 - mean_absolute_error: 0.0544\n"
     ]
    }
   ],
   "source": [
    "history = compile_and_fit(conv_model, conv_window)\n",
    "\n",
    "IPython.display.clear_output()\n",
    "val_performance['Conv'] = conv_model.evaluate(conv_window.val)\n",
    "performance['Conv'] = conv_model.evaluate(conv_window.test, verbose=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "sYRipDeXs0Kr"
   },
   "source": [
    "이 `conv_model`과 `multi_step_dense` 모델의 차이점은 `conv_model`은 모든 길이의 입력에서 실행될 수 있다는 것입니다. 컨볼루셔널 레이어는 입력의 슬라이딩 창에 적용됩니다.\n",
    "\n",
    "![시퀀스에서 컨볼루션 모델 실행](images/wide_conv_window.png)\n",
    "\n",
    "더 넓은 입력에서 실행하면 더 넓은 출력이 생성됩니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:59:38.778284Z",
     "iopub.status.busy": "2022-12-14T22:59:38.777603Z",
     "iopub.status.idle": "2022-12-14T22:59:38.836067Z",
     "shell.execute_reply": "2022-12-14T22:59:38.835298Z"
    },
    "id": "hoqccxx9r5jF"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wide window\n",
      "Input shape: (32, 24, 19)\n",
      "Labels shape: (32, 24, 1)\n",
      "Output shape: (32, 22, 1)\n"
     ]
    }
   ],
   "source": [
    "print(\"Wide window\")\n",
    "print('Input shape:', wide_window.example[0].shape)\n",
    "print('Labels shape:', wide_window.example[1].shape)\n",
    "print('Output shape:', conv_model(wide_window.example[0]).shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "h_WGxtLIHhRF"
   },
   "source": [
    "출력은 입력보다 짧습니다. 훈련 또는 플롯 작업을 수행하려면 레이블과 예상의 길이가 동일해야 합니다. 따라서 레이블과 예측 길이가 일치하도록 몇 개의 추가 입력 타임스텝으로 넓은 창을 생성하는 `WindowGenerator`를 빌드합니다. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:59:38.840027Z",
     "iopub.status.busy": "2022-12-14T22:59:38.839443Z",
     "iopub.status.idle": "2022-12-14T22:59:38.845219Z",
     "shell.execute_reply": "2022-12-14T22:59:38.844551Z"
    },
    "id": "_VPvJ_VwTc0f"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Total window size: 27\n",
       "Input indices: [ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23\n",
       " 24 25]\n",
       "Label indices: [ 3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26]\n",
       "Label column name(s): ['T (degC)']"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "LABEL_WIDTH = 24\n",
    "INPUT_WIDTH = LABEL_WIDTH + (CONV_WIDTH - 1)\n",
    "wide_conv_window = WindowGenerator(\n",
    "    input_width=INPUT_WIDTH,\n",
    "    label_width=LABEL_WIDTH,\n",
    "    shift=1,\n",
    "    label_columns=['T (degC)'])\n",
    "\n",
    "wide_conv_window"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:59:38.848718Z",
     "iopub.status.busy": "2022-12-14T22:59:38.848140Z",
     "iopub.status.idle": "2022-12-14T22:59:38.990897Z",
     "shell.execute_reply": "2022-12-14T22:59:38.990062Z"
    },
    "id": "gtqlWYXeKXej"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wide conv window\n",
      "Input shape: (32, 26, 19)\n",
      "Labels shape: (32, 24, 1)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Output shape: (32, 24, 1)\n"
     ]
    }
   ],
   "source": [
    "print(\"Wide conv window\")\n",
    "print('Input shape:', wide_conv_window.example[0].shape)\n",
    "print('Labels shape:', wide_conv_window.example[1].shape)\n",
    "print('Output shape:', conv_model(wide_conv_window.example[0]).shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "yzxbbS56cSBV"
   },
   "source": [
    "이제 더 넓은 창에 모델의 예측을 플롯할 수 있습니다. 첫 번째 예측 전 3개의 입력 타임스텝에 주목하세요. 여기서 모든 예측은 이전 3개의 타임스텝에 기초합니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:59:38.994880Z",
     "iopub.status.busy": "2022-12-14T22:59:38.994159Z",
     "iopub.status.idle": "2022-12-14T22:59:39.671454Z",
     "shell.execute_reply": "2022-12-14T22:59:39.670575Z"
    },
    "id": "gR7VyL45UuEe"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x800 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "wide_conv_window.plot(conv_model)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "H4crpOcoMlSe"
   },
   "source": [
    "### 순환 신경망\n",
    "\n",
    "Recurrent Neural Network(RNN)는 시계열 데이터에 적합한 신경망 유형입니다. RNN은 시계열을 단계별로 처리하여 타임스텝 사이에서 내부 상태를 유지합니다.\n",
    "\n",
    "[RNN을 사용한 텍스트 생성](https://www.tensorflow.org/text/tutorials/text_generation) 튜토리얼 및 [Keras를 사용한 순환 신경망(RNN)](https://www.tensorflow.org/guide/keras/rnn) 가이드에서 자세히 알아볼 수 있습니다.\n",
    "\n",
    "이 튜토리얼에서는 LSTM(`tf.keras.layers.LSTM`)이라는 RNN 레이어를 사용합니다."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "vfQbHSMb1ATa"
   },
   "source": [
    "`tf.keras.layers.LSTM`와 같이 모든 keras RNN 레이어에 대한 중요한 생성자 인수는 `return_sequences` 인수입니다. 이 설정은 다음 두 가지 방법 중 하나로 레이어를 구성할 수 있습니다.\n",
    "\n",
    "1. 기본값인 `False`인 경우 레이어는 최종 타임스텝의 출력만 반환하여 단일 예측을 수행하기 전에 모델이 내부 상태를 준비할 시간을 줍니다.\n",
    "\n",
    "![lstm 워밍업 및 단일 예측](images/lstm_1_window.png)\n",
    "\n",
    "1. `True`이면 레이어가 각 입력에 대한 출력을 반환합니다. 다음과 같은 경우에 유용합니다.\n",
    "    - RNN 레이어 스태킹\n",
    "    - 여러 타임스텝에서 동시에 모델 훈련\n",
    "\n",
    "![모든 타임스텝 후에 예측하는 lstm](images/lstm_many_window.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:59:39.675954Z",
     "iopub.status.busy": "2022-12-14T22:59:39.675385Z",
     "iopub.status.idle": "2022-12-14T22:59:39.687856Z",
     "shell.execute_reply": "2022-12-14T22:59:39.687203Z"
    },
    "id": "DXKLCJy8nWNU"
   },
   "outputs": [],
   "source": [
    "lstm_model = tf.keras.models.Sequential([\n",
    "    # Shape [batch, time, features] => [batch, time, lstm_units]\n",
    "    tf.keras.layers.LSTM(32, return_sequences=True),\n",
    "    # Shape => [batch, time, features]\n",
    "    tf.keras.layers.Dense(units=1)\n",
    "])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "F124B00KZcLC"
   },
   "source": [
    "`return_sequences=True`이면 모델을 한 번에 24시간 분량 데이터에 대해 훈련할 수 있습니다.\n",
    "\n",
    "참고: 이 경우에는 모델 성능의 관점에서 기대할 것이 없습니다. 첫 번째 타임스텝에서 모델이 이전 스텝에 액세스할 수 없으므로 이전에 표시한 단순한 `linear` 및 `dense` 모델보다 더 나을 것이 없기 때문입니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:59:39.691514Z",
     "iopub.status.busy": "2022-12-14T22:59:39.690982Z",
     "iopub.status.idle": "2022-12-14T22:59:40.056174Z",
     "shell.execute_reply": "2022-12-14T22:59:40.055394Z"
    },
    "id": "eZEROCQVYV6q"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Input shape: (32, 24, 19)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Output shape: (32, 24, 1)\n"
     ]
    }
   ],
   "source": [
    "print('Input shape:', wide_window.example[0].shape)\n",
    "print('Output shape:', lstm_model(wide_window.example[0]).shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T22:59:40.059884Z",
     "iopub.status.busy": "2022-12-14T22:59:40.059308Z",
     "iopub.status.idle": "2022-12-14T23:00:47.585549Z",
     "shell.execute_reply": "2022-12-14T23:00:47.584686Z"
    },
    "id": "uvdWRl1e9WJl"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/438 [..............................] - ETA: 31s - loss: 0.0065 - mean_absolute_error: 0.0566"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 17/438 [>.............................] - ETA: 1s - loss: 0.0057 - mean_absolute_error: 0.0524 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 34/438 [=>............................] - ETA: 1s - loss: 0.0060 - mean_absolute_error: 0.0534"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 51/438 [==>...........................] - ETA: 1s - loss: 0.0059 - mean_absolute_error: 0.0527"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 68/438 [===>..........................] - ETA: 1s - loss: 0.0057 - mean_absolute_error: 0.0522"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 85/438 [====>.........................] - ETA: 1s - loss: 0.0057 - mean_absolute_error: 0.0519"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "102/438 [=====>........................] - ETA: 1s - loss: 0.0057 - mean_absolute_error: 0.0519"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "285/438 [==================>...........] - ETA: 0s - loss: 0.0056 - mean_absolute_error: 0.0517"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "387/438 [=========================>....] - ETA: 0s - loss: 0.0055 - mean_absolute_error: 0.0514"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "421/438 [===========================>..] - ETA: 0s - loss: 0.0056 - mean_absolute_error: 0.0515"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "438/438 [==============================] - 1s 3ms/step - loss: 0.0056 - mean_absolute_error: 0.0515\n"
     ]
    }
   ],
   "source": [
    "history = compile_and_fit(lstm_model, wide_window)\n",
    "\n",
    "IPython.display.clear_output()\n",
    "val_performance['LSTM'] = lstm_model.evaluate(wide_window.val)\n",
    "performance['LSTM'] = lstm_model.evaluate(wide_window.test, verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:00:47.589973Z",
     "iopub.status.busy": "2022-12-14T23:00:47.589372Z",
     "iopub.status.idle": "2022-12-14T23:00:48.053154Z",
     "shell.execute_reply": "2022-12-14T23:00:48.052408Z"
    },
    "id": "NwAOWCVgB26e"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x800 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "wide_window.plot(lstm_model)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "pYglOCKehi8F"
   },
   "source": [
    "### 성능"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "2pCk0_rwhi8H"
   },
   "source": [
    "이 데이터세트를 사용하면 일반적으로 각 모델의 성능이 이전 모델보다 약간 더 좋습니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:00:48.058117Z",
     "iopub.status.busy": "2022-12-14T23:00:48.057511Z",
     "iopub.status.idle": "2022-12-14T23:00:48.246994Z",
     "shell.execute_reply": "2022-12-14T23:00:48.246185Z"
    },
    "id": "JjEkt488hi8I"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.arange(len(performance))\n",
    "width = 0.3\n",
    "metric_name = 'mean_absolute_error'\n",
    "metric_index = lstm_model.metrics_names.index('mean_absolute_error')\n",
    "val_mae = [v[metric_index] for v in val_performance.values()]\n",
    "test_mae = [v[metric_index] for v in performance.values()]\n",
    "\n",
    "plt.ylabel('mean_absolute_error [T (degC), normalized]')\n",
    "plt.bar(x - 0.17, val_mae, width, label='Validation')\n",
    "plt.bar(x + 0.17, test_mae, width, label='Test')\n",
    "plt.xticks(ticks=x, labels=performance.keys(),\n",
    "           rotation=45)\n",
    "_ = plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:00:48.251047Z",
     "iopub.status.busy": "2022-12-14T23:00:48.250401Z",
     "iopub.status.idle": "2022-12-14T23:00:48.254388Z",
     "shell.execute_reply": "2022-12-14T23:00:48.253773Z"
    },
    "id": "cBMCpsdphi8L"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Baseline    : 0.0852\n",
      "Linear      : 0.0672\n",
      "Dense       : 0.0581\n",
      "Multi step dense: 0.0650\n",
      "Conv        : 0.0561\n",
      "LSTM        : 0.0521\n"
     ]
    }
   ],
   "source": [
    "for name, value in performance.items():\n",
    "  print(f'{name:12s}: {value[1]:0.4f}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "b5rUJ_2YMWzG"
   },
   "source": [
    "### 다중 출력 모델\n",
    "\n",
    "지금까지 모델은 모두 단일 타임스텝에 대해 단일 출력 특성 `T (degC)`를 예측했습니다.\n",
    "\n",
    "이러한 모든 모델은 간단히 출력 레이어의 단위 수를 변경하고 code0}labels(`example_labels`)에 모든 특성을 포함하도록 훈련 창을 조정하여 여러 특성을 예측하도록 변환할 수 있습니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:00:48.258127Z",
     "iopub.status.busy": "2022-12-14T23:00:48.257489Z",
     "iopub.status.idle": "2022-12-14T23:00:48.383757Z",
     "shell.execute_reply": "2022-12-14T23:00:48.382845Z"
    },
    "id": "9Gk0Z91xjOwv"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Inputs shape (batch, time, features): (32, 24, 19)\n",
      "Labels shape (batch, time, features): (32, 24, 19)\n"
     ]
    }
   ],
   "source": [
    "single_step_window = WindowGenerator(\n",
    "    # `WindowGenerator` returns all features as labels if you \n",
    "    # don't set the `label_columns` argument.\n",
    "    input_width=1, label_width=1, shift=1)\n",
    "\n",
    "wide_window = WindowGenerator(\n",
    "    input_width=24, label_width=24, shift=1)\n",
    "\n",
    "for example_inputs, example_labels in wide_window.train.take(1):\n",
    "  print(f'Inputs shape (batch, time, features): {example_inputs.shape}')\n",
    "  print(f'Labels shape (batch, time, features): {example_labels.shape}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "XmcjHfDskX1N"
   },
   "source": [
    "레이블의 `features` 축은 이제 1이 아닌 입력과 동일한 깊이를 갖습니다."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "9k7S5IHNhSNF"
   },
   "source": [
    "#### 기준\n",
    "\n",
    "여기서는 동일한 기준 모델(`Baseline`)을 사용할 수 있지만 이번에는 특정 `label_index`를 선택하는 대신 모든 특성을 반복합니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:00:48.387654Z",
     "iopub.status.busy": "2022-12-14T23:00:48.387051Z",
     "iopub.status.idle": "2022-12-14T23:00:48.401754Z",
     "shell.execute_reply": "2022-12-14T23:00:48.401071Z"
    },
    "id": "sqqB9W-pjr5i"
   },
   "outputs": [],
   "source": [
    "baseline = Baseline()\n",
    "baseline.compile(loss=tf.keras.losses.MeanSquaredError(),\n",
    "                 metrics=[tf.keras.metrics.MeanAbsoluteError()])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:00:48.405396Z",
     "iopub.status.busy": "2022-12-14T23:00:48.404785Z",
     "iopub.status.idle": "2022-12-14T23:00:49.828421Z",
     "shell.execute_reply": "2022-12-14T23:00:49.827640Z"
    },
    "id": "ltQdgaqQjQWu"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/438 [..............................] - ETA: 56s - loss: 0.0800 - mean_absolute_error: 0.1530"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 27/438 [>.............................] - ETA: 0s - loss: 0.0874 - mean_absolute_error: 0.1585 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 54/438 [==>...........................] - ETA: 0s - loss: 0.0879 - mean_absolute_error: 0.1585"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 82/438 [====>.........................] - ETA: 0s - loss: 0.0885 - mean_absolute_error: 0.1588"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "109/438 [======>.......................] - ETA: 0s - loss: 0.0891 - mean_absolute_error: 0.1596"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "136/438 [========>.....................] - ETA: 0s - loss: 0.0895 - mean_absolute_error: 0.1598"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "165/438 [==========>...................] - ETA: 0s - loss: 0.0897 - mean_absolute_error: 0.1598"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "194/438 [============>.................] - ETA: 0s - loss: 0.0895 - mean_absolute_error: 0.1597"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "222/438 [==============>...............] - ETA: 0s - loss: 0.0894 - mean_absolute_error: 0.1596"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "249/438 [================>.............] - ETA: 0s - loss: 0.0893 - mean_absolute_error: 0.1595"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "276/438 [=================>............] - ETA: 0s - loss: 0.0895 - mean_absolute_error: 0.1596"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "304/438 [===================>..........] - ETA: 0s - loss: 0.0893 - mean_absolute_error: 0.1594"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "332/438 [=====================>........] - ETA: 0s - loss: 0.0891 - mean_absolute_error: 0.1593"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "360/438 [=======================>......] - ETA: 0s - loss: 0.0890 - mean_absolute_error: 0.1593"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "388/438 [=========================>....] - ETA: 0s - loss: 0.0888 - mean_absolute_error: 0.1591"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "416/438 [===========================>..] - ETA: 0s - loss: 0.0886 - mean_absolute_error: 0.1589"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "438/438 [==============================] - 1s 2ms/step - loss: 0.0886 - mean_absolute_error: 0.1589\n"
     ]
    }
   ],
   "source": [
    "val_performance = {}\n",
    "performance = {}\n",
    "val_performance['Baseline'] = baseline.evaluate(wide_window.val)\n",
    "performance['Baseline'] = baseline.evaluate(wide_window.test, verbose=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "dfbCrf5q3P6n"
   },
   "source": [
    "#### 밀집"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:00:49.832787Z",
     "iopub.status.busy": "2022-12-14T23:00:49.832266Z",
     "iopub.status.idle": "2022-12-14T23:00:49.841214Z",
     "shell.execute_reply": "2022-12-14T23:00:49.840590Z"
    },
    "id": "NdpzH1dYjdIN"
   },
   "outputs": [],
   "source": [
    "dense = tf.keras.Sequential([\n",
    "    tf.keras.layers.Dense(units=64, activation='relu'),\n",
    "    tf.keras.layers.Dense(units=64, activation='relu'),\n",
    "    tf.keras.layers.Dense(units=num_features)\n",
    "])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:00:49.844836Z",
     "iopub.status.busy": "2022-12-14T23:00:49.844259Z",
     "iopub.status.idle": "2022-12-14T23:02:02.373334Z",
     "shell.execute_reply": "2022-12-14T23:02:02.372445Z"
    },
    "id": "6uHuU9Cd3PTo"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/439 [..............................] - ETA: 30s - loss: 0.0422 - mean_absolute_error: 0.1166"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 18/439 [>.............................] - ETA: 1s - loss: 0.0634 - mean_absolute_error: 0.1322 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 37/439 [=>............................] - ETA: 1s - loss: 0.0682 - mean_absolute_error: 0.1342"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 57/439 [==>...........................] - ETA: 1s - loss: 0.0673 - mean_absolute_error: 0.1334"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 76/439 [====>.........................] - ETA: 0s - loss: 0.0683 - mean_absolute_error: 0.1343"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 95/439 [=====>........................] - ETA: 0s - loss: 0.0671 - mean_absolute_error: 0.1330"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "115/439 [======>.......................] - ETA: 0s - loss: 0.0670 - mean_absolute_error: 0.1334"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "136/439 [========>.....................] - ETA: 0s - loss: 0.0685 - mean_absolute_error: 0.1345"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "155/439 [=========>....................] - ETA: 0s - loss: 0.0682 - mean_absolute_error: 0.1343"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "175/439 [==========>...................] - ETA: 0s - loss: 0.0691 - mean_absolute_error: 0.1348"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "195/439 [============>.................] - ETA: 0s - loss: 0.0691 - mean_absolute_error: 0.1350"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "215/439 [=============>................] - ETA: 0s - loss: 0.0693 - mean_absolute_error: 0.1349"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "235/439 [===============>..............] - ETA: 0s - loss: 0.0695 - mean_absolute_error: 0.1350"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "254/439 [================>.............] - ETA: 0s - loss: 0.0697 - mean_absolute_error: 0.1351"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "273/439 [=================>............] - ETA: 0s - loss: 0.0704 - mean_absolute_error: 0.1354"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "293/439 [===================>..........] - ETA: 0s - loss: 0.0699 - mean_absolute_error: 0.1351"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "313/439 [====================>.........] - ETA: 0s - loss: 0.0695 - mean_absolute_error: 0.1349"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "333/439 [=====================>........] - ETA: 0s - loss: 0.0697 - mean_absolute_error: 0.1350"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "353/439 [=======================>......] - ETA: 0s - loss: 0.0699 - mean_absolute_error: 0.1352"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "372/439 [========================>.....] - ETA: 0s - loss: 0.0696 - mean_absolute_error: 0.1350"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "392/439 [=========================>....] - ETA: 0s - loss: 0.0694 - mean_absolute_error: 0.1348"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "412/439 [===========================>..] - ETA: 0s - loss: 0.0692 - mean_absolute_error: 0.1346"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "432/439 [============================>.] - ETA: 0s - loss: 0.0691 - mean_absolute_error: 0.1346"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "439/439 [==============================] - 1s 3ms/step - loss: 0.0692 - mean_absolute_error: 0.1346\n"
     ]
    }
   ],
   "source": [
    "history = compile_and_fit(dense, single_step_window)\n",
    "\n",
    "IPython.display.clear_output()\n",
    "val_performance['Dense'] = dense.evaluate(single_step_window.val)\n",
    "performance['Dense'] = dense.evaluate(single_step_window.test, verbose=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "dsc9pur_mHsx"
   },
   "source": [
    "#### RNN\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:02:02.378083Z",
     "iopub.status.busy": "2022-12-14T23:02:02.377459Z",
     "iopub.status.idle": "2022-12-14T23:03:36.704157Z",
     "shell.execute_reply": "2022-12-14T23:03:36.703352Z"
    },
    "id": "4QbGLMyomXaz"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/438 [..............................] - ETA: 30s - loss: 0.0585 - mean_absolute_error: 0.1158"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 17/438 [>.............................] - ETA: 1s - loss: 0.0622 - mean_absolute_error: 0.1207 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 34/438 [=>............................] - ETA: 1s - loss: 0.0628 - mean_absolute_error: 0.1210"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 51/438 [==>...........................] - ETA: 1s - loss: 0.0624 - mean_absolute_error: 0.1210"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 68/438 [===>..........................] - ETA: 1s - loss: 0.0627 - mean_absolute_error: 0.1213"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 85/438 [====>.........................] - ETA: 1s - loss: 0.0624 - mean_absolute_error: 0.1212"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "103/438 [======>.......................] - ETA: 1s - loss: 0.0623 - mean_absolute_error: 0.1211"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "121/438 [=======>......................] - ETA: 0s - loss: 0.0620 - mean_absolute_error: 0.1209"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "138/438 [========>.....................] - ETA: 0s - loss: 0.0622 - mean_absolute_error: 0.1210"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "156/438 [=========>....................] - ETA: 0s - loss: 0.0622 - mean_absolute_error: 0.1209"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "173/438 [==========>...................] - ETA: 0s - loss: 0.0623 - mean_absolute_error: 0.1210"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "190/438 [============>.................] - ETA: 0s - loss: 0.0623 - mean_absolute_error: 0.1209"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "225/438 [==============>...............] - ETA: 0s - loss: 0.0625 - mean_absolute_error: 0.1211"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
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     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "276/438 [=================>............] - ETA: 0s - loss: 0.0625 - mean_absolute_error: 0.1211"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "293/438 [===================>..........] - ETA: 0s - loss: 0.0624 - mean_absolute_error: 0.1210"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "310/438 [====================>.........] - ETA: 0s - loss: 0.0622 - mean_absolute_error: 0.1209"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "327/438 [=====================>........] - ETA: 0s - loss: 0.0622 - mean_absolute_error: 0.1208"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "345/438 [======================>.......] - ETA: 0s - loss: 0.0622 - mean_absolute_error: 0.1208"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "363/438 [=======================>......] - ETA: 0s - loss: 0.0622 - mean_absolute_error: 0.1208"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "380/438 [=========================>....] - ETA: 0s - loss: 0.0621 - mean_absolute_error: 0.1207"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "397/438 [==========================>...] - ETA: 0s - loss: 0.0621 - mean_absolute_error: 0.1207"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "414/438 [===========================>..] - ETA: 0s - loss: 0.0621 - mean_absolute_error: 0.1206"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "431/438 [============================>.] - ETA: 0s - loss: 0.0620 - mean_absolute_error: 0.1206"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "438/438 [==============================] - 1s 3ms/step - loss: 0.0620 - mean_absolute_error: 0.1206\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "CPU times: user 3min 58s, sys: 58.6 s, total: 4min 56s\n",
      "Wall time: 1min 34s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "wide_window = WindowGenerator(\n",
    "    input_width=24, label_width=24, shift=1)\n",
    "\n",
    "lstm_model = tf.keras.models.Sequential([\n",
    "    # Shape [batch, time, features] => [batch, time, lstm_units]\n",
    "    tf.keras.layers.LSTM(32, return_sequences=True),\n",
    "    # Shape => [batch, time, features]\n",
    "    tf.keras.layers.Dense(units=num_features)\n",
    "])\n",
    "\n",
    "history = compile_and_fit(lstm_model, wide_window)\n",
    "\n",
    "IPython.display.clear_output()\n",
    "val_performance['LSTM'] = lstm_model.evaluate( wide_window.val)\n",
    "performance['LSTM'] = lstm_model.evaluate( wide_window.test, verbose=0)\n",
    "\n",
    "print()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "UwhY2f_Nn0_K"
   },
   "source": [
    "<a id=\"residual\"></a>\n",
    "\n",
    "#### 고급: 잔여 연결\n",
    "\n",
    "이전의 `Baseline` 모델은 시퀀스가 타임스텝 사이에서 크게 변하지 않는다는 사실을 이용했습니다. 지금까지 이 튜토리얼에서 훈련한 모든 모델은 무작위로 초기화된 다음, 출력이 이전 타임스텝에서 약간 변경된다는 사실을 학습해야 했습니다.\n",
    "\n",
    "신중한 초기화로 이 문제를 해결할 수 있지만 모델 구조로 빌드하는 것이 더 간단합니다.\n",
    "\n",
    "시계열 분석에서는 다음 값을 예측하는 대신 다음 타임스텝에서 값이 어떻게 달라지는 지를 예측하는 모델을 빌드하는 것이 일반적입니다. 마찬가지로 딥러닝에서 <a href=\"https://arxiv.org/abs/1512.03385\" class=\"external\">잔여 네트워크</a>(Residual networks) 또는 ResNets는 각 레이어가 모델의 누적 결과에 추가되는 아키텍처를 나타냅니다.\n",
    "\n",
    "이것은 변화가 작아야 한다는 사실을 이용하는 방법입니다.\n",
    "\n",
    "![A model with a residual connection](images/residual.png)\n",
    "\n",
    "기본적으로, `Baseline`과 일치하도록 모델을 초기화합니다. 그러면 이 작업에서 약간 더 나은 성능으로 모델이 더 빨리 수렴시키는 데 도움이 됩니다."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "yP58A_ORx0kM"
   },
   "source": [
    "이 접근 방식은 이 튜토리얼에서 설명하는 모든 모델과 연계하여 사용할 수 있습니다.\n",
    "\n",
    "여기서는 LSTM 모델에 적용합니다. `tf.initializers.zeros`를 사용하여 초기 예측하는 변경이 작고 잔류 연결을 압도하지 않도록 한다는 점에 유의하세요. `zeros`가 마지막 레이어에서만 사용되기 때문에 여기에서 그래디언트에 대한 대칭 파괴 문제는 없습니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:03:36.708398Z",
     "iopub.status.busy": "2022-12-14T23:03:36.707672Z",
     "iopub.status.idle": "2022-12-14T23:03:36.712687Z",
     "shell.execute_reply": "2022-12-14T23:03:36.711961Z"
    },
    "id": "7YlfnDQC22TQ"
   },
   "outputs": [],
   "source": [
    "class ResidualWrapper(tf.keras.Model):\n",
    "  def __init__(self, model):\n",
    "    super().__init__()\n",
    "    self.model = model\n",
    "\n",
    "  def call(self, inputs, *args, **kwargs):\n",
    "    delta = self.model(inputs, *args, **kwargs)\n",
    "\n",
    "    # The prediction for each time step is the input\n",
    "    # from the previous time step plus the delta\n",
    "    # calculated by the model.\n",
    "    return inputs + delta"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:03:36.716458Z",
     "iopub.status.busy": "2022-12-14T23:03:36.715670Z",
     "iopub.status.idle": "2022-12-14T23:04:44.644811Z",
     "shell.execute_reply": "2022-12-14T23:04:44.644013Z"
    },
    "id": "NNeH02pspc9B"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/438 [..............................] - ETA: 30s - loss: 0.0667 - mean_absolute_error: 0.1254"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 17/438 [>.............................] - ETA: 1s - loss: 0.0612 - mean_absolute_error: 0.1179 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 34/438 [=>............................] - ETA: 1s - loss: 0.0605 - mean_absolute_error: 0.1166"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 50/438 [==>...........................] - ETA: 1s - loss: 0.0607 - mean_absolute_error: 0.1170"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 67/438 [===>..........................] - ETA: 1s - loss: 0.0612 - mean_absolute_error: 0.1172"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 83/438 [====>.........................] - ETA: 1s - loss: 0.0615 - mean_absolute_error: 0.1175"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "100/438 [=====>........................] - ETA: 1s - loss: 0.0614 - mean_absolute_error: 0.1175"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "118/438 [=======>......................] - ETA: 0s - loss: 0.0617 - mean_absolute_error: 0.1177"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "134/438 [========>.....................] - ETA: 0s - loss: 0.0619 - mean_absolute_error: 0.1180"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "151/438 [=========>....................] - ETA: 0s - loss: 0.0619 - mean_absolute_error: 0.1180"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "168/438 [==========>...................] - ETA: 0s - loss: 0.0622 - mean_absolute_error: 0.1183"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "185/438 [===========>..................] - ETA: 0s - loss: 0.0623 - mean_absolute_error: 0.1184"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "202/438 [============>.................] - ETA: 0s - loss: 0.0623 - mean_absolute_error: 0.1184"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "218/438 [=============>................] - ETA: 0s - loss: 0.0624 - mean_absolute_error: 0.1185"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "234/438 [===============>..............] - ETA: 0s - loss: 0.0623 - mean_absolute_error: 0.1184"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "251/438 [================>.............] - ETA: 0s - loss: 0.0625 - mean_absolute_error: 0.1185"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "268/438 [=================>............] - ETA: 0s - loss: 0.0626 - mean_absolute_error: 0.1186"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "284/438 [==================>...........] - ETA: 0s - loss: 0.0627 - mean_absolute_error: 0.1187"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "300/438 [===================>..........] - ETA: 0s - loss: 0.0626 - mean_absolute_error: 0.1186"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "317/438 [====================>.........] - ETA: 0s - loss: 0.0625 - mean_absolute_error: 0.1186"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "334/438 [=====================>........] - ETA: 0s - loss: 0.0625 - mean_absolute_error: 0.1186"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "351/438 [=======================>......] - ETA: 0s - loss: 0.0625 - mean_absolute_error: 0.1185"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "368/438 [========================>.....] - ETA: 0s - loss: 0.0626 - mean_absolute_error: 0.1186"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "385/438 [=========================>....] - ETA: 0s - loss: 0.0625 - mean_absolute_error: 0.1186"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "402/438 [==========================>...] - ETA: 0s - loss: 0.0626 - mean_absolute_error: 0.1186"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "419/438 [===========================>..] - ETA: 0s - loss: 0.0625 - mean_absolute_error: 0.1185"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "436/438 [============================>.] - ETA: 0s - loss: 0.0626 - mean_absolute_error: 0.1186"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "438/438 [==============================] - 1s 3ms/step - loss: 0.0626 - mean_absolute_error: 0.1186\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "CPU times: user 2min 50s, sys: 41.1 s, total: 3min 31s\n",
      "Wall time: 1min 7s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "residual_lstm = ResidualWrapper(\n",
    "    tf.keras.Sequential([\n",
    "    tf.keras.layers.LSTM(32, return_sequences=True),\n",
    "    tf.keras.layers.Dense(\n",
    "        num_features,\n",
    "        # The predicted deltas should start small.\n",
    "        # Therefore, initialize the output layer with zeros.\n",
    "        kernel_initializer=tf.initializers.zeros())\n",
    "]))\n",
    "\n",
    "history = compile_and_fit(residual_lstm, wide_window)\n",
    "\n",
    "IPython.display.clear_output()\n",
    "val_performance['Residual LSTM'] = residual_lstm.evaluate(wide_window.val)\n",
    "performance['Residual LSTM'] = residual_lstm.evaluate(wide_window.test, verbose=0)\n",
    "print()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "I42Er9Du6co1"
   },
   "source": [
    "#### 성능"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "LZxR38P_6pUi"
   },
   "source": [
    "다음은 이러한 다중 출력 모델의 전반적인 성능입니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:04:44.649447Z",
     "iopub.status.busy": "2022-12-14T23:04:44.648751Z",
     "iopub.status.idle": "2022-12-14T23:04:44.818784Z",
     "shell.execute_reply": "2022-12-14T23:04:44.817990Z"
    },
    "id": "6XgTK9tnr7rc"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.arange(len(performance))\n",
    "width = 0.3\n",
    "\n",
    "metric_name = 'mean_absolute_error'\n",
    "metric_index = lstm_model.metrics_names.index('mean_absolute_error')\n",
    "val_mae = [v[metric_index] for v in val_performance.values()]\n",
    "test_mae = [v[metric_index] for v in performance.values()]\n",
    "\n",
    "plt.bar(x - 0.17, val_mae, width, label='Validation')\n",
    "plt.bar(x + 0.17, test_mae, width, label='Test')\n",
    "plt.xticks(ticks=x, labels=performance.keys(),\n",
    "           rotation=45)\n",
    "plt.ylabel('MAE (average over all outputs)')\n",
    "_ = plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:04:44.822895Z",
     "iopub.status.busy": "2022-12-14T23:04:44.822242Z",
     "iopub.status.idle": "2022-12-14T23:04:44.826413Z",
     "shell.execute_reply": "2022-12-14T23:04:44.825707Z"
    },
    "id": "URz3ajCc6kBj"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Baseline       : 0.1638\n",
      "Dense          : 0.1340\n",
      "LSTM           : 0.1217\n",
      "Residual LSTM  : 0.1196\n"
     ]
    }
   ],
   "source": [
    "for name, value in performance.items():\n",
    "  print(f'{name:15s}: {value[1]:0.4f}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "_Vt2MJhNxwPU"
   },
   "source": [
    "위의 성능은 모든 모델 출력에 대한 평균입니다."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "eYokb7Om2YbK"
   },
   "source": [
    "## 다중 스텝 모델\n",
    "\n",
    "이전 섹션의 단일 출력 및 다중 출력 모델은 모두 미래 1시간의 **단일 타임스텝 예측**을 수행했습니다.\n",
    "\n",
    "이 섹션에서는 이러한 모델을 확장하여 **다중 타임스텝 예측**을 수행하는 방법을 살펴봅니다.\n",
    "\n",
    "다중 스텝 예측에서 모델은 일정 범위의 미래 값을 예측하는 방법을 학습해야 합니다. 따라서 한 미래 시점만 예측하는 단일 스텝 모델과 달리 다중 스텝 모델은 미래 값의 시퀀스를 예측합니다.\n",
    "\n",
    "대략적으로 두 가지 접근 방식이 있습니다.\n",
    "\n",
    "1. 전체 시계열이 한 번에 예측되는 싱글샷 예측\n",
    "2. 모델이 단일 스텝 예측만 수행하고 출력이 입력으로 피드백되는 자기 회귀적 예측\n",
    "\n",
    "이 섹션에서는 모든 모델이 **모든 출력 타임스텝에 걸쳐 모든 특성**을 예측합니다.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "WFsDAwVt4_rq"
   },
   "source": [
    "다중 스텝 모델의 경우, 훈련 데이터는 다시 시간별 샘플로 구성됩니다. 그러나 여기에서 모델은 과거의 24시간을 고려하여 미래의 24시간을 예측하는 방법을 학습합니다.\n",
    "\n",
    "다음은 데이터세트로부터 이러한 조각을 생성하는 `Window` 객체입니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:04:44.830651Z",
     "iopub.status.busy": "2022-12-14T23:04:44.830015Z",
     "iopub.status.idle": "2022-12-14T23:04:45.363431Z",
     "shell.execute_reply": "2022-12-14T23:04:45.362589Z"
    },
    "id": "1cFYtsz6XiGw"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Total window size: 48\n",
       "Input indices: [ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23]\n",
       "Label indices: [24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47]\n",
       "Label column name(s): None"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x800 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "OUT_STEPS = 24\n",
    "multi_window = WindowGenerator(input_width=24,\n",
    "                               label_width=OUT_STEPS,\n",
    "                               shift=OUT_STEPS)\n",
    "\n",
    "multi_window.plot()\n",
    "multi_window"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "5lg8SInh9Jzd"
   },
   "source": [
    "### 기준"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "axwpoWYOApJL"
   },
   "source": [
    "이 작업의 간단한 기준은 필요한 출력 타임스텝 수에 대해 마지막 입력 타임스텝을 반복하는 것입니다.\n",
    "\n",
    "![각 출력 단계에 대해 마지막 입력 반복](images/multistep_last.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:04:45.367999Z",
     "iopub.status.busy": "2022-12-14T23:04:45.367722Z",
     "iopub.status.idle": "2022-12-14T23:04:47.325739Z",
     "shell.execute_reply": "2022-12-14T23:04:47.324816Z"
    },
    "id": "_5iaHSaJ9Rxv"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/437 [..............................] - ETA: 1:10 - loss: 0.6104 - mean_absolute_error: 0.5006"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 25/437 [>.............................] - ETA: 0s - loss: 0.6262 - mean_absolute_error: 0.5017  "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 52/437 [==>...........................] - ETA: 0s - loss: 0.6280 - mean_absolute_error: 0.5021"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 78/437 [====>.........................] - ETA: 0s - loss: 0.6302 - mean_absolute_error: 0.5013"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "104/437 [======>.......................] - ETA: 0s - loss: 0.6261 - mean_absolute_error: 0.4998"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "131/437 [=======>......................] - ETA: 0s - loss: 0.6250 - mean_absolute_error: 0.4997"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "158/437 [=========>....................] - ETA: 0s - loss: 0.6265 - mean_absolute_error: 0.4998"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "184/437 [===========>..................] - ETA: 0s - loss: 0.6292 - mean_absolute_error: 0.5010"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "211/437 [=============>................] - ETA: 0s - loss: 0.6304 - mean_absolute_error: 0.5016"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "237/437 [===============>..............] - ETA: 0s - loss: 0.6305 - mean_absolute_error: 0.5017"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "264/437 [=================>............] - ETA: 0s - loss: 0.6310 - mean_absolute_error: 0.5016"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "291/437 [==================>...........] - ETA: 0s - loss: 0.6308 - mean_absolute_error: 0.5016"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "318/437 [====================>.........] - ETA: 0s - loss: 0.6312 - mean_absolute_error: 0.5016"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "347/437 [======================>.......] - ETA: 0s - loss: 0.6305 - mean_absolute_error: 0.5012"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "375/437 [========================>.....] - ETA: 0s - loss: 0.6298 - mean_absolute_error: 0.5008"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "402/437 [==========================>...] - ETA: 0s - loss: 0.6298 - mean_absolute_error: 0.5008"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "429/437 [============================>.] - ETA: 0s - loss: 0.6290 - mean_absolute_error: 0.5008"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "437/437 [==============================] - 1s 2ms/step - loss: 0.6285 - mean_absolute_error: 0.5007\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1200x800 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "class MultiStepLastBaseline(tf.keras.Model):\n",
    "  def call(self, inputs):\n",
    "    return tf.tile(inputs[:, -1:, :], [1, OUT_STEPS, 1])\n",
    "\n",
    "last_baseline = MultiStepLastBaseline()\n",
    "last_baseline.compile(loss=tf.keras.losses.MeanSquaredError(),\n",
    "                      metrics=[tf.keras.metrics.MeanAbsoluteError()])\n",
    "\n",
    "multi_val_performance = {}\n",
    "multi_performance = {}\n",
    "\n",
    "multi_val_performance['Last'] = last_baseline.evaluate(multi_window.val)\n",
    "multi_performance['Last'] = last_baseline.evaluate(multi_window.test, verbose=0)\n",
    "multi_window.plot(last_baseline)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "AvHZ93ObAfMA"
   },
   "source": [
    "이 작업은 과거의 24시간을 고려하여 미래의 24시간을 예측하는 것이므로 또 다른 간단한 접근법은 내일도 비슷하다는 가정 하에 전날을 반복하는 것입니다.\n",
    "\n",
    "![Repeat the previous day](images/multistep_repeat.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:04:47.330321Z",
     "iopub.status.busy": "2022-12-14T23:04:47.329698Z",
     "iopub.status.idle": "2022-12-14T23:04:49.219256Z",
     "shell.execute_reply": "2022-12-14T23:04:49.218497Z"
    },
    "id": "L8Y1uMhGwIRs"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/437 [..............................] - ETA: 1:00 - loss: 0.5366 - mean_absolute_error: 0.4497"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 26/437 [>.............................] - ETA: 0s - loss: 0.4316 - mean_absolute_error: 0.3978  "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 53/437 [==>...........................] - ETA: 0s - loss: 0.4270 - mean_absolute_error: 0.3971"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 81/437 [====>.........................] - ETA: 0s - loss: 0.4359 - mean_absolute_error: 0.4002"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "109/437 [======>.......................] - ETA: 0s - loss: 0.4362 - mean_absolute_error: 0.4006"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "137/437 [========>.....................] - ETA: 0s - loss: 0.4347 - mean_absolute_error: 0.4005"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "165/437 [==========>...................] - ETA: 0s - loss: 0.4339 - mean_absolute_error: 0.4000"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "193/437 [============>.................] - ETA: 0s - loss: 0.4308 - mean_absolute_error: 0.3984"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "220/437 [==============>...............] - ETA: 0s - loss: 0.4320 - mean_absolute_error: 0.3989"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "246/437 [===============>..............] - ETA: 0s - loss: 0.4302 - mean_absolute_error: 0.3981"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "273/437 [=================>............] - ETA: 0s - loss: 0.4294 - mean_absolute_error: 0.3975"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "301/437 [===================>..........] - ETA: 0s - loss: 0.4268 - mean_absolute_error: 0.3961"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "329/437 [=====================>........] - ETA: 0s - loss: 0.4284 - mean_absolute_error: 0.3965"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "357/437 [=======================>......] - ETA: 0s - loss: 0.4289 - mean_absolute_error: 0.3965"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "386/437 [=========================>....] - ETA: 0s - loss: 0.4276 - mean_absolute_error: 0.3961"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "415/437 [===========================>..] - ETA: 0s - loss: 0.4273 - mean_absolute_error: 0.3959"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "437/437 [==============================] - 1s 2ms/step - loss: 0.4270 - mean_absolute_error: 0.3959\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1200x800 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "class RepeatBaseline(tf.keras.Model):\n",
    "  def call(self, inputs):\n",
    "    return inputs\n",
    "\n",
    "repeat_baseline = RepeatBaseline()\n",
    "repeat_baseline.compile(loss=tf.keras.losses.MeanSquaredError(),\n",
    "                        metrics=[tf.keras.metrics.MeanAbsoluteError()])\n",
    "\n",
    "multi_val_performance['Repeat'] = repeat_baseline.evaluate(multi_window.val)\n",
    "multi_performance['Repeat'] = repeat_baseline.evaluate(multi_window.test, verbose=0)\n",
    "multi_window.plot(repeat_baseline)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "tbndS-ct9C2Q"
   },
   "source": [
    "### 싱글샷 모델\n",
    "\n",
    "이 문제에 대한 한 가지 높은 수준의 접근법은 모델이 한 번에 전체 시퀀스 예측을 수행하는 \"싱글샷\" 모델을 사용하는 것입니다.\n",
    "\n",
    "이 모델은 `OUT_STEPS*features` 출력 단위를 이용한 `tf.keras.layers.Dense`로 효율적으로 구현할 수 있습니다. 이 모델은 이 출력의 형상을 필요한 `(OUTPUT_STEPS, features)`로 바꾸기만 하면 됩니다."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "NCKS4m1VKrDQ"
   },
   "source": [
    "#### 선형\n",
    "\n",
    "마지막 입력 타임스텝을 기반으로 하는 단순한 선형 모델은 기준 모델보다 성능이 더 좋지만 강력하지 못합니다. 이 모델은 선형 프로젝션을 이용해 단일 입력 타임스텝으로부터 `OUTPUT_STEPS` 타임스텝을 예측해야 합니다. 주로 하루 중 시간과 연중 시간을 기반으로 하는 행동의 저차원 조각만 캡처할 수 있습니다.\n",
    "\n",
    "![마지막 타임스텝에서 모든 타임스텝 예측](images/multistep_dense.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:04:49.224280Z",
     "iopub.status.busy": "2022-12-14T23:04:49.223699Z",
     "iopub.status.idle": "2022-12-14T23:05:26.763090Z",
     "shell.execute_reply": "2022-12-14T23:05:26.762298Z"
    },
    "id": "kfRz_WVhIQcd"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/437 [..............................] - ETA: 28s - loss: 0.2271 - mean_absolute_error: 0.2947"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 22/437 [>.............................] - ETA: 0s - loss: 0.2448 - mean_absolute_error: 0.2990 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 44/437 [==>...........................] - ETA: 0s - loss: 0.2507 - mean_absolute_error: 0.3028"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 66/437 [===>..........................] - ETA: 0s - loss: 0.2514 - mean_absolute_error: 0.3026"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 89/437 [=====>........................] - ETA: 0s - loss: 0.2518 - mean_absolute_error: 0.3029"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "111/437 [======>.......................] - ETA: 0s - loss: 0.2532 - mean_absolute_error: 0.3035"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "134/437 [========>.....................] - ETA: 0s - loss: 0.2537 - mean_absolute_error: 0.3037"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "157/437 [=========>....................] - ETA: 0s - loss: 0.2541 - mean_absolute_error: 0.3041"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "179/437 [===========>..................] - ETA: 0s - loss: 0.2547 - mean_absolute_error: 0.3043"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "201/437 [============>.................] - ETA: 0s - loss: 0.2545 - mean_absolute_error: 0.3045"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "222/437 [==============>...............] - ETA: 0s - loss: 0.2554 - mean_absolute_error: 0.3047"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "244/437 [===============>..............] - ETA: 0s - loss: 0.2555 - mean_absolute_error: 0.3047"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "267/437 [=================>............] - ETA: 0s - loss: 0.2550 - mean_absolute_error: 0.3045"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "289/437 [==================>...........] - ETA: 0s - loss: 0.2551 - mean_absolute_error: 0.3046"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "312/437 [====================>.........] - ETA: 0s - loss: 0.2556 - mean_absolute_error: 0.3047"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "334/437 [=====================>........] - ETA: 0s - loss: 0.2550 - mean_absolute_error: 0.3043"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "379/437 [=========================>....] - ETA: 0s - loss: 0.2552 - mean_absolute_error: 0.3046"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "425/437 [============================>.] - ETA: 0s - loss: 0.2555 - mean_absolute_error: 0.3048"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "437/437 [==============================] - 1s 2ms/step - loss: 0.2552 - mean_absolute_error: 0.3047\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x800 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "multi_linear_model = tf.keras.Sequential([\n",
    "    # Take the last time-step.\n",
    "    # Shape [batch, time, features] => [batch, 1, features]\n",
    "    tf.keras.layers.Lambda(lambda x: x[:, -1:, :]),\n",
    "    # Shape => [batch, 1, out_steps*features]\n",
    "    tf.keras.layers.Dense(OUT_STEPS*num_features,\n",
    "                          kernel_initializer=tf.initializers.zeros()),\n",
    "    # Shape => [batch, out_steps, features]\n",
    "    tf.keras.layers.Reshape([OUT_STEPS, num_features])\n",
    "])\n",
    "\n",
    "history = compile_and_fit(multi_linear_model, multi_window)\n",
    "\n",
    "IPython.display.clear_output()\n",
    "multi_val_performance['Linear'] = multi_linear_model.evaluate(multi_window.val)\n",
    "multi_performance['Linear'] = multi_linear_model.evaluate(multi_window.test, verbose=0)\n",
    "multi_window.plot(multi_linear_model)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "zi2TMHk2IRrh"
   },
   "source": [
    "#### 밀집\n",
    "\n",
    "입력과 출력 사이에 `tf.keras.layers.Dense`를 추가하면 선형 모델이 더 강력해지지만 여전히 단일 입력에 기반합니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:05:26.767640Z",
     "iopub.status.busy": "2022-12-14T23:05:26.767068Z",
     "iopub.status.idle": "2022-12-14T23:06:21.546087Z",
     "shell.execute_reply": "2022-12-14T23:06:21.545252Z"
    },
    "id": "jezm-BKaGj91"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/437 [..............................] - ETA: 28s - loss: 0.2352 - mean_absolute_error: 0.2890"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 20/437 [>.............................] - ETA: 1s - loss: 0.2332 - mean_absolute_error: 0.2888 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 41/437 [=>............................] - ETA: 1s - loss: 0.2284 - mean_absolute_error: 0.2873"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 62/437 [===>..........................] - ETA: 0s - loss: 0.2219 - mean_absolute_error: 0.2838"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 82/437 [====>.........................] - ETA: 0s - loss: 0.2240 - mean_absolute_error: 0.2846"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "103/437 [======>.......................] - ETA: 0s - loss: 0.2227 - mean_absolute_error: 0.2843"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "124/437 [=======>......................] - ETA: 0s - loss: 0.2225 - mean_absolute_error: 0.2840"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "146/437 [=========>....................] - ETA: 0s - loss: 0.2222 - mean_absolute_error: 0.2839"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "168/437 [==========>...................] - ETA: 0s - loss: 0.2219 - mean_absolute_error: 0.2837"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "190/437 [============>.................] - ETA: 0s - loss: 0.2222 - mean_absolute_error: 0.2840"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "211/437 [=============>................] - ETA: 0s - loss: 0.2224 - mean_absolute_error: 0.2840"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "232/437 [==============>...............] - ETA: 0s - loss: 0.2223 - mean_absolute_error: 0.2840"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "275/437 [=================>............] - ETA: 0s - loss: 0.2225 - mean_absolute_error: 0.2844"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "296/437 [===================>..........] - ETA: 0s - loss: 0.2218 - mean_absolute_error: 0.2839"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
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     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "402/437 [==========================>...] - ETA: 0s - loss: 0.2216 - mean_absolute_error: 0.2837"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "437/437 [==============================] - 1s 2ms/step - loss: 0.2211 - mean_absolute_error: 0.2833\n"
     ]
    },
    {
     "data": {
      "image/png": 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6mUzAzGc6AgDWJCTh+t18PUdERNQ85eXlYfLkyYiPj1fbHh8fj8mTJyMvL09PkRE9PI2SeqL7rVixAnZ2dvU+jyAIiImJqfd5iJqStUeT8N0/S9ctDPVDv/ZOeo6IpNK3nRMGdGiBcqWI/8Vf0nc4REQGRYpkPC8vD4MHPY1ly5Zh2NBnERcXBwCIi4vDsKHPYtmyZRg86GmNz8XGAWosNErq7e3t4eDgoNGDDEN4eDhCQkL0HQYR3Wff5bv4v5iKJdDeesobo3t56jkiktrMZ3whE4Dfz6biZFKWvsMhIjIIUiTjlec4e/o49k+0wDPtZAgdEYI5c+YgdEQIhrSXYf9EC5w9fVzjc0nROEAkBY2S+oiICHz11Vf46quvMHv2bABAUFAQ5s6di7lz5yIoKAgAMGfOHN1F2kQVFxcjMjISI0eOxIAnB2DkyJGIjIxEcXGxvkMjogZ0MTUXr68+CYVSRGj3lnhnoLe+QyId6OBqjVE9PQAAC7ddgCiKdRxBRGTY6tujLVUyPnXqVBw6koC4saZ41MsI60eZ4pl2MixYsABD2suwbmTF9rixpjh0JAFTp07VaTxSvT9EAABRS6GhoeI333xTZfs333wjDh8+XNvTNXo5OTkiADEnJ6fKc0VFReL58+fFoqKihzr35s2bRXtHexGAaOVjJdr2sRWtfKxEAKK9o70YGxtb3/BrNGHChBo/ry+++ELs3LmzaGFhIXp4eIivvfaamJeXp3p++fLloq2trRgdHS22b99eNDU1FQcNGiQmJSWpnScmJkbs3r27aGpqKrZp00acO3euWFZWpnoegBgdHS2KoiiWlJSIb7zxhujq6iqampqKXl5e4ieffCL5dUuhvp870YNSc4rEgE92ia1mbBXDlhwSi8vK9R0S6dCd7EKxw+xtYqsZW8X4syn6DoeISGdyc3PFvgH+IgDRxNhI3Lp1qyiKorh161bRxNhIBCD2DfAXc3NzazzHpEmTRADi/okWoviRjVgy21oc3tFEBCCG+JqIJbOtRfEjG3H/RAsRgDhp0qRqz7N9+3bRxNhI7ZiS2dZiVJi52u/DO5qIJsZG4vbt23Uaj1TvDzVdteWhD9J6Tn18fDwGDx5cZfvgwYOxa9euh2tZaIZiY2MxYsQIKFop4L3IG60/aA3P1z3R+oPW8F7kDUUrBUJCQhAbG9vgsclkMixevBjnzp3DypUrsXv3bkyfPl1tn8LCQvz3v//FqlWrcPDgQWRnZ2Ps2LGq5/fv34/x48fj7bffxvnz5/Hjjz9ixYoV+O9//1vtay5evBixsbFYv349Ll26hNWrV6N169a6vEyiRiG/pBwTlx9DSk4x2rWwxE8v9oKpkVzfYZEOudmaY/KjbQAAi7ZfRLlCqeeIiIikJ1WPdlhYGEyMjfDFkXKUKkSYyAWsH2WKqDBzrBtpChO5gFKFiM8Pl8PE2AhhYWHVnicoKAhR0THYdlWJMZtKVOca4WusOkfYxhL8fk2JqOgY1UhkXcUjdY8/NW9aJ/WOjo7YvHlzle2bN2+Go6OjJEE1dcXFxQifFA6rblbwnOIJU1f1lQVMXU3hOcUTVt2sED4pvMGH4k+dOhUDBgxA69at8eSTT2LBggVYv3692j5lZWX49ttvERgYiJ49e2LlypU4dOgQjh49CgCYN28eZs6ciQkTJqBt27Z4+umnMX/+fPz444/VvmZSUhK8vb3x6KOPolWrVnj00Ufx3HPP6fxaifSpXKHEm2tO4nxKLpysTLBiYh/YWhjrOyxqAK8+3g4Olia4frcA644n6zscIiLJSTXcXapkHACCg4MxfcZMxFwoRdzlcrXn4i6XY/PFUkyfMRPBwcE1nkOqeKR6f4iAh0jq582bhxkzZmDo0KFYsGABFixYgKFDh2LmzJmYN2+eLmJU2bdvH4YOHQp3d3eNK6fv2bMHPXr0gKmpKdq3b48VK1boNEZNbNiwAVn3suAS5gJBJlS7jyAT4DLaBVn3srBx48YGjW/Xrl146qmn0LJlS1hbW+PFF1/EvXv3UFhYqNrHyMgIvXv3Vv3esWNH2NnZ4cKFCwCA06dP4+OPP4aVlZXq8fLLLyMlJUXtPJXCw8Nx6tQpdOjQAW+99RZ27Nih+wsl0iNRFPFR7Dn8eekuzIxl+GVCb3g6WOg7LGogNmbGeOvJ9gCAr3ZeQUFJeR1HEBEZFql6tAFpknGgopDdZ58uQoivCYJ9jNRfw8cIwzua4LNPF6kK3+kyHinfH4Bz85s7rZP68PBwHDx4EDY2NoiKikJUVBRsbGxw4MABhIeH6yDEfxUUFKBr16747rvvNNr/xo0bCA4OxoABA3Dq1ClMnToVL730UpWbvaHFxMTAyseqSg/9g0zdTGHlY4Xo6OgGigxITEzEs88+iy5dumDTpk04ceKE6v0uLS3V+Dz5+fmYN28eTp06pXqcOXMGV65cgZmZWZX9e/TogRs3bmD+/PkoKipCWFgYRo0aJdl1ETU2P++/jtUJSRAEIGJMd3TztNN3SNTAxvm3QitHC2Tkl+Dn/df1HQ4RkaSk7GGXIhmPj49XDWu/P2mOvlCmllRXDoOvLV+QIh4p3x9W46eHWqfe398fq1evxsmTJ3Hy5EmsXr0a/v7+UsdWxTPPPIMFCxZgxIgRGu2/ZMkStGnTBl988QV8fX0xZcoUjBo1Cl999ZWOI61dZlYm5HaazZmV2cmQmZWp44j+deLECSiVSnzxxRcICAiAj48P7ty5U2W/8vJyHD9+XPX7pUuXkJ2dDV9fXwAVSfqlS5fQvn37Kg+ZrPrbzsbGBmPGjMHPP/+MdevWYdOmTcjMbLhrJ2oo286k4JNtFwEAs4M7YXBnVz1HRPpgYiTD9KCOAICf9l1Heh5XPSGixkOKnl8perSlSsbXr1+P0rJyvBtgpJY0h64vUkuq3ws0QmlZeZWpp1LHI9X7w7n5BDxkUn/t2jXMnj0b48aNQ3p6OgDg999/x7lz5yQNrr4OHz6MgQMHqm0LCgrC4cOHazympKQEubm5ag+pOdg7QJGt0GhfZbYSDvYOkscAADk5OWo96adOnYKTkxPKysrwzTff4Pr164iMjMSSJUuqHGtsbIw333wTCQkJOHHiBMLDwxEQEIA+ffoAAD788EOsWrUK8+bNw7lz53DhwgWsXbtWtSTig7788kv89ttvuHjxIi5fvowNGzbA1dUVdnZ2Orl2In1IySnCikOJmLr2LwDAhMBWmNSvtX6DIr0a4ueKrp52KCxVYPEfV/QdDhERAOl6fqXo0ZYqGY+IiEDfAH8Ery3BgaRyVS/47NmzVb3lB5LKEby2BH0D/BEREaHTeKR6fzg3n4CHSOr37t0LPz8/JCQkYNOmTcjPzwdQMYf6o48+kjzA+khNTYWLi4vaNhcXF+Tm5qKoqKjaYxYuXAhbW1vVw9PTU/K4QkJCkH85HyWpJbXuV5JSgvzL+RqPTNDWnj170L17d7VHZGQkvvzyS3z66afo3LkzVq9ejYULF1Y51sLCAjNmzMC4cePQr18/WFlZYd26darng4KCsHXrVuzYsQO9e/dGQEAAvvrqK7Rq1araWKytrfHZZ5+hV69e6N27NxITE7Ft27Yae/WJDM2ahJvou2g35saeQ6lChK+bNT4c+ggEofq6GtQ8CIKAD56p6K3/7Wgyrt3N13NERNTcSdXzK1WPtlTJuLW1Nbbv2InOXXuh//JC1bD2+fPnq4bB919eiM5de2H7jp2wtrbWaTxSvT9Sz80nwySIoihqc0BgYCBGjx6NadOmwdraGqdPn0bbtm1x9OhRhIaG4tatW7qKVY0gCIiOjkZISEiN+/j4+GDixImYNWuWatu2bdsQHByMwsJCmJubVzmmpKQEJSX/Jtu5ubnw9PRETk4ObGxs1PYtLi7GjRs30KZNm2rnidekuLgY7h7uULRSwHOKZ7XF8kSliORvkyG/KcedW3e0Oj/p1sN+7mS4UnKKcCOjAG2cLOFmW/V7o0yhRFpuMVJyKh6pOUUVP2cXIyW3GLezCpGRr16TQiYAB2c+We35qPl5aeUx7LqQjqBHXPDji730HQ4RNWOTJ0/GsmXLsH+iBR71MlL1RG++WIoQXxNVonggqRz9lxdi0qRJWLp0qc7OA/zb0HDoSAJMjI0QFR2D4OBgxMXFIXRECErLytE3wL/WZPz+c02dOhVhYWFq89Tj4+Oxfv16REREaHSO+sYj5ftT+br3NxBUenBufl3FBKnxyM3Nha2tbbV56IOMan22GmfOnMGaNWuqbHd2dkZGRoa2p9MpV1dXpKWlqW1LS0uDjY1NtQk9AJiamsLUtPYCdvVlZmaGlctXIiQkBMnfJsMlzEWtaF5JSgnSNqQh/1Q+YmJimDgS6dG6Y0mYFXUGShEQADzT2RXONmZIySlCak4x7uQUIyO/BNo1jwJKEUjMKGRSTwCAGYM7YvfFdMSfS8PxxEz0aq2baVdERHUJCwvDr5Gr8MWRcvRpKVf1/MZdliPYx0jjnt+IiAhcPH8OwWuPI24s8PnhclWP9mefLsKYTSV4N8Cozh5t4N9e9geT8eDgYMRu2apxMl55ruqS46CgoFqL0Ukdj5TvT+Xc/AULFiDushwjfP9dHrdybv7s2bOZ0DdhWvfUe3h4YP369ejbt69aT310dDTee+89XLt2TVexqtGkp37GjBnYtm0bzpw5o9o2btw4ZGZmYvv27Rq9Tm0tJPXtsY2NjUX4pHBk3cuClY8VZHYyKLOVyL+cD3tHe6xcvhJDhw7V+rykW+ypbz5ScorQb9FuKDX4ljSRy+Biawo3W3O42ZrB1dYM7rbmcLU1g7FcwEsrj6udRy4IODBzAJN6UpkV9Td+O5qMHl522PRaX07NICK9karnV8oe9qZIqveHPfVNk0576seOHYsZM2Zgw4YNEAQBSqUSBw8exHvvvYfx48c/dNCayM/Px9WrV1W/37hxA6dOnYKDgwO8vLwwa9Ys3L59G6tWrQIA/Oc//8G3336L6dOnY9KkSdi9ezfWr19f59qTDWXYsGG4c+sONm7ciOjoaGRmZcLBwwEj5ozAqFGjmDAS6dmNjIJqE/phXd3Rq7U9XG3MKpJ4OzM4WJhAVs1UmkoLQ/3wQdRZKEQRckHAJ6GdmdCTmqkDfRDz1x2cTMpG/LlUDO7spu+QiKiZkqrnV8oedikVFxdjw4YNiImJqfj7294BISEhGD16dIP+/S3F+1PT3Py4y+WqkRXrR5lWFPMbEYLYLVs1HpFAhkPrnvrS0lK88cYbWLFiBRQKBYyMjKBQKDBu3DisWLECcrlmS7U9jD179mDAgAFVtk+YMAErVqxAeHg4EhMTsWfPHrVj3nnnHZw/fx4eHh6YM2cOwsPDNX5NXfbUk2Hi5958pOQUIXDhbrVt9elhT8kpQmJGIVo7WTChp2p9ueMSFu++ijZOltjxzmMwlrNYKBE1vKbc8/vgSFm5nRyKbIXBjpStbm7+qPVF2HK5HMM6GGHDaHON5+YDFaMH3nzzTbRo0QLXr19XNXq0bdsWd+/exTfffNMsR1XogzY99Von9ZWSkpJw9uxZ5Ofno3v37vD29n6oYBs7JvX0IH7uzcetrEL0//RPVH5JVvawj+ntpde4qOnKLynH45/9iXsFpZgf0hkvBlS/YggRUU3qWwguPj4ew4Y+W2vP7/2JvSH1/MbGxmLEiBGw6mZVtaZVagnS1lfUtIqOjsawYcMaLK76jByoHMJ/5tQxbHvODJ8dLEXclXIYu5miLKUEz3ob4f1+JhjyWzH8uvWudSh/Xl4e/Hv3woVLlyETABM3M5h6mKLkVglKU4qhFAHfjj5IOHqciX0D0Capf+guAC8vLwwZMgRhYWFNNqEnoubt1yNJEAH0am2H314OwIGZA5jQk05ZmRph6sCK/6d+vesy8kvK9RwRERkSKdaXl3Id9sakuLgY4ZPCYdXNCp5TPNUSegAwdTWF5xRPWHWzQvikcBQXFzdIXLGxsXD3cMf48eOx4+wO/FXwF3ac3YHx48fD3cMdW7ZsqfV4a2trvPn2VBSWVCzJF3etHJ5vt4L3J97wfLsVtl6r6KEvLFHizben1pnQJ12/jP0TLRDsY4TS9GKYuJigNL0Yz3Ywwv6JFki6dhn+vXvVeg9Rw9O6p14URWzcuBF//vkn0tPToVQq1Z6PioqSNEB9Y089PYife/NQXKZAwMI/kF1Yhp9e7IlBj7jqOyRqJsoUSgz6ah9uZBTgrae8Me1pH32HREQG4P715ePGmqqqqU+fMROffboIQ9rLVNXUa1uLXarzNDaRkZEYP348vBd5V0no71eSUoIrs64gMjISL7zwgk5jkmLkQOVS2eUe5ZBby2Hrbwtrv38/j7wzechJyIEiTwGjW0Y1LpUdHh6OlStXqg/j31CELZfKMayjETaMUh/GXzn9mXRHpz31U6dOxYsvvogbN27AysoKtra2ag8ioqYg9tQdZBeWwcPeHE/5uug7HGpGjOUyzBjcAQDw877rSM9tmN4iIjJsU6dOxaEjCYgba4pHvYywfpQpnmknw4IFC1RD6R/1MkLcWFMcOpKAqVOnVnueyuJtnbv2Qv/lhaq58/Pnz0dUdAy2Xa3oETakhB4AYmJiYOVjVWtCDwCmbqaw8rFCdHS0TuORauTAhg0bkHUvC67PucLjJQ+1hB4ArP2s4fGSB1zHuiLrXhY2btxY7XlatGgBmQD873CpajTGxtHmiAozVyX0pQoRnx0qhUyoWM6cGg+tq99HRkYiKioKQ4YM0UU8RER6J4oilh9KBACMD2wFeS1V7Yl0IegRV/TwssPJpGx8tesKFob66TskyTWW6tNETYVU68sDjbdqfX1kZmVCbqdZQW+ZnQyZWZl17lef77HKZNz7fW8INfydIcgEuIx2wZVZV7Bx48ZqRw48TGNFdee5fv06TNzMsPVqMUZvLFIl8pUrH1T23MddK4eJm1mDLWNOmtG6p97W1hZt27bVRSzUBIWHhyMkJET1+xNPPFFjy7CmpDgHUW2OJWbhQkouzIxlCOvlqe9wqBkSBAEfDPEFAKw7loSr6U1r7mJ955ASUVVBQUGqnvT7576P8DWuUtwuKjqmzuJ21tbWWLp0aZX9goKCsHTpUoNK6AHAwd4BimyFRvsqs5VwsHeodZ/6fo9JNXJAqsaKzKxMmHqYwvGZFoi9WI64y+o1XeIul2PLpXI4PtMCJh4mGjV6UMPROqmfO3cu5s2bh6KiIl3E06zk5eVh8uTJiI+PV9seHx+PyZMn67QARXh4OARBgCAIMDExQfv27fHxxx+jvFy3RZmioqIwf/58jfbds2cPBEFAdnb2Q5+D6GGs/KeXfkT3lrCzMNFvMNRs9WrtgEGdXKAUgUW/X9J3OJKpnEOqaKWA9yJvtP6gNTxf90TrD1rDe5E3FK0UCAkJQWxsrEbnKy4uRmRkJEaOHIkBTw7AyJEjERkZ2WBFrogak8r15WMulFablG2+WIrpM2Ya3DJ0UggJCUH+5XyUpJbUul9JSgnyL+djxIgRNe4jxfeYVMm4VI0VDvYOKLlVgnu/38WwjkYI9lEf0B3sY4ShHYxw7/e7KL1VWmejBzUsrZP6sLAwZGVlwdnZGX5+fujRo4fagzQjRXXS+ho8eDBSUlJw5coVvPvuu5g7dy7+97//VdmvtLRUstd0cHCod8uuFOcgqsmd7CJsP5cKAJjQt7V+g6Fmb/rgjpDLBOy6kIajNxpXr0hKThEOXctASo7mjfxSV59mjz+Ruri4OHz26SKE+JpUm5QN72iCzz5dpPq7szkZPXo07B3tkbY+DaKy+jrholJE2oY02DvaY9SoUdXuI9X3mFTJuFSNFW3btkVpSjGebW+kNoc++kKZ2hz74HZGKE0pRrt27TSKnRqG1kn9hAkTcOLECbzwwgsYOXIkhg8frvagut1fVXT/RAs8006G0BEhmDNnDkJHhGBIexn2T7TA2dPHdZrYm5qawtXVFa1atcJrr72GgQMHIjY2VjVk/r///S/c3d3RoUNFwabk5GSEhYXBzs4ODg4OGD58OBITE1XnUygUmDZtGuzs7ODo6Ijp06fjwcUVHhw6X1JSghkzZsDT0xOmpqZo3749li5disTERAwYMAAAYG9vD0EQEB4eXu05srKyMH78eNjb28PCwgLPPPMMrly5onp+xYoVsLOzQ3x8PHx9fWFlZaVq0Ki0Z88e9OnTB5aWlrCzs0O/fv1w8+ZNid5pMiSrE25CoRTh38YBHV1rrzRKpGvtna0wtnfFFJC5sedw6Kp2SbSurDuWhH6LdmPczwnot2g31h1L0ui4yjmkLmEudc4hra2gEyB9jz+RoYuPj1f9HXn/+vL3J2WVxfNCR4RUGSna1JmZmWHl8pXIP5WP5G+TqyTBJSklSP42Gfmn8rFy+coa58RL9T0mVTIuVWPF3bt3oRSB9wNNVPfOqA1FCF1fhNEbi1T30PS+JlCKQHp6eq1x63NEcnOkdVIfFxeH6Oho/PDDD5g7dy4++ugjtQfVTarqpFIzNzdX9cr/8ccfuHTpEnbu3ImtW7eirKwMQUFBsLa2xv79+3Hw4EFVclx5zBdffIEVK1Zg2bJlOHDgADIzM+usHDp+/Hj89ttvWLx4MS5cuIAff/wRVlZW8PT0xKZNmwAAly5dQkpKCr7++utqzxEeHo7jx48jNjYWhw8fhiiKGDJkCMrKylT7FBYW4vPPP0dkZCT27duHpKQkvPfeewCA8vJyhISE4PHHH8fff/+Nw4cP45VXXoEgsDhac1NcpsBvR5MBABP7tdZvMET/eHugN0zkAs6n5GLcL9ol0VIRRRHJmYWI+zsF/xdzBjM2nUHl345KEfgg6qxGjQ1SzSFtrOtNE+lTU11fXkpDhw5FdHQ05DfluDLzChI/SUTS90lI/CQRV2ZdgfymHDExMRg6dGiN55Dqe0yqZFyqxopvvvkGvh19MPjXQhxIKlcVxWsxtAW2Xi3H6I1FOJBUjsG/FsK3ow+++eabGq+9MYxIbm60rn7v6elZ5zp5VDspq5NKQRRF/PHHH4iPj8ebb76Ju3fvwtLSEr/88gtMTCrmE//6669QKpX45ZdfVMnu8uXLYWdnhz179mDQoEGIiIjArFmzEBoaCgBYsmRJra3Aly9fxvr167Fz504MHDgQANSKMDo4VAwzcnZ2hp2dXbXnuHLlCmJjY3Hw4EH07dsXALB69Wp4enoiJiYGo0ePBgCUlZVhyZIlqqFCU6ZMwccffwygYg3InJwcPPvss6rnfX19tX8jyeBt/TsFmQWlcLc1w0AuY0eNhEIpokzx7x98ShGYuekM7hWUoquHHVo5WsDN1lyyVRpEUURabgn+vpWNv2/l4O/bOThzKxtZhWU1HqMQRSRmFMLN1rzWc0s1h1SqqtFETUlERAQunj+H4LXHETcWqvXlZ8+ejc8+XYQxm0pU68v3DfBHRESEvkPWi2HDhuHOrTvYuHEjoqOjK6rWezhgxJwRGDVqVJ1V66X6HqtMxkNCQpD8bXLVdepTSpC2oWKd+piYmFrjqmysCJ8Ujiszr8DKxwoyOxmU2UrkX86HvaN9nY0V1tbWSDh6HP69e6H/8suQCYCJmxlK0kpg4myGrZeKEXuxHL4dfZBw9HiNU2EfHJH8+eFyhI4IwfQZM/HZp4swpL0M7wZYIHhtxYhkQ1oWsTHTOqn/4osvMH36dCxZsgStW7fWQUhNX2V10tARIRizqUQ1ROr+JSO0qU76sLZu3QorKyuUlZVBqVRi3LhxmDt3Lt544w34+fmpEnoAOH36NK5evVrlH11xcTGuXbuGnJwcpKSkwN/fX/WckZERevXqVWUIfqVTp05BLpfj8ccff+hruHDhAoyMjNRe19HRER06dMCFCxdU2ywsLNTm/ri5uamGDTk4OCA8PBxBQUF4+umnMXDgQISFhcHNze2h4yLDI4oiVhy6AQB4IbAVjORaD2Qi0okbGQV48FtUBPDZ9n+L55nIZfBwMEdrR0u0crRAa0dLeP3zXw97cxjfdz+n5BThRkYB2jhZws3WHBn5JThzK6cigb+Vjb9v5+BuXtXhoMZyAR1dbdCuhSU2n7qjFpNcENDayaLOa3Gwd4DithZzSD2qn0Mq1RJORE1J5TJ0gwc9jf7LE2BibISo6BgEBwcjICAAoSNCEHOhEH0D/Jt9ImVmZoYXXnjhob4XpPoeA6RJxivVt7EC+CexP3Ycb775JpydnXHt2rWK8wQ4oF27dkhPT8c333xT671TOSJ5/0QLPOplhD4t5QjbWIIFCxYgxNdElffEjQX6L68Ykbx06dI6Y6PaaZ3Uv/DCCygsLES7du1gYWEBY2NjteczMxtXIZ/GqrI66YIFCxB3Wa5K6IF/q5POnj1bp9VJBwwYgB9++AEmJiZwd3eHkdG/t4OlpaXavvn5+ejZsydWr15d5TwtWrR4qNc3N6+9R0dKD96ngiCoNTYsX74cb731FrZv345169Zh9uzZ2LlzJwICAhosRtKvk0lZOHs7FyZGMozt7aXvcIhU2jhZQiYA94/OFAD0beeI1NxiJGcWoVShxPW7Bbh+t6DK8XKZgJZ25mjlaIEyhRIJ1zNVCbmtuRFyiqqueiKXCfB2tkIXD1v4edihS0tbdHSzhqlRRe9UYDtHfBB1FgpRhFwQ8Elo5zp76YGKOaRRUVEoSS2pNSFXzSGdU/0cUl2sNy2V+qxbTc1bXl5elXXhgYo5yJquC98U15dvbKT6HqskRTJeqT6NFZWsra2xYsWKhz6+sY1Ibi60Tuqb61AdqWlanTQgIEBnib2lpSXat2+v0b49evTAunXr4OzsXOP0Czc3NyQkJOCxxx4DUDFX/cSJEzWuiuDn5welUom9e/eqht/fr3KkgEJRc2uor68vysvLkZCQoBp+f+/ePVy6dAmdOnXS6Noqde/eHd27d8esWbMQGBiINWvWMKlvRlYcqiiMGNLNHQ6WXMaOGg83W3MsDPWrkkSP+afxSaEUkZJThKR7hUi8V4ib9wqQeK8AN+8V4ua9QhSVKZCUWYikzMIq565M6Nu1sERXDzv4ediii4ctOrnZwtyk5qR5TG8vPObTAokZhWjtZKFRQg9UzCF9+523kbY+DZ5TPKsdOq/JHFIpe8qkFBsbi/BJ4ci6lwUrHyvI7eRQ3FYgKioKb7/zNlYuX6lRjxs1P5VDlg8dScCvkatUPexxcXEIHRGC0rJyXDx/TqMe9sr15R8UFBSks9GfDaUxNJpJ9T12PymS8caisYxIbm60SurLysqwd+9ezJkzB23atNFVTE1eTdVJ4y6Xq1qw1o8yrShuMiIEsVu26v2Gf/755/G///0Pw4cPx8cffwwPDw/cvHkTUVFRmD59Ojw8PPD2229j0aJF8Pb2RseOHfHll19WWWP+fq1bt8aECRMwadIkLF68GF27dsXNmzeRnp6OsLAwtGrVCoIgYOvWrRgyZAjMzc1hZWWldg5vb28MHz4cL7/8Mn788UdYW1tj5syZaNmypcarMdy4cQM//fQThg0bBnd3d1y6dAlXrlzB+PHj6/OWkQFJyy3G72cqVkPgMnbUGNWWRMtlAjzsLeBhb4G+D7TTiqKIu3klSLxXiF0X0vDTvutVzr1sQi88+RA1JNxszTVO5itJNYdU6p4yKVRW47fqZgXv973Vryu1BGnr0xASEoLo6GgMGzZM5/GQ4eAcZM00lkYzKefCN1WNYURyc6PVpFFjY2NVRXJ6eIZYndTCwgL79u2Dl5cXQkND4evri8mTJ6O4uFjVc//uu+/ixRdfxIQJExAYGAhra+sal9+o9MMPP2DUqFF4/fXX0bFjR7z88ssoKKgYPtqyZUvMmzcPM2fOhIuLC6ZMmVLtOZYvX46ePXvi2WefRWBgIERRxLZt26oMua/t2i5evIiRI0fCx8cHr7zyCt544w28+uqrWrxDZMhWH7mJcqWI3q3t8Yi7rb7DIaqWm605Ats5apVIC4IAZxsz9GnjgIn9WuPBDiW5IMDXvWGL30pRfVqqqtH3Ky4uRmRkJEaOHIkBTw7AyJEjERkZqVHlfFbjp/porKsiNSaNbQlLKb7HmjJNRyRXVsWn+hPEmqqY1WDChAno1q0b3nnnHV3F1Kjk5ubC1tYWOTk5VYadFxcX48aNG2jTpo1WrXD3t8jGjTVVVSdVb5GtqE7auWuvZtsi21g97OdOjVNJuQL9Fu1GRn4pvh3XHc92cdd3SEQ6s+5YUo3D+BtacXGx+hxSeweMGKH5HNItW7YgJCQEVt2s6uwpq+sP62p7ALMVqkJVdfUARkZGYvz48fBe5F3nyIErs64gMjKyzmG2jWGYcWOOpymJj4/HsKHP1jqC8/4hy5qM4GxKn1dxcTHcPdyhaKWodbh78rfJkN+U486tOw12jfX9HmuKdHE/N1e15aEP0jqpX7BgAb744gs89dRT6NmzZ5WCam+99Zb2ETdiukjqAfW5U/dXJ71/7hSrkzZOTOqblui/buGddafhamOG/TMGqFUJJ2qKUnKKtJ4L31g9mIw/WDVak+G49w+br9I48M+w+fxT+bUOmx85ciR2nN2B1h+0rjPmxE8SMajzoFpHPta3kUFqjS2epqjy77/7E6FKD85BrmvIclP7vHTRaEa6M3nyZCxbtkxV/b7y/t18sVSt+v2BpHL0X16ISZMmsfp9DXSa1Nc2l14QBFy/XnW+niHTVVIPSFPllBoek/qmZfh3B3E6ORvvDfLBlCe99R0OUbMg5f//6tNTJlUP4IAnB+Cvgr/g+bpnnfEmfZ+EHpY98OfuP6t9XopGBilJHU9T6kGW2pw5c7BgwQJEhZmrzUGOvlCG0PVFmD17NubPn1/rORrb/VOpPp+71I1mpFsckSwdnSb1zY0uk3oyTPzcm46/krIw4vtDMJHLcGjWk3Cyqn3NayKqv8Y0Uk2qHkCpko7GNsxY6niaWg+ylKToqdfF/SNFI0x9P3cpG82oYUj5Pd+cO0G1SerrNc5UFEWwTYCIDNXKQ4kAgGe7ujGhJ2oAD1b5fqadDKEjQjBnzhxVQrN/ogXOnq6o8p2Xl6fTeGJiYmDlY1VrQg8Apm6msPKxQnR0dLXPh4SEIP9yPkpSS2o9j6oafw1FZDds2ICse1lwCXOpNiEDAEEmwGW0C7LuZWHjxo21vl59SRlPYyt01pjUtCpS9IUyVfHkyuJ5oSNCEB8fX+15pL5/YmNj4e7hjvHjx2PH2R34q+Av7Di7A+PHj4e7hzu2bNlS57VJ8bk72DtAka3FEpb2DbOEJdXM2toa23fsxIQJE/DW21OxbNkyDHhyAJYtW4a33p6KCRMmaJzQDx70NJYtW4ZhQ59VFdaLi4vDsKHPYtmyZQ3y/wpD8FBJ/apVq+Dn5wdzc3OYm5ujS5cuiIyMlDo2IiKdSc8rRtw/y9iFcxk7ogbR2Kp8Z2ZlQm4n12hfmZ0MmVmZ1T4nVTV+qRoZpCJVPFwdoHZSrYok5f0jRTIu1ecuVaMZNaw///wTsVtj8fnnn6s1Cn3++eeI3RqLPXv21Hp8Y2sEbuy0Tuq//PJLvPbaaxgyZAjWr1+P9evXY/DgwfjPf/6Dr776ShcxNnocrdC88PNuGtYkJKFMIaKHlx26eNjpOxyiZiEsLAwmxkb44ki5Wg9kVJi5Wg/l54fLYWJshLCwMJ3GI1UPYOW61fmn8pH8bXKV5KMkpQTJ3yYj/1Q+Vi5fWeOwZakaGe5Xn6X6pIpHFyMQ6nNdjU1ERAT6BvgjeG0JDiSVY/SGYmy9XIZWrVphy6UyhG0sxoGkcgSvLUHfAH9ERERUex6pPi+pknGpPnddLGFJuiVFo1BjawRu7LRO6r/55hv88MMP+PTTTzFs2DAMGzYMn332Gb7//nssXrxYFzE2WpXroBcWFuo5EmpIlZ935edPhqe0XInVCUkAgAnspSdqMEFBQYiKjsG2q0q1HsgRvsZVljmKio7R+TJHUvYASrFutdTDjOs7fFqqeKQegSDFsPDGpHKockuvdui/vBBbL5fB2NUU2S7ZMHY1xZZLZei/vBAtW7WrdciyVJ+XVMm4VJ+7VI1m1DCkahRqbI3AjZ2RtgekpKSgb9++Vbb37dsXKSkpkgRlKORyOezs7JCeng4AsLCwgCBU/+VHhk8URRQWFiI9PR12dnaQyzVrDafG5/ezKbibV4IW1qZ4prObvsMhalaCg4MxfcZMLFiwAHGX5WpVvuMul2PzxVLMnj27zmW7pDB69Gi8/c7bSFufVmthMU17AIcNG4Y7t+6oV+P3cMCIOZpV4w8JCUFUVBRKUkvqLNyXfzkfI+bU3MhwfxV07/e9q62CHhISUmsVdKnikXIEghTX1Rj9+eefuHj5CowdjdFieAs4PPZvwp25LxN3N9/FxUtX8Oeff+r883qYZLy6ApJSfu6VjWbhk8JxZeaVapewrKvRjBpGZaOQ9/vedTYKXZl1BRs3bqz2/qlsBA4dEYIxm0pUiXzl/zMauhG4sdO6+n3nzp0xbtw4fPDBB2rbFyxYgHXr1uHMmTOSBqhvdVUdFEURqampyM7ObvjgSC/s7Ozg6urKBhwDFvr9QZxMysbUgd6YOtBH3+EQNStSrscthS1btiAkJKT6JcBSSpC2oWIJsIZIGKSqXt7YztNUVweQSmP7vKSqNq+Lpejqs4QlNQypP3cplno0VNpUv9e6p37evHkYM2YM9u3bh379+gEADh48iD/++KPGwh1NmSAIcHNzg7OzM8rKyvQdDumYsbExe+gN3N+3snEyKRvGcgHj/L30HQ5Rs1JTle+4y+UI9jFSDa8M21iC0BEhiN2yVee9L42pB7BymHFISAiSv02us5GhpiRGqp4yqeKRqgdZquuSWn2X3Gpsn5eDvQMUt7UYxu9R/TB+KUeeVDIzM8MLL7zQIJ8rPRwpR2jExcXhs08XIcTXBME+6mlrsI8Rhnc0wWefLkJAQECDNAI3Zlon9SNHjkRCQgK++uorxMTEAAB8fX1x9OhRdO/eXer4DIZcLmeyR2QAVvyzjF2wnxucrdmqT9SQ/q3ybaE2h37zxVKE+JqoEv33Ao2w+WIh1q9f3yBDKus7bF5KUjQySDV8Wqp4pJrmIOV1SeX+9bh/jVxV7XrcF8+fq3UufGP7vKRKxqWe3kKGQapGIakbgZv6evcPtaRdz5498euvv+LEiRM4ceIEfv3112ad0BORYcjIL8HW0xW1P1ggj6jhPVjlu3Ko/ezZs1XF8zSp8q0LlT2AmzZtwp+7/8SmTZvwwgsv6GVIb2UjQ2RkJAZ1HoQelj0wqPMgREZG4s6tO3WOGpC6in5942nMqwPUh1RLbjW2z0uqavMscNc8SVWAVKqlHoHmsd691nPqAUCpVOLq1atIT0+HUqlUe+6xxx6TLLjGQJu5DETUuH27+wo+33EZXT1ssXnKo/oOh6hZur9n08TYqNqezb4B/rX2bFLtdDGXWQqxsbEInxSOrHtZ1fYgr1y+staEs7Fd1+TJk7Fs2TLsn2iBR72Mahx5ciCpHP2XF2LSpElYunRplfM0tusCpK01Ud/PnQyLVLUd7m80ixtris8Pl+P3a0pMnzETn326CEPay/BugBGC15agc9deNf4/Q6rz6IM2eajWPfVHjhxB+/bt4evri8ceewxPPPGE6jFgwICHDpqISJfKFEpEHrkJAAjv11q/wRA1Y5XLd02aNAmxW7aq5kEGBwcjdstWTJo0SeM/qvLy8jB58mTEx8erbY+Pj8fkyZMNutelPqRcqk9K9e1BbmzXJdWSW43tugBplmisVN/PnQyLVCM0Kv9f0blrL/RfXohtVxXo2as3Dhw8gJ69eiPuigL9lxfWmYg3l/Xute6p79atG3x8fDBv3jy4ublVqQBua2sraYD6xp56oqZh6993MGXNX3CyMsHBmU/C1Ig1MIgMGXv8a8Yq8Q13XVKs5tAYr+v+2Fhtnh6GVCM01q5diwnhE1BaUgorHyvI7eRQZCuQfzkfJqYmWLVyFcaMGVPj8fHx8Rg29Nla5+bf/2+1IQq0akqbPFTrpN7S0hKnT59G+/bt6xWkoWBST9Q0jF5yCMcSs/DWk+0xbVAHfYdDRPVgyMMpG0pjWqpPSo3xuqRYcqsxXhdRfdW3USg2NhYjRoyo/t9FagnS1lf8u4iOjsawYcNqPE9jW0pVUzpN6p988klMnz4dgwcPrleQhoJJPZHhO3s7B89+cwBGMgEHZz4JFxv2LhAZMqnmMjd1TXUuc2O6LimThcZ0XUT6JvUIFkNc716nSX10dDRmz56N999/H35+fjA2NlZ7vkuXLtpH3IgxqScyfO9vOI0NJ25haFd3fPMcV+ogMnSGPJyyoTXV4dON4bp0cR82husiagwiIyMxfvx4eC/yrnNpxSuzriAyMrLGpR7ZU18NmaxqbT1BECCKIgRBgEKh2bqEhoJJPZFhyywoRcDCP1BarsSm1wLRs1X166ESkWEx1D/SqOngiBEi3ZFqVQhDbgTWafX7GzduVHlcv35d9V9d++6779C6dWuYmZnB398fR48erXHfFStWQBAEtQdbOYmal7XHklBarkTnljbo4WWv73CISCLBwcGYPmMmYi6UIu5yudpzcZfLsfliKabPmKlRQs8q+vQwIiIi0DfAH8FrS3AgqVyVFMyePRvbrioxZlPF9uC1Jegb4I+IiAh9h0xkMDKzMiG306yoscxOhsyszGqfk3K9+8bMSNsDWrVqpYs4NLJu3TpMmzYNS5Ysgb9/xZdjUFAQLl26BGdn52qPsbGxwaVLl1S/P1itn4iaruTMAizdX9HYOCGwNf/9EzUhcXFx+OzTRQjxNUGwj/qfM8E+Rhje0QSffboIAQEBtSb291fR/zVyVbVV9C+eP9csi+1R7SqX3Bo86Gn0X66+CkNAQABCR4Qg5kJhs12Fgag+HOwdoLit2QhwZbYSDh7Vj8SMiIjAxfPnELz2OOLGQlVYdfbs2fjs00UYs6lEVVjVkBvfNOqpj42NRVlZmcYn3bZtG4qKih46qJp8+eWXePnllzFx4kR06tQJS5YsgYWFBZYtW1bjMYIgwNXVVfVwcXGRPC4ianzWHUvCY5/twb2Ciu+uknKlniMiIqnEx8dXGXpfqhARfaFMbb3wZ9rJEDoipEoPfKX7q+jvn2ih2n/OnDmq8++faIGzp49j8KCn2WNPVVQm9pMmTULslq2qBqTg4GDEbtmKSZMmMaEnegghISHIv5xfZZ37B5WklCD/cj5GjBhR7fMPrndfOS1r/vz5iIqOwbarSo3Wu2/sNErqR4wYgezsbI1POnbsWKSkpDxsTNUqLS3FiRMnMHDgQNU2mUyGgQMH4vDhwzUel5+fj1atWsHT0xPDhw/HuXPnan2dkpIS5Obmqj2IyLCk5BRhVtQZ3F8w5KPN55CSI31jIxE1PKmGU06dOhWHjiQgbqwpHvUyUjUELFiwQNVg8KiXEeLGmuLQkQRMnTq1YS+UDIK1tTWWLl1aZR5uUFAQli5darBJApE+jR49GvaO9khbnwZRWX0JOFEpIm1DGuwd7TFq1Kgaz9UcGt80Gn4viiLCw8Nhalpz5cH7FRcX1yuo6mRkZEChUFTpaXdxccHFixerPaZDhw5YtmwZunTpgpycHHz++efo27cvzp07Bw8Pj2qPWbhwIebNmyd5/ETUcG5kFODB73+FKCIxoxButub6CYqIJCPVcMqwsDD8GrkKXxwpR5+WclUPf9xluVoBpc8Pl8PE2AhhYWENe6FERM2UmZkZVi5fiZCQECR/m1x1nfqUEqRtqFinPiYmps66aZWNbw8KCgpqNIXx6kOj6vcTJ07U+sT/+9//4OTk9FBBVefOnTto2bIlDh06hMDAQNX26dOnY+/evUhISKjzHGVlZfD19cVzzz1X4zqEJSUlKCn5d5hHbm4uPD09Wf2eyIBcSMnFM1/vV9smFwQcmDmAST1RE3H/XPj75zLfPxdek7nMrKLffOXl5WHq1KkICwtT+6M+Pj4e69evR0REhEH33BE1BbGxsQifFI6se1mw8rGCzE4GZbYS+ZfzYe9oj5XLV2Lo0KH6DlMntKl+r1FP/fLlyyUJrD6cnJwgl8uRlpamtj0tLQ2urq4ancPY2Bjdu3fH1atXa9zH1NRU4xEJRNQ4/bL/htrvckHAJ6GdmdATNSGVwykfTMoqh1NqmpRVVtFfsGAB4i7LMcLXWPVcZRX92bNnM6FvYlggkcgwDBs2DHdu3cHGjRsRHR2NzKxMOHg4YMScERg1ahRXNvuH1uvU65O/vz/69OmDb775BgCgVCrh5eWFKVOmYObMmXUer1Ao8Mgjj2DIkCH48ssvNXpNrlNPZFgOXcvAuJ8TIAjAjy/2hLWpMVo7WTChJ6JqSdlTz55fw3B/gcS4saaq6RvTZ8zEZ58uwpD2MtX0DUMvnkVEhkun69Tr07Rp0/Dzzz9j5cqVuHDhAl577TUUFBSopgeMHz8es2bNUu3/8ccfY8eOHbh+/TpOnjyJF154ATdv3sRLL72kr0sgIh0qLlNgdvRZAMAL/q0wqJMrAts5MqEnompJVUUf+DdRXLZsGYYNfRZxcXEAKhoNhg19FsuWLWMF/UaCBRKJqKkxqKR+zJgx+Pzzz/Hhhx+iW7duOHXqFLZv364qnpeUlKRWdT8rKwsvv/wyfH19MWTIEOTm5uLQoUPo1KmTvi6BiHTo+z3XcD2jAC2sTfH+4A76DoeIGjmpquhzaTzDEhYWBhNjI3xxpFyt8SYqzFytcYcFEonIUBjU8Ht94PB7IsNwNT0fz3y9D2UKEd+N64HgLm76DomIGjmphmFPnjwZy5Ytw/6JFnjUy0jVOLD5YilCfE1UieKBpHL0X16ISZMmVVuFmRoOCyQSNT/FxcXYsGEDYmJiKubm2zsgJCQEo0ePbpRz85vs8HsiouqIoogPos+gTCHiyY7OGOKnWfFMImreKovtde7aC/2XF6qSuPnz5yMqOgbbrirRf3lhnfOq2fNreCoLJMZcKEXc5XK15yoLJE6fMVPjhL64uBiRkZEYOXIkBjw5ACNHjkRkZKROlnkmIu3FxsbC3cMd48ePx46zO/BXwV/YcXYHxo8fD3cPd2zZskXfIdaL1j31N27cwP79+3Hz5k0UFhaiRYsW6N69OwIDAxtlC0d9saeeqPFbfywZ0zf9DXNjOXa88xg8HSz0HRIRGRApCtyx59ewSPl5PbjkltxODkW2olksuUVkCGJjYzFixAhYdbOqut59agnS1lesdx8dHY1hw4bpMVJ12uShGif1q1evxtdff43jx4/DxcUF7u7uMDc3R2ZmJq5duwYzMzM8//zzmDFjBlq1aiXJhTQGTOqJGreM/BI89cVe5BSV4YMhHfHKY+30HRIRNVNz5szBggULEBVmrrY0XvSFMoSuL8Ls2bMxf/78Os/DKvq6FR8fj2FDn8Uz7QSsH2WmGkkRd7kcwT7/1lcYvaEY26+LiN2yVe1zuJ+hJgtEzUVxcTHcPdyhaKWA5xRPCDKhyj6iUkTyt8mQ35Tjzq07jaajWvLh9927d8fixYsRHh6OmzdvIiUlBSdOnMCBAwdw/vx55ObmYvPmzVAqlejVqxc2bNggyYUQEdXlk7gLyCkqg6+bDSb1a6PvcIiomYqLi8Nnny5CiK8Jgn2M1J4L9jHC8I4m+OzTRaqq+DVhFX3dqyyQ+F6gsSqBH7WhCKHrizB6Y5FqCsX7fY1rLZBYXFyM8EnhsOpmBc8pnmoJPQCYuprCc4onrLpZIXxSOIfiE+nBhg0bkHUvCy5hLtUm9AAgyAS4jHZB1r0sbNy4sYEjlIZGSf2iRYuQkJCA119/HZ6enlWeNzU1xRNPPIElS5bg4sWLaNu2reSBEhE96ODVDET9dRuCACwM9YORnGVCiKjhSbU0HqvoN4xFixbBxFiOwasLcSCpHKM2FCHuWjlaDG2BrVfLMXpjEQ4klWPw6kKYGMuxaNGias/TXJIFIkMWExMDKx+rKo1uDzJ1M4WVjxWio6MbKDJpafQXcE1Djqrj6OiInj17PnRARESaKC5T4P+izwAAxge0QjdPO/0GRETNllRL43H9dM3k5eVh8uTJVRpH4uPjMXny5DobO7Zv347SMgXgZob+ywsRd60cnlNawWWkCzyntMLWqxWrFMDVDKVlihobYZpLskBkyDKzMiG3k2u0r8xOhsysTB1HpBsad2vduXMH7733HnJzc6s8l5OTg/fffx9paWmSBkdEVJPv/ryKxHuFcLExxXtBXJOeiPQnIiICfQP8Eby2BAeSylVF1mbPno1tV5UYs6lie/DaEvQN8EdERES152EV/bpJMT2hMhn3mtkGdv3t4Pl2K1h3q6hRYN3NGp5vt4Jdfzt4zWpTazLeXJIFIkPmYO8ARbZCo32V2Uo42DvoOCLd0Dip//LLL5Gbm1vtJH1bW1vk5eXhyy+/lDQ4IqLqXEnLw5K91wAA84Y9Amsz4zqOICLSHamWxgsKClLtf38P/whfY7URAJXn12YkZVMg1fSEymRcbi6Hx2QPWPupfx7WftbwmOwBubm81mS8uSQLRIYsJCQE+ZfzUZJaUut+JSklyL+cjxEjRjRQZNLSOKnfvn07xo8fX+Pz48ePx9atWyUJioioJkrlv2vSD/R1RtAjXJOeiPSvMrGfNGkSYrdsVS2DFhwcjNgtWzFp0qRaE/pKUq+f3pRINT1BqmS8uSQLRIZs9OjRsHe0R9r6NIjK6hd9E5Ui0jakwd7RHqNGjWrgCKWhcVJ/48YNeHl51fi8h4cHEhMTpYiJiKhG648n41hiFixM5Jg3vDMEofriREREDc3a2hpLly6t0oMeFBSEpUuXarQMnVRV9IH6zz1vbKSaniBVMt5ckgUiQ2ZmZoaVy1ci/1Q+kr9NrvLvviSlBMnfJiP/VD5WLl/ZaJaz05bGSb25uXmtSXtiYiLMzc2liImIqFp380rwybYLAIBpT/ugpR2/c4io6ZCqij7QOJfGq28jg1TTE6RKxptLskBk6IYOHYro6GjIb8pxZeYVJH6SiKTvk5D4SSKuzLoC+U05YmJiMHToUH2H+tA0Tur9/f0RGRlZ4/OrVq1Cnz59JAmKiKg6/407j9zicnRuaYPwvq31HQ4RkaSkqqIv9dJ4UvT4S9XIIMX0BCmT8eaQLBA1BcOGDcOdW3cQGRmJQZ0HoYdlDwzqPAiRkZG4c+uO4f8bFTW0e/duUS6Xi++++66Ympqq2p6amipOmzZNlMvl4h9//KHp6QxGTk6OCEDMycnRdyhEzdq+y+liqxlbxTYzt4p/J2frOxwiIsnl5uaKfQP8RRtzubh/ooU4vKOJaGJsJM6ePVs0MTYSQ3xNxP0TLUQbc7nYN8BfzM3NrfY8kyZNEgGI+ydaiOJHNmLJbGtxeEcTEYAY4msilsy2FsWPbMT9Ey1EAOKkSZPqjAmAaGJsJG7dulUURVHcunWraGJsJAKoNRYpr+v+173/Oiofldd5f5y12bx5s2jvaC8CEK18rESbPjailY+VCEC0d7QXY2Nj6zxHpaKiIjEyMlIMDQ0VnxjwhBgaGipGRkaKRUVFGp+DiOh+2uShgiiK1Y87qsaPP/6It99+G2VlZbCxsYEgCMjJyYGxsTG++uorvPbaazpodtCv3Nxc2NraIicnp9rK/0Ske8VlCgz6ah+SMgsxsV9rfDT0EX2HRESkE5U92oeOJMDE2AhR0TEIDg5GXFwcQkeEoLSsHH0D/GstuhcfH49hQ5+tMow/7nI5gn2MqgxVj92ytdqh6vf3+MeNNcXnh8vx+zUlps+Yic8+XYQh7WV4N8AIwWtLaq3sP3nyZCxbtgz7J1rgUS8j1WtvvliKEF8TVYwHkirWh580aRKWLl2qs+u6X3FxMTZu3Ijo6GhkZmXCwd4BI0aMwKhRozhcnoj0Sps8VKukHgBu376N9evX4+rVqxBFET4+Phg1ahQ8PDzqFXRjxaSeSP/+F38R3/15Da42Ztj17uOwMjWq+yAiIgOVl5eHqVOnIiwsTC0pjY+Px/r16xEREVFn0b3KRoD7E+BKD849r2moemNLxqWKh4jIEOg0qW9umNQT6dfltDwM+Xo/ypUifnyxJ5ewIyLS0Jw5c7BgwQJEhZljhK+xanv0hTKEri/C7NmzMX/+/BqPl7JnXIpGBqlGDhARGQKdJvWxsbHVn0gQYGZmhvbt26NNmzbanLJRY1JPpD9KpYjRPx7GiZtZGNTJBT+N76XvkIiIDIIUSbSU5wHq38gASDM9gYjIEOg0qZfJZBAEAQ8eVrlNEAQ8+uijiImJgb29vfbRNzJM6on0Z01CEj6IPgNLEzl2Tnsc7lzCjoioTlLPPZciGZeycUCK6QlERI2dNnmoxkvaVdq5cyd69+6NnTt3IicnBzk5Odi5cyf8/f2xdetW7Nu3D/fu3cN777330BdARJSeV4xFv1esSf/uoA5M6ImINCTV0nhARTL+2aeLEOJrgmAf9XomwT5GGN7RBJ99uki1RF114uPjqyT0pQoR0RfKVLGsH2WqWnrvwaXzHmRtbY2lS5dWaYgICgrC0qVLmdATUbOjdVL/9ttv48svv8RTTz0Fa2trWFtb46mnnsL//vc/vP/+++jXrx8iIiKwc+dOXcRLRM1ASk4Rpq49hdzicvi1tMUErklPRKSxiIgI9A3wR/DaEhxIKlf1gs+ePRvbrioxZlPF9uC1Jegb4I+IiIhqzyNVMi5lIwMREVWldVJ/7dq1arv/bWxscP36dQCAt7c3MjIy6h8dETU7644loe+i3Th07R4AYECHFpDLhDqOIiKiStbW1ti+Yyc6d+2F/ssLVcPa58+fj6joGGy7qkT/5YV1FpOTKhmXqpGBiIiqp3VS37NnT7z//vu4e/euatvdu3cxffp09O7dGwBw5coVeHp6ShclETULKTlFmBV1BveX7Pjuz2tIySnSX1BERAaoMrGfNGkSYrdsVc1TDw4ORuyWrZg0aVKdxeSkSsalamQgIqLqaV0o79KlSxg+fDhu3LihStyTk5PRtm1bbN68GT4+PoiJiUFeXh5efPFFnQTdkFgoj6jhHLqagXG/JFTZ/tvLAQhs56iHiIiImjcpq82zwB0RkeZ0vk69UqnEjh07cPnyZQBAhw4d8PTTT0Mm07rjv9EzlKQ+JacINzIK0MbJEm62LChGhmnZgev4eOsFtW1yQcCBmQN4XxMR6QmTcSKihqfzpL5ScXExTE1NIQhNd76rIST1644lYeamMxABCALwyQg/PNfHS99hEWnl5r0CDPl6PwpKFRAAiKhI6D8J7YwxvXk/ExEREVHzoU0ealTrs9VQKpX473//iyVLliAtLQ2XL19G27ZtMWfOHLRu3RqTJ09+6MBJe6o5yP/8LorArKgzOHDlLoZ2bYn+3k6wNNX6YyZqUGUKJd5eewoFpQr0aeOAL8O6IjmzCK2dLNhDT0RERERUC63Hyy9YsAArVqzAZ599BhMTE9X2zp0745dffpE0OKrbjYwCKKsZaxF3JhX/+fUEus/fifDlR/HrkZssNkaN1uI/ruBUcjZszIzw1Zhu8LC3QGA7Ryb0RERERER10DqpX7VqFX766Sc8//zzkMvlqu1du3bFxYsXJQ2O6tbGyRIPrvYlE4AxvTzh5WCB0nIl9ly6i9kxZxG4cDee/WY/InZdxtnbOajHzAsiyRy9kYnv/rwKAPgk1A8t7ZjIExERERFpSutx2bdv30b79u2rbFcqlSgrK5MkKNKcm605Fob64YOos1CIotocZFEUcTU9HzsvpOGPC+k4mZSFs7dzcfZ2LiJ2XYGbrRme7OiMgZ1cENjWEWbGchbcowaVU1SGd9adglIERvX0wLNd3PUdEhERERGRQdE6qe/UqRP279+PVq1aqW3fuHEjunfvLllgpLkxvb3wmE8LJGYUqs1BFgQB3i7W8HaxxutPtEdGfgn+vJiOXRfSsP9KBlJyirE6IQmrE5JgYSJHGydLnL+TCxEVvf0LQ/1YoIx0RhRF/F/0GdzOLkIrRwvMHfaIvkMiIiIiIjI4Wif1H374ISZMmIDbt29DqVQiKioKly5dwqpVq7B161ZdxEgacLM1r7Nn3cnKFKN7eWJ0L08Ulylw+Po97Dpf0YufmluMc3dyVfsq/ym495hPC/bYk05sOnkbW/9OgZFMwNdju8OKBR2JiIiIiLSm9Zz64cOHY8uWLdi1axcsLS3x4Ycf4sKFC9iyZQuefvppXcRIOmBmLMeADs747wg/HJ71JD4Z0bnKPkoROHztnh6io6YuMaMAH20+CwB452kfdPO0029AREREREQG6qG6xvr374+dO3dKHQvpiSAIGNDRGTIBVSrpz4r6G/kl5XgxoBUEQaj+BERaKFMo8fa6iuXr/Ns44D+Pt9N3SEREREREBkvrnnpqmioL7sn/SdxlAtDe2RIl5SI+3HwO45cd5ZJ4JImvd13B6fuWr5M/uHwDERERERFpTKOk3t7eHg4ODho9dO27775D69atYWZmBn9/fxw9erTW/Tds2ICOHTvCzMwMfn5+2LZtm85jNFRjenvhwMwB+O3lAByc+SR2TH0cc4d2gpmxDPuvZGDQV/sQ89dtLoVHDy3h+j18t6di+bqFoV3gzuXriIiIiIjqRaPh9xEREaqf7927hwULFiAoKAiBgYEAgMOHDyM+Ph5z5szRSZCV1q1bh2nTpmHJkiXw9/dHREQEgoKCcOnSJTg7O1fZ/9ChQ3juueewcOFCPPvss1izZg1CQkJw8uRJdO5cdQ45VS24F96vDfr7tMC09adxOjkbU9edwo7zqVgQ4gcHSxM9RkqGJqewYvk6UQRG9/RAcBc3fYdERERERGTwBFHLbteRI0diwIABmDJlitr2b7/9Frt27UJMTIyU8anx9/dH79698e233wIAlEolPD098eabb2LmzJlV9h8zZgwKCgrUqvIHBASgW7duWLJkiUavmZubC1tbW+Tk5MDGxkaaCzFA5Qolvt9zDYv/uIJypYgW1qb4dKQfnuzoou/QyACIoogpv/2FuL9T0NrRAnFv9Yclq90TEREREVVLmzxU6zn18fHxGDx4cJXtgwcPxq5du7Q9ncZKS0tx4sQJDBw4ULVNJpNh4MCBOHz4cLXHHD58WG1/AAgKCqpxfwAoKSlBbm6u2oMAI7kMbz3ljejX+8Hb2Qp380owacVxVSE9otpsPHELcfctX8eEnoiIiIhIGlon9Y6Ojti8eXOV7Zs3b4ajo6MkQVUnIyMDCoUCLi7qPcMuLi5ITU2t9pjU1FSt9geAhQsXwtbWVvXw9PSsf/BNiJ+HLba8+SheerQNBAH47Wgynvl6H47eyNR3aNRIJWYU4KPYcwAqlq/ryuXriIiIiIgko3V32bx58/DSSy9hz5498Pf3BwAkJCRg+/bt+PnnnyUPsKHNmjUL06ZNU/2em5vLxP4BZsZyzH62E57ydcF7G04jObMIY346jFf6t8U7T/vAzFiu7xCpkShTKPH22r9QyOXriIiIiIh0Quue+vDwcBw8eBA2NjaIiopCVFQUbGxscODAAYSHh+sgxApOTk6Qy+VIS0tT256WlgZXV9dqj3F1ddVqfwAwNTWFjY2N2oOqF9jOEdun9kdYLw+IIvDjvusY/u1BnLuTg5ScIhy6lsFl8Jq5r3ZexulbObA1N+bydUREREREOqB1oTx98vf3R58+ffDNN98AqCiU5+XlhSlTptRYKK+wsBBbtmxRbevbty+6dOnCQnkS23k+DbOi/kZGfinkAqAUAREV690vDPXDmN5e+g6RGtjha/cw7pcjEEXg++d7YIgfq90TEREREWlC8kJ5BQUFWgWg7f6amjZtGn7++WesXLkSFy5cwGuvvYaCggJMnDgRADB+/HjMmjVLtf/bb7+N7du344svvsDFixcxd+5cHD9+vErlfqq/pzu5IH7qY3jcxwmKfxJ6oCK5/yDqLHvsm5nswlJMW1+xfF1YLw8m9EREREREOqJRUt++fXssWrQIKSkpNe4jiiJ27tyJZ555BosXL5YswPuNGTMGn3/+OT788EN069YNp06dwvbt21XF8JKSktRi7Nu3L9asWYOffvoJXbt2xcaNGxETE8M16nXE0coUrz5Wdc60QhSRmFGoh4hIH0RRxAfRZ5CSU4w2Tpb4aOgj+g6JiIiIiKjJ0mj4/aVLl/DBBx8gLi4OXbt2Ra9eveDu7g4zMzNkZWXh/PnzOHz4MIyMjDBr1iy8+uqrkMubRrE0Dr/XTkpOEfot2g3lA3fVnveeQGsnS/0ERQ0mJacIyw8k4qf912EkE7Dptb6sdk9EREREpCVt8lCt5tQnJSVhw4YN2L9/P27evImioiI4OTmhe/fuCAoKwjPPPNNkkvlKTOq1t+5YEj6IOgvFfbfW4Edc8d3zPVgorQlbdywJs6LOqBp0Bnd2wZIXeuk3KCIiIiIiA6SzpL45YlL/cFJyipCYUYiM/GK8u/5vlCqUeK6PJz4Z4QdBYGLf1FQ3QkMmAAdnPgk3W3P9BUZEREREZIC0yUO1XqeeSBNutuaqZM5YLsPrq0/it6PJcLA0wftBHfUcHUntanp+lSkXShFIzChkUk9EREREpENar1NPpK3Bnd3w3xF+AIDv/ryGpQdu6DkikpIoilh3LKnKdrkgoLWThR4iIiIiIiJqPpjUU4N4ro8X3g/qAACYv/U8ok7e0nNEJJWv/7iCrX+nQkDFkHugIqH/JLQze+mJiIiIiHSMw++pwbz+RDtkFpRi6YEbeH/j37CzMMaTHV30HRbVw/rjyYjYdQUAMD+kM57ydUZiRiFaO1kwoSciIiIiagAa99R//PHHKCzkWuP08ARBwP8N8UVo95ZQKEW8vvokjidm6jssekj7Lt/FB1FnAFQ02LwQ0AputuYIbOfIhJ6IiIiIqIFonNTPmzcP+fn5uoyFmgGZTMCno7rgyY7OKC5TYtKKY7iYmqvvsEhL5+7k4LVfT6BcKSKkm7tqagURERERETUsjZN6rnxHUjGWy/DduB7o3doeucXlGL/0KJIzOQrEUNzOLsLE5cdQUKpAYFtHfDaqK5cpJCIiIiLSE60K5fEPd5KKuYkcv0zojY6u1kjPK8ELSxNwN69E32FRHXIKyxC+7CjS80rg42KFJS/2hIkR620SEREREemLVn+N+/j4wMHBodYHkaZszY2xalIfeDqY4+a9QkxYdhS5xWX6DotqUFKuwCuRx3ElPR8uNqZYMbEPbM2N9R0WEREREVGzplX1+3nz5sHW1lZXsVAz5GxjhshJ/hi15BDOp+Ti5ZXHsXJSH5gZy/UdGt1HqRTx/oa/kXAjE1amRlgxsQ/c7VgMj4iIiIhI3wRRw8nyMpkMqampcHZ21nVMjUpubi5sbW2Rk5MDGxsbfYfTZJ29nYPnfjqCvJJyPN3JBT883wNGcg7rbiwW/X4RS/Zeg5FMwPKJvdHfu4W+QyIiIiIiarK0yUM1zpo4n550qXNLW/w8oRdMjGTYeT4NH0SfYXHGRmLV4UQs2XsNAPDpyC5M6ImIiIiIGhFWv6dGI6CtI755rjtkArD++C0s2n5R3yE1ezvPp2Fu7DkAwLtP+2BkTw89R0RERERERPfTOKlXKpXNbug9NbygR1yxKLQLAODHvdfxefxFHLqWgZScIj1H1vz8lZSFN387CaUIjO3tiSlPttd3SERERERE9ACN59Q3V5xTrx9L9l7Dot//7amXCcDCUD+M6e2lx6iaj8SMAoz84RDuFZTiiQ4t8Mv4XqxxQERERETUQHQyp56oIQ3v5o77qzgoRWBW1BkkZRboLabm4l5+CcKXH8W9glJ0bmmD78axaCERERERUWPFv9SpUbqRUYAHh5AoReDZxQewcNsFXLubr5e4mrqiUgVeWnUcifcK4WFvjmXhvWFpqtXKl0RERERE1ID41zo1Sm2cLCETKhL5++UWl+PHfdfx477r6NPaAWN6e2KInxvMTbiufX2k5BThWnoBftp3DX8lZcPW3BgrJvaBs7WZvkMjIiIiIqJacE59HTinXn/WHUvCB1FnoRBFyAUB80MegZOVKdYdS8afl9JVCb+1qRGGd3fH2N5e6NzSVr9BG6B1x5IwK+qM6v2UywSsfSUAvVs76DcwIiIiIqJmSps8lEl9HZjU61dKThESMwrR2skCbrbmqu2pOcXYeCIZ644nIznz38r4j7jbYGxvTwzr1hK25sb6CNmgpOQUod+i3WojImQCcHDmk2rvNxERERERNRwm9RJiUt+4KZUiDl+/h7XHkhF/NhWlCiUAwNRIhmA/N4zp7Yk+bRyQmluMGxkFaONkyWT1HwUl5fh463msO5Zc5bnfXg5AYDtHPURFRERERETa5KGcU08GTSYT0K+9E/q1d0JWQSmi/7qNtceScDktH1F/3UbUX7fhZGWCe/mlEMGl8YCKYniRRxKxZO91ZBaUVnleLgho7WShh8iIiIiIiEhb7KmvA3vqDY8oijiVnI11x5IRc+o2isuUas8LArB72hNo08JSTxHqR3GZAqsTkvDDnmvIyC8BALRytIB/GwdsPHELSrEiof8ktHOzbvQgIiIiItI3Dr+XEJN6w7b7YhomrTheZbuZkQzBXdwR2qMlAto6Qi4T9BBdwyguU2Dt0SR8v+ca0vMqknkPe3O89ZQ3Qru3hJFcVmPtAiIiIiIiangcfk/0D183m2qXxisuV2LTyVvYdPIWXG3MMLybO0b0aImOrk2n4aakXIH1x2/hu91XkZpbDABoaWeON59sj5E9PWAsl6n2dbM1ZzJPRERERGSA2FNfB/bUG74Hl8ZbMKIz2jtbIerkbcT9fQe5xeWqfTu6WiO0R0sM69oSrraGuUZ7mUKJjSdu4dvdV3E7u2JlADdbM7wxoD3CennCxEhWxxmIiIiIiEifOPxeQkzqm4aahpeXlCvw58V0RP91G7svpqNMUfHPQRCAfu2cENK9JQZ3doWVqZHqPI2piv798ThZmSL65G0s3n0Ft7Iqknlna1O8MaA9xvT2hJmxXM/REhERERGRJpjUS4hJffORXViKuDMpiD55G8dvZqm2mxnLMKiTKxytTLDyUCKUYv2r6EvROLDuWBJmRZ2BUgQEAPaWJqpq9k5Wpnj9iXYY5+/FZJ6IiIiIyMAwqZcQk/rmKeleIWJO3UbMX7dxPaOg2n0EAGN6e8LG3BgyQYBcVlE9XiYT/v3v/T8LgFwm4GRSFmL+ugPxn3MM7+aO7l72UChFKEURCqUIhShCqRShUOLfn1XbROQWl2HD8Vt48B+vnbkx3hjQHi8EtIK5CZN5IiIiIiJDxKReQkzqmzdRFHH6Vg5+2HMV8efS9B1OnZaH98aAjs76DoOIiIiIiOqB1e+JJCIIArp52mHusEew83yaWhV9AcC4AC9YGMuhUKKaXvb7fhYBpVJEel4xjiVmVXkd/zb2aGFt9kDPfmVvv/oIALlMQGGpAr8euanWUy8XBHR0s9b5e0JERERERI0Hk3oiDbjZmmNhqJ9aFf1PQjtrPac+JacI/RbtVmsckAsCIsZ213pufeeWNlXiaQzF+4iIiIiIqOEYzPD7zMxMvPnmm9iyZQtkMhlGjhyJr7/+GlZWVjUe88QTT2Dv3r1q21599VUsWbJE49fl8Hu6X01V9LXx4BJ7D9M4IGU8RERERETUuDTJOfXPPPMMUlJS8OOPP6KsrAwTJ05E7969sWbNmhqPeeKJJ+Dj44OPP/5Ytc3CwkKr5JxJPekCk3EiIiIiIqpJk5tTf+HCBWzfvh3Hjh1Dr169AADffPMNhgwZgs8//xzu7u41HmthYQFXV9eGCpVII2625kzmiYiIiIio3mT6DkAThw8fhp2dnSqhB4CBAwdCJpMhISGh1mNXr14NJycndO7cGbNmzUJhYWGt+5eUlCA3N1ftQURERERERNQYGURPfWpqKpyd1ZfpMjIygoODA1JTU2s8bty4cWjVqhXc3d3x999/Y8aMGbh06RKioqJqPGbhwoWYN2+eZLETERERERER6Ypek/qZM2fi008/rXWfCxcuPPT5X3nlFdXPfn5+cHNzw1NPPYVr166hXbt21R4za9YsTJs2TfV7Tk4OvLy82GNPREREREREDaIy/9SkBJ5ek/p3330X4eHhte7Ttm1buLq6Ij09XW17eXk5MjMztZov7+/vDwC4evVqjUm9qakpTE1NVb9Xvpmenp4avw4RERERERFRfeXl5cHW1rbWffSa1Ldo0QItWrSoc7/AwEBkZ2fjxIkT6NmzJwBg9+7dUCqVqkRdE6dOnQIAuLm5aXyMu7s7kpOTYW1tDUEQND6uoeXm5sLT0xPJycms0k8Gj/czNSW8n6kp4f1MTQnvZ2rMRFFEXl5erUXhKxnUknZpaWlYsmSJakm7Xr16qZa0u337Np566imsWrUKffr0wbVr17BmzRoMGTIEjo6O+Pvvv/HOO+/Aw8Ojytr1TQGX3qOmhPczNSW8n6kp4f1MTQnvZ2oqDKL6PVBRxb5jx4546qmnMGTIEDz66KP46aefVM+XlZXh0qVLqur2JiYm2LVrFwYNGoSOHTvi3XffxciRI7FlyxZ9XQIRERERERGRpAyi+j0AODg4qHrlq9O6dWu1IgKenp5NskeeiIiIiIiIqJLB9NRT7UxNTfHRRx+pFfkjMlS8n6kp4f1MTQnvZ2pKeD9TU2Ewc+qJiIiIiIiISB176omIiIiIiIgMFJN6IiIiIiIiIgPFpJ6IiIiIiIjIQDGpJyIiIiIiIjJQTOqbiO+++w6tW7eGmZkZ/P39cfToUX2HRFSnffv2YejQoXB3d4cgCIiJiVF7XhRFfPjhh3Bzc4O5uTkGDhyIK1eu6CdYolosXLgQvXv3hrW1NZydnRESEoJLly6p7VNcXIw33ngDjo6OsLKywsiRI5GWlqaniIlq9sMPP6BLly6wsbGBjY0NAgMD8fvvv6ue571MhmzRokUQBAFTp05VbeM9TYaOSX0TsG7dOkybNg0fffQRTp48ia5duyIoKAjp6en6Do2oVgUFBejatSu+++67ap//7LPPsHjxYixZsgQJCQmwtLREUFAQiouLGzhSotrt3bsXb7zxBo4cOYKdO3eirKwMgwYNQkFBgWqfd955B1u2bMGGDRuwd+9e3LlzB6GhoXqMmqh6Hh4eWLRoEU6cOIHjx4/jySefxPDhw3Hu3DkAvJfJcB07dgw//vgjunTporad9zQZPJEMXp8+fcQ33nhD9btCoRDd3d3FhQsX6jEqIu0AEKOjo1W/K5VK0dXVVfzf//6n2padnS2ampqKv/32mx4iJNJcenq6CEDcu3evKIoV966xsbG4YcMG1T4XLlwQAYiHDx/WV5hEGrO3txd/+eUX3stksPLy8kRvb29x586d4uOPPy6+/fbboijy+5maBvbUG7jS0lKcOHECAwcOVG2TyWQYOHAgDh8+rMfIiOrnxo0bSE1NVbu3bW1t4e/vz3ubGr2cnBwAgIODAwDgxIkTKCsrU7ufO3bsCC8vL97P1KgpFAqsXbsWBQUFCAwM5L1MBuuNN95AcHCw2r0L8PuZmgYjfQdA9ZORkQGFQgEXFxe17S4uLrh48aKeoiKqv9TUVACo9t6ufI6oMVIqlZg6dSr69euHzp07A6i4n01MTGBnZ6e2L+9naqzOnDmDwMBAFBcXw8rKCtHR0ejUqRNOnTrFe5kMztq1a3Hy5EkcO3asynP8fqamgEk9ERGRhN544w2cPXsWBw4c0HcoRA+tQ4cOOHXqFHJycrBx40ZMmDABe/fu1XdYRFpLTk7G22+/jZ07d8LMzEzf4RDpBIffGzgnJyfI5fIqFTrT0tLg6uqqp6iI6q/y/uW9TYZkypQp2Lp1K/788094eHiotru6uqK0tBTZ2dlq+/N+psbKxMQE7du3R8+ePbFw4UJ07doVX3/9Ne9lMjgnTpxAeno6evToASMjIxgZGWHv3r1YvHgxjIyM4OLiwnuaDB6TegNnYmKCnj174o8//lBtUyqV+OOPPxAYGKjHyIjqp02bNnB1dVW7t3Nzc5GQkMB7mxodURQxZcoUREdHY/fu3WjTpo3a8z179oSxsbHa/Xzp0iUkJSXxfiaDoFQqUVJSwnuZDM5TTz2FM2fO4NSpU6pHr1698Pzzz6t+5j1Nho7D75uAadOmYcKECejVqxf69OmDiIgIFBQUYOLEifoOjahW+fn5uHr1qur3Gzdu4NSpU3BwcICXlxemTp2KBQsWwNvbG23atMGcOXPg7u6OkJAQ/QVNVI033ngDa9aswebNm2Ftba2ah2lrawtzc3PY2tpi8uTJmDZtGhwcHGBjY4M333wTgYGBCAgI0HP0ROpmzZqFZ555Bl5eXsjLy8OaNWuwZ88exMfH814mg2Ntba2qb1LJ0tISjo6Oqu28p8nQMalvAsaMGYO7d+/iww8/RGpqKrp164bt27dXKTBG1NgcP34cAwYMUP0+bdo0AMCECROwYsUKTJ8+HQUFBXjllVeQnZ2NRx99FNu3b+ecOGp0fvjhBwDAE088obZ9+fLlCA8PBwB89dVXkMlkGDlyJEpKShAUFITvv/++gSMlqlt6ejrGjx+PlJQU2NraokuXLoiPj8fTTz8NgPcyNT28p8nQCaIoivoOgoiIiIiIiIi0xzn1RERERERERAaKST0RERERERGRgWJST0RERERERGSgmNQTERERERERGSgm9UREREREREQGikk9ERERERERkYFiUk9ERERERERkoJjUExERERERERkoJvVEREREREREBopJPREREREREZGBYlJPREREREREZKCY1BMREREREREZKCb1RERERERERAbKSN8BNHZKpRJ37tyBtbU1BEHQdzhERERERETUxImiiLy8PLi7u0Mmq70vnkl9He7cuQNPT099h0FERERERETNTHJyMjw8PGrdh0l9HaytrQFUvJk2NjZ6joaIiIiIiIiautzcXHh6eqry0dowqa9D5ZB7GxsbJvVERERERETUYDSZAs5CeUREREREREQGikk9ERERERERkYFiUk9qUnKKcOhaBlJyivQdChEREREREdWBc+pJZd2xJMyKOgOlCMgEYGGoH8b09tJ3WERERERERFQD9tQTgIoe+sqEHgCUIvBB1Fn22BMRERERETViTOoJAHAjo0CV0FdSiCISMwr1ExARERERERHViUk9AQDyS8qrbJMJQGsnCz1EQ0RERERERJpgUk+4kpaH6Rv/rrK9jZMlXG3M9BARERERERERaYJJfTN3K6sQLy49iuzCMnTztMMf0x7H4rHdYCwXcO1uAeLPpeo7RCIiIiIiIqoBk/pm7F5+CcYvPYrU3GK0d7bC8vDeaOdshWHdWuK1x9sBABbEXUBxmULPkRIREREREVF1mNQ3U3nFZQhffgzXMwrQ0s4ckZP7wN7SRPX8f55oBzdbM9zKKsJP+67rMVIiIiIiIiKqCZP6Zqi4TIFXVp3Amds5cLA0QeTkPnCzNVfbx8LECB8M8QUAfL/nKu5kc2k7IiIiIiKixoZJfTOjUIqYuvYUDl+/B0sTOVZO7IO2Layq3ffZLm7o08YBxWVKfLLtQgNHKq2UnCIcupaBlBw2ThARERERUdPBpL4ZEUUR/xd9BtvPpcJELsPPE3rBz8O2xv0FQcBHQztBJgBb/05BwvV7DRitdNYdS0K/Rbsx7ucE9Fu0G+uOJek7JCIiIiIiIkkwqW9GPou/hLXHkiETgMXPdUPfdk51HvOIuy2e6+MFAJi75TwUSlHXYUoqJacIs6LOoDJspQh8EHWWPfZERERERNQkMKlvJn7edx0/7LkGAPhkhB8Gd3bT+Nh3B3WAjZkRLqTk4rejhtXLfSElFw+2QyhEEYkZhfoJiIiIiIiISEIGk9RnZmbi+eefh42NDezs7DB58mTk5+fXedzhw4fx5JNPwtLSEjY2NnjsscdQVNS8emk3nriF//4zJ3764A4Y+0/Pu6YcLE3w7qAOAIAvdlxCdmGp5DHqwp3sIvw3rvpaADlFhnENREREREREtTGYpP7555/HuXPnsHPnTmzduhX79u3DK6+8Uusxhw8fxuDBgzFo0CAcPXoUx44dw5QpUyCTGcxl19vO82mYselvAMDL/duo1p/X1vP+XujgYo2swjJ8tfOylCHqxJlbOQj57iCu3S2AlakRZIL681PXncL+K3f1ExwREREREZFEBFEUG/0k6QsXLqBTp044duwYevXqBQDYvn07hgwZglu3bsHd3b3a4wICAvD0009j/vz5D/3aubm5sLW1RU5ODmxsbB76PPqQcP0eXlx2FKXlSozs4YHPR3eBIAh1H1iDQ1czMO6XBMhlAuLeehQdXRvn+7HjXCreXnsKRWUKdHCxxtLwXpDLBCRmFMLVxgxzt5zD3st3YSKX4fvne2BgJxd9h0xERERERKSiTR5qEF3Whw8fhp2dnSqhB4CBAwdCJpMhISGh2mPS09ORkJAAZ2dn9O3bFy4uLnj88cdx4MCBWl+rpKQEubm5ag9DdO5ODl5aeRyl5UoM9HXBpyP96pXQA0Df9k54prMrFEoR82LPo7G1B4miiKUHbuDVX0+gqEyB/t5O2PBaIDzsLeBma47Ado5o08ISP43viaBHXFCqUOI/v57A1r/v6Dt0IiIiIiKih2IQSX1qaiqcnZ3VthkZGcHBwQGpqanVHnP9+nUAwNy5c/Hyyy9j+/bt6NGjB5566ilcuXKlxtdauHAhbG1tVQ9PT0/pLqSBJGYUYMKyo8grKUefNg74dlx3GMml+ag/GOILUyMZDl+/h+1nq3/v9aFcocSHm89h/tbzEEVgnL8Xlof3ho2ZcZV9TY3k+G5cD4R0c0e5UsRbv/2FDceT9RA1ERERERFR/eg1qZ85cyYEQaj1cfHixYc6t1KpBAC8+uqrmDhxIrp3746vvvoKHTp0wLJly2o8btasWcjJyVE9kpMNK9lLyy3GC0sTkJFfCl83G/wyoRfMjOWSnd/TwQKv/jMvf0HcBRSXKSQ798PKKy7DS6uOI/LITQgC8H9DfPHfkM61NmQYyWX4IqwbnuvjCaUIvL/xb0QeTmy4oImIiIiIiCRgpM8Xf/fddxEeHl7rPm3btoWrqyvS09PVtpeXlyMzMxOurq7VHufmVrFkW6dOndS2+/r6Iimp5mXZTE1NYWpqqkH0jUtKThHO3srFwt8v4FZWEVo5WmDVpD7V9lTX12uPt8PG48m4nV2EH/dex9sDvSV/DU3dyS7CpBXHcDE1D2bGMkSM6Y7Bnau/Jx4klwn4ZIQfzIzlWH4wEXM2n0NhqULVaEFERERERNTY6TWpb9GiBVq0aFHnfoGBgcjOzsaJEyfQs2dPAMDu3buhVCrh7+9f7TGtW7eGu7s7Ll26pLb98uXLeOaZZ+offCOy7lgSZkWdUa3Hbm1qhF8n+6OFtW4aJ8xN5Pgg2BdT1vyFH/ZexaheHmhpZ66T16rNmVs5mLzyGNLzStDC2hS/jO+Frp52Wp1DEAR8+GwnWJoY4ds/r2Lh7xdRUKrAOwO9612DgIiIiIiISNcMYk69r68vBg8ejJdffhlHjx7FwYMHMWXKFIwdO1ZV+f727dvo2LEjjh49CqAiWXv//fexePFibNy4EVevXsWcOXNw8eJFTJ48WZ+XI6mUnCK1hB4ACkrLYSTXbUIa7OcG/zYOKC5T4pNt1a8Fr0s7zqUi7MfDSM8rQQcXa8S80U/rhL6SIAh4L6gD3g/qAABY/McVfLLtQqMrBEhERERERPQgjXrqp02bpvWJZ8+eDQcHB62Pq8nq1asxZcoUPPXUU5DJZBg5ciQWL16ser6srAyXLl1CYWGhatvUqVNRXFyMd955B5mZmejatSt27tyJdu2azvDqGxkFagk9AChFIDGjEG62uus9FwQBHw19BM9+sx9xf6fgxYB7CGjrqLPXq1RZ4f6/2y5AFIHHfFrgu3HdYS3BNIM3BrSHhYkc87acx8/7b6CwVIH5wztD9uAi90RERERERI2ERuvUy2QyBAYGwsTERKOTHjhwAJcuXULbtm3rHaC+NfZ16lNyitBv0W61xF4uCDgwc4BOk/pKs2PO4NcjSejoao2tbz4qWZX96pQrlPgo9hxWJ1TURBjn74WPhz0i+WuuO5aEmVFnIIpAaPeW+GxUF51eFxERERER0f20yUM1nlMfHR1dZVm5mlhbW2t6WqonN1tzLAz1wwdRZ6EQRcgFAZ+Edm6QhB4A3n26A7acTsHF1Dz8diwZLwa00snr5BWX4Y01f2Hf5bsQBOCDZ3zxUv82Opn3Pqa3F8yM5Zi2/jSi/rqN4nIFIsZ0h4kRE3siIiIiImpcNErqly9fDltbW41P+uOPP8LFxeWhgyLtjOnthcd8WiAxoxCtnSwaLKEHAHtLE7w7yAcfbj6HL3ZcwtAubrCz0GxEhyZScopwLDELX++6jGt3C2BmLMPXY7sj6BHNKtw/rOHdWsLcWI4pa/7CtjOpKCo9jh9e6Cnp8oBERERERET1pdHw++assQ+/bwzKFUo8+80BXEzNw/jAVvh4eGdJzvvrkZuYE3MWlTeolakR1rzsjy4edpKcXxN7L9/Fq5HHUVymRN92jpg/vDPS8orRxsmyQRtPiIiIiIio+dAmD2VSXwcm9Zo5dC0D435OgEwAtr3dHx1dH+69yiksw5+X0rH59G38efGu2nMyATg488kGT6YTrt/DpBXHUFCqUItlYagfxvT2atBYiIiIiIio6ZN8Tr29vb3Gc5czMzM12o+alr7tnDDEzxXbzqRiXux5rHnZX+N7JiWnCDvPp2HHuTQcuX4P5Q+W8/9HQ1T1r45/W0dEjO2Gl1edUIvlg6izeMynBXvsiYiIiIhIbzRK6iMiIlQ/37t3DwsWLEBQUBACAwMBAIcPH0Z8fDzmzJmjkyDJMHwwxBd/XEjH4ev38PvZVAzxc6t2P1EUcTU9HzvOp2HHuVScvpWj9ryPixX6tnXCyiOJEB+o6t/ayUKXl1AjS9Oq/1QUoohzt3OZ1BMRERERkd5oPfx+5MiRGDBgAKZMmaK2/dtvv8WuXbsQExMjZXx6x+H32vlq52V8/ccVuNqYYVGoHzq4WcPN1hxKpYi/krOw41wadpxPw42MAtUxggD09LLHoEdc8HQnV7RxsgRQsbTcg1X99TXcvbqlAwHA1swI7wV1wHN9vLjsHRERERERSUKnc+qtrKxw6tQptG/fXm371atX0a1bN+Tn52sfcSPGpF47RaUKBCzchZyicgAVCXvv1g64frcAGfklqv1M5DL0a++IQY+44ilfZzhbm1V7vpScIr1U9a/O/Y0MMgFoYW2KtNyKa+rgYo0Ph3ZCv/ZOeo2RiIiIiIgMn07Wqa/k6OiIzZs3491331XbvnnzZjg6Omp7OmpisotKkftPQg8AoggcvVFRZ8HazAhPdnTGoE6ueLxDC1hVM6T9QW625npP5is9uHRgCytTrDmahC93XsaltDw8/0sCgh5xwf8N6QQvR/1MEyAiIiIiouZF66R+3rx5eOmll7Bnzx74+/sDABISErB9+3b8/PPPkgdIhuVGRgGqG/rxwZCOCO/bBiZGhj1E/cFGhvGBrTGsqzsidl1B5JGbiD+Xhj8v3sXk/m3wxoD2GjVcEBERERERPSytM6zw8HAcPHgQNjY2iIqKQlRUFGxsbHDgwAGEh4frIEQyJG2cLCF7oOi9XBAwtKu7wSf0NbGzMMHcYY/g97f7o7+3E0oVSvyw5xoGfL4HG44nQ1lDNX8iIiIiIqL64jr1deCceu01pgJ3DU0URfxxIR0L4s4j8V4hAKCLhy0+GtoJPVs56Dk6IiIiIiIyBDotlAcA165dw/Lly3H9+nVERETA2dkZv//+O7y8vPDII488dOCNEZP6h9OYCtzpQ0m5AisPJWLxH1eRX1JRY2B4N3fMfKZjs3w/iIiIiIhIc9rkoVqPh967dy/8/PyQkJCATZs2qardnz59Gh999NHDRUxNjputOQLbOTbbBNbUSI5XHmuHP997AmN6eUIQgM2n7uDJz/fi611XcONuAQ5dy0BKTpG+QyUiIiIiIgOmdU99YGAgRo8ejWnTpsHa2hqnT59G27ZtcfToUYSGhuLWrVu6ilUv2FNPUjh7OwfztpzDscQste0yAVgY6tdspicQEREREVHddNpTf+bMGYwYMaLKdmdnZ2RkZGh7OqJmoXNLW6x/NRAfD1efnqIUgQ+izrLHnoiIiIiIHorWSb2dnR1SUlKqbP/rr7/QsmVLSYIiaooEQUB7Z6sq2xWiiMSMQj1EREREREREhk7rpH7s2LGYMWMGUlNTIQgClEolDh48iPfeew/jx4/XRYxETUZ1S/7JBKC1k4V+AiIiIiIiIoOmdVL/ySefoGPHjvD09ER+fj46deqExx57DH379sXs2bN1ESNRk+Fma46FoX6Q35fYB3dxa7YFBYmIiIiIqH4eep36pKQknD17Fvn5+ejevTu8vb2ljq1RYKE80oWUnCIs2XMNKw/fREdXa/z+dn8IglD3gURERERE1ORpk4caPeyLeHl5wcuLFbuJHoabrTneedoHvx1LxsXUPJy9nQs/D1t9h0VERERERAZG66ReFEVs3LgRf/75J9LT06FUKtWej4qKkiw4oqbMzsIEQY+4YsvpO1h3PAl+Hn76DomIiIiIiAyM1nPqp06dihdffBE3btyAlZUVbG1t1R5EpLkxvTwBAJtP3UFxmULP0RARERERkaHRuqc+MjISUVFRGDJkiC7iIWpW+rZzhIe9OW5lFeH3sykY0d1D3yEREREREZEB0bqn3tbWFm3bttVFLETNjkwmYHTPit76dceS9RwNEREREREZGq2T+rlz52LevHkoKirSRTxEzc6oXh4QBODI9UzcvFeg73CIiIiIiMiAaJ3Uh4WFISsrC87OzvDz80OPHj3UHkSknZZ25ujv3QIAsP44e+uJiIiIiEhzWs+pnzBhAk6cOIEXXngBLi4uXFubSAJjenli3+W72HjiFt4Z6AMjudbtbURERERE1AxpndTHxcUhPj4ejz76qC7iIWqWBnZyhr2FMdJyS7Dvyl082dFF3yEREREREZEB0Lo70NPTEzY2NrqIhajZMjWSqyrfs2AeERERERFpSuuk/osvvsD06dORmJiog3CImq8xvSuq4P9xIR1380r0HA0RERERERkCrYffv/DCCygsLES7du1gYWEBY2NjteczMzMlC46oOengao2unnY4nZyN6L9u4ZXH2uk7JCIiIiIiauS0TuojIiJ0EAYRARUF804nZ2PdsWS83L8tC1ESEREREVGttErqy8rKsHfvXsyZMwdt2rTRVUxEzdbQrm6Yv/U8rt0twMmkLPRs5aDvkIiIiIiIqBHTak69sbExNm3apKtYiJo9azNjDPFzA8CCeUREREREVDetC+WFhIQgJiZGB6EQEQCE9aqogr/17xTkl5TrORoiIiIiImrMtJ5T7+3tjY8//hgHDx5Ez549YWlpqfb8W2+9JVlwRM1RnzYOaONkiRsZBYj7+w7G9PbSd0hERERERNRICaIoitocUNtcekEQcP369XoH1Zjk5ubC1tYWOTk5sLGx0Xc41Ex8v+cqPtt+CT287BD1ej99h0NETUhKThFuZBSgjZMl3GzN9R0OERERVUObPFTrnvobN248dGBEpJlRPTzwxY7LOJmUjavpeWjvbK3vkIioCVh3LAmzos5AKQIyAVgY6sfRQERERAZO6zn19xNFEVp29BORBpxtzDCgQwsALJhHRNJIySlSJfQAoBSBmZvO4LeEJKTlFus3OCIiInpoD5XUr1q1Cn5+fjA3N4e5uTm6dOmCyMhIqWNTk5mZieeffx42Njaws7PD5MmTkZ+fX+sxqampePHFF+Hq6gpLS0v06NGD1fvJYIT18gQARJ28jdJypZ6jISJDdyOjQJXQVxIBzIo+A/9P/kDAJ3/gP5EnsGTvNRy5fg8FLNRJRERkELQefv/ll19izpw5mDJlCvr1q5jre+DAAfznP/9BRkYG3nnnHcmDBIDnn38eKSkp2LlzJ8rKyjBx4kS88sorWLNmTY3HjB8/HtnZ2YiNjYWTkxPWrFmDsLAwHD9+HN27d9dJnERSGdDRGU5WpsjIL8Hui2kY3NlN3yERkQFLya7aGy8AaOdshet385GaW4zt51Kx/VwqgIrh+T4u1ujmaVfx8LKDt7M15DKh4nycm09ERNQoPFShvHnz5mH8+PFq21euXIm5c+fqZM79hQsX0KlTJxw7dgy9evUCAGzfvh1DhgzBrVu34O7uXu1xVlZW+OGHH/Diiy+qtjk6OuLTTz/FSy+9pNFrs1Ae6dPC3y/gx73XMaBDCyyf2Eff4RCRgcrIL8HgiP3IyC+BgIoeerkg4JPQzhjT2wuFpeU4cysHp5KzVY+UnKqNAJYmcvh52MLUSIZ9lzMggnPziYiIdEGnhfJSUlLQt2/fKtv79u2LlJQUbU+nkcOHD8POzk6V0APAwIEDIZPJkJCQgBEjRlR7XN++fbFu3ToEBwfDzs4O69evR3FxMZ544okaX6ukpAQlJSWq33NzcyW7DiJthfXyxI97r2Pv5btIzSmGq62ZvkMiIgMjiiJmbvobGfkl6OBijR9f7ImUnGK0drJQ9bBbmBjBv60j/Ns6qo5Lyy3+N8lPysbft7JRUKrAkeuZaudXisAHUWfxmE8L9tgTERHpgdZz6tu3b4/169dX2b5u3Tp4e3tLEtSDUlNT4ezsrLbNyMgIDg4OSE1NrfG49evXo6ysDI6OjjA1NcWrr76K6OhotG/fvsZjFi5cCFtbW9XD09NTsusg0la7Flbo3doeShHYeIIF84hIe2uOJmHXhXSYyGWIGNsNrZ0sEdjOsc4E3MXGDEGPuGLG4I747ZUA/D03CDveeQyv9G9bZV+FKCIxo1BXl0BERES10DqpnzdvHj788EMMHjwY8+fPx/z58zF48GDMmzcPH3/8sVbnmjlzJgRBqPVx8eJFbUNUmTNnDrKzs7Fr1y4cP34c06ZNQ1hYGM6cOVPjMbNmzUJOTo7qkZzMRIr0q7Jg3vrjt6B8sMoVEVEtrt3Nx/yt5wEA0wd3gK/bw08jk8sE+LhYY+KjrfHPtPp/nxMEtHayqE+oRERE9JC0Hn4/cuRIJCQk4KuvvkJMTAwAwNfXF0ePHtW6+Ny7776L8PDwWvdp27YtXF1dkZ6erra9vLwcmZmZcHV1rfa4a9eu4dtvv8XZs2fxyCOPAAC6du2K/fv347vvvsOSJUuqPc7U1BSmpqZaXQeRLgV3ccO8LeeRlFmIIzfuoW87J32HRNSosYBbhTKFEu+sO4XiMiUebe+ESf3aSHJeN1tzLAz1wwdRZ6EQRdXc/Ob8XhMREemT1kk9APTs2RO//vprvV+8RYsWaNGiRZ37BQYGIjs7GydOnEDPnj0BALt374ZSqYS/v3+1xxQWVgwDlMnUByPI5XIolVwejAyHhYkRhnZ1w29Hk7H+WDKTeqJarEm4if+LOQtRZAG3iF2X8f/s3XlYlOX6B/DvLAz7LiIqroBa7ru4pGVi4QIItJki/tqtqMylg5ZpadbpcDrWqdNRU+qkoIAsJWqauZcLpuaCC4KCuLBvA8y8vz+ISWSbkXeYhe/nuuYq3pl55p5FmPt9nue+f79WCEdrC3wSMgDSe6fXW+CJYV0wzscNGbfL6uzNJyIiotanc/V7AFCr1bh48SJu3rxZL0EeN26caMHd7bHHHkNubi6+/PJLTUu7oUOHalraXb9+HY888gg2btyI4cOHo6qqCg888AA8PDzwySefwNXVFQkJCXj77beRnJyMxx9/XKvHZfV7MgYnMvMR+MVBWMql+PVvE+FobWHokIiMysWbJVh/8Aq+O5xZ57hUAhxY9HCbSzp/vZKHJ/5zCIIAfPHMYDzejy0xiYiITIleq98fPnwYTz/9NK5evYp7zwdIJBKoVCpdh9TKd999h3nz5uGRRx6BVCrFjBkz8Nlnn2mur6qqwvnz5zUz9BYWFvjhhx+waNEiTJ06FSUlJfDy8sKGDRu0TuiJjMVATyf4uNvhQm4JEtOu49lR3QwdEpHBFVdUIfn3HMQczcKJzIIGb6MWgLX7ruBv/n0gkYg3U23Miiqq8MbmNAgCEDykMxN6IiIiM6fzTP3AgQPh4+ODZcuWwcPDo96XJEdHR1EDNDTO1JOx+O++y1iRchZ9Ozkg+dWxhg6HyCDUagGHL99B7LFr+PF0DiqqalaLyaQSjOzugoOX7qChP2q+PV3x0Yz+8HQx/2Jub2xOQ/yJ6+jiYoMfXh8LO8v72mlHRERkVioqKhAbG4uEhATk5efBxdkFAQEBCAkJgZWV8bWN1iUP1Tmpt7W1xcmTJ5tsC2dOmNSTscgrrcSID3ehSiUg5bUxeLCjeZ1AI2pKVl4ZYo9dw9Zj13C9oFxz3Ku9HUKGdEbgoE5o72CFzb9lagq4SSXA4/08sOtsLiqq1LBRyLBwcm88O7KrqPvLjUniyWy89v0JSCVA7IujMKSri6FDIiIiMrjExESEhYch/04+7HzsIHOSQVWgQsmFEji7OmPD+g2YOnWqocOsQ6/L70eMGIGLFy+2maSeyFi42Crw6APu+OHUDcT8loVl05nUk3m5t2p9eaUKP56uWV5/+HKe5nb2VnJMHdARIUM6Y6CnU50VYw0VcMu4XYqFW3/HkSt5eDfxDFJ+z8FHwf3RvZ2tQZ6XvmQXlCMyvqZl67yHvZnQExERoSahDwwMhN1AO3i/7Q3LDn91OlPeUCI3JhcBAQGIj4/HtGnTDBjp/dN5pj4+Ph6RkZF4++230a9fP1hY1C3Y1b9/f1EDNDTO1JMx+fn8TYSt/w2O1hY48s4jsLKQGTokIlFs/i0Ti+NOQS0AEgkwtKszzuYUo0RZDaDm2Oie7RAytDP8Huyg82dfrRbw3ZGrWPnjOZRVqmBlIcX8Sb0wZ3R3yPQ4a3/389JnNX6VWsAz/z2Mw5fzMNDTCbEvjoKFTNr8HYmIiMxYRUUFOnbuCFVXFTzneULSwN98QS0ga00WZFdlyL6WbTRL8fW6/P7eFnFATYE8QRD0WijPUJjUkzFRqQWM/Wg3sgsr8NlTgzBtQEdDh0TUYjmF5Ri9ajfUDfw16uJig+AhnTFjSGd0cmr5LHdWXhkWx53C/ou3AQCDujjh4+D+8Gpv3+Kx73bpVgm2HLuGf/98qc5xfVXj/2rvJaz88RxsFDL88NpYdGulVQj3q7i4GBEREQgNDYWfn5/meGpqKmJiYhAVFQV7e3HfEyIianuio6Mxa9YseK+qO0N/L2WOEumL0xEdHY2ZM2e2YoSN0+vy+ytXrtx3YETUMjKpBMFDOuOz3RcR81sWk3oyC1dulzaY0C+Z0gdzfLuLuv/d08UG0XOHY/NvWfgg5SxOZBbg8c/2I2KiN54f2wPy+5zdVqsF/H69EDvO3MCOP3Jx8WZJw7cTgO8OX8Vbk3qJVo3/9PVCfLLjPADg3akPmERCP3nSozh4+Ai+jd6IuPgE+Pv7IyUlBUGBAaisqsa5P85g+46dTOyJiHRgaoXgWkNCQgLsfOyaTOgBwNLDEnY+doiPjzeapF4XOif1Xbt21UccRKSlkKGe+Gz3Rey/eBtZeWVtopo3mTcref1EWiaR4PF+HnopaCeRSPDk8Jq99+/En8LP529h9fbz+PHUDXwc0h+9O2i3KquyWo3Dl+9gxx83sPOPXOQWKTXXyaUSDO7ihN8y8utV41+z5xJ+vZKPZdMfRB+Plq0AK69UIWJzGqpUAvwedEfoUM8WjadvtQn96ZNHsW+ODT45VI2gwAAsWLgIqz9ahce9pHhrpA38Nx3F5EmPMrEnItJSg4XgrqsQFxeH19943SgLwbWGvPw8yJy027IndZIiLz+v+RsaIa2mJBITE1FVVaX1oD/88APKy8ubvyER6czTxQajvVwBALHHrhk4GqKWUVarsCzpjzrHZBIJPgzqq9eicgDQ0cka68OG4ZOQAXCwkuPU9UJM/dd+/HNXOqpUauQUluPgpdvIKfzr71mJshopv+fg9U0nMGTFTsxa9yu+PZyJ3CIlbBUy+Pf3wD+fHIhjSx5FzIu+WDWjH2R/zshLJYDfA+6wspDi14w8+H+2D+8lnkFhmfZ/X++18sezuHizBO3tLbEyqL9os//6EhERgYOHjyDlSUuM6SJHTLAlHuspxYoVK/C4lxSbZ9QcT3nSEgcPH0FERIShQyYiMnq1heBUXVXwXuWNbu90g+fLnuj2Tjd4r/KGqqsKAQEBSExMNHSorc7F2QWqAu22h6sL1HBxNs0is1rtqZfJZLhx4wbc3Ny0GtTBwQFpaWno0aNHiwM0NO6pJ2O0Le06Xt+Uho6OVti38GG9Fvoi0qclCacRffgqHK0tsC5sKCqrBU3V+tZ0s6gCf0s4jZ1/5AIAPBytcKOoAsKfBe4CBnVCfmklDly8g0qVWnO/dnY1XSkmPdgBvj1dYSmvPxuQU1hepxr/9YJyfJhyFimncgDUdLZYOLkXQoZ46rQyYc+5m5jzzW8AgI3hwzHOR7u/0YaUmpqKaVOnaBJ4hUyCSpWAlAvV8PeRa34O3aLEj5fUSExKrrPnnoiI6jLlQnCtoa3sqdcqqZdKpXjsscdgadn0XoRaycnJOHfuHJN6Ij2pqFJhxIc/obC8Cose643pAzu2ehJE1FK1J6cAYH3YMEzo3d6g8QiCgMST2ViacBqFFdWN3q6bqw38HuyASQ+6Y6Cn832fVDtw8TbeTTyj2X8/oLMj3p/eFwM8nZq97+0SJSZH7cPtEiXmjO6Gd6c+eF8xGELt3vm7E/tadyf0tXvtiYjMXUv2wpty0toaTPmkhy55qFbL72fPno327dvD0dFRq8szzzzDBJhIj6wsZHjQo2af6aofz2H0qt3Y/FumgaMi0l56bjEWbf2zp/oEL4Mn9EDNXvvpAzvho+CGW7M+McwTO98Yhz3zx2Px430wpKtLi1bJjPZqhx9fH4tI/z6ws5Tj5LVCBHxxAIu2/o47JcpG7ycIAhZt/R23S5TwcbfDwsm97zsGQ/D398eChYuQcLYSKRfqnjxJuVCNbecqsWDhIib0RNQmJCYmomPnjpg1axZ2nN6BE6UnsOP0DsyaNQsdO3dEUlJSk/e/n0JwbYmVlRU2rN+AkrQSZK3JgvJG3b+vyhwlstZkoSStBBvWbzCahF5XOre0a2s4U0/GKKewHL6rduPuf70yiQT7F03gjD0ZvRJlNaav2Y9Lt0ox2ssVG8NHGNUWkoZa7On739fNogqs2n4OccevAwAcrOSY79cLTw/vUq8i//+OZOKd+FNQyKTYNm90i4vttbaUlBQEBkzHYz0liA2xrjdTHxxTju2XBcQnbGNiT0RmrXYvvN1AO7iHutdJzJU3lMiNyUVJWgni4+Mxbdq0BseY8PAEnCg9Ac+Xmy+UmvlFJgbbDsae3XtEew6tQYyq/vcWEpQ6SaEuUKPkQgmcXZ2NspCg6DP1RGRcrtwuxb2n41SCgIzbZYYJyMw1VDCN7o8gCFgcdwqXbpWig4MV/vnkIKNK6AHAw9EaK4P+KnDXGoX72jtY4dPQgdjy4ig84OGAoopqLN12BlP+tR+/XqmpxJtTWI6tx7LwftIZAMCCyb1MLqFPTU2tSeh7/JXQV6oExJ+tQqVKgEImwZZQa0zuIUFgwHSkpqYaOmQiIr2oqKhAWHgY7AbawXOeZ72ZdssOlvCc5wm7gXYICw9DRUVFg+OYeyG4lq5kqDVt2jRkX8tGdHQ0JvWdhMG2gzGp7yRER0cj+1q20SX0utK5pR0RGV73draQSlCvt/eGQxno39kRtpb8py2Wzb9lYnHcKaj/LJi2MqgfnhjWxdBhmayNh64i6WQ25FIJ1jw9CO3stKvV0tqeGFbT8u7uAnetYWg3FyS9Ogb/+zUTn6Sex7kbxQj96hAGejri92uFmn/zXu1tET66e6vEJKbvv/8eVdUqvD3aRpPQB8eWI+l8Nab1liM2uCbRXzBagaQLZfj+++9ZKI+IzFJsbCzy7+TD+23vBvd5A4BEKoF7iDvSF6djy5YtDe6FDwgIQFxcHJQ3lM3uqS+5UILAJYGiPQd9u3slg/fb3g2uZAgICGhyJcPdrKysMHPmTLOsKcCZeiITdO9MouTPy/bTNzB1zX78kV1k0PjMRU5huSahB2pOoiyOO2XwGXtTXTlwPDMfK1Jq2tcteqw3hnYz7tkCD0drjOrp2upbWmRSCZ4d2RV75o/HU8NrTiClZRXWOYl3+VYpcosbnrUxZr6+vpBKgMn/K8f+zGoEx5Yj5VI13Ka6IfliNUK21Byf/L9ySCXA6NGjDR0yEZFeiLUXPiQkBM6uzsiNyYVw72zPnwS1gNzYXDi7OiM4OLjFsWuroqIC0dHRmDFjBiY8PAEzZsxAdHR0o6sO7r2vGCsZ2gom9UQm6olhXbB/0QR8/9xIHFz8MDY9PxIdHKxw+VYpAr44gG8PXwVLZtw/lVrAt4eu1lsNoRaAgM8P4PVNJ7D+wBWcyMyHslq7ZW9i2PxbJkav2o2nvz5iUgUS80orMe+746hSCXi8XwfMHWN6s8ytzcVWgZVB/fBBQN9616kFmOR2m9TUVFj3tIXE0wpj15ch5VI1POd1hfsMd3jO64rki9UYu74MEk8rWPe0xfbt2w0dMhGRXuTl50HmVL8NakOkTlLk5ec1eJ2xFoJr6bL52pUM7qHuza5kyL+Tjy1btujjaZgMrtElMmEejtaaWUQPR2v88PpYzI89id3nbiIy4TQOXbqDlTP6wcHKwsCRmo5qlRrb0rLx+Z6LuHy7tMHb5BYpsS0tG9vSsgEAFjIJHvBwwEBPJwzs4oSBns7o5moDiaTuH6GcwnJcuV2K7u1stZr9raxWI7eoAtkF5cguLMf5G8X4cu9lzfVqAXgn7jTG+bgZdYFElVpAxOY0ZBdWoHs7W3w0o3+914Ya93Cf9pBuQ73Cfd3a2RguqPuUl58HuYscHed0RM7/cuA43BH2/Wo6edgPtIfn611R+GshPJ72wPX11xv9EktEZOpcnF2guq7DXvjOja9umzp1KuLj4xEWHob0RekNFoJLSEjQet94SwvTibFs/n5WMpjjsnpt6ZzUX7lyBfv27cPVq1dRVlYGNzc3DBo0CKNGjTLZFgBE5sLFVoH/zhqKtfuv4KPt55ByKge/Xy/AmqcGa9X7ui2rUqkRf+I6Pt9zEVfv1MyAOtlYYER3F+z8IxdqoSaRipzSBz3c7HAyqwBpf17ySitx8lohTl4rxIZDVzX3HdDZCQM8nTDI0wlXbpdiRcofmr35HwT2w8Q+7sguKEdOYTmuF1Qg58/kPbugJpG/VaKsVxDxXrUFEo05qf/X7nT8cuEWrCyk+PfMwbDnSSad1G63eSfuNFSC0CqF+/Sl9kuszFqGznM717vevp+9Jslv7kssEZEpE3svfG0huC1btiA+Pr4mGe/sgsAlgQgODr7vKvEyJxlU11WIi4vD62+83myV+HuXzd87y167bD5rTRbCwsMa7Qsv1kqGtkLrlnbfffcd/vnPf+Lo0aNwd3dHx44dYW1tjby8PFy6dAlWVlZ45plnsHDhQnTt2lXfcbcatrQjU3UiMx+vfn8C1/LLYSGTYOHk3pg7pjtnSO9RWa1G3PFr+Pzni8jKq9mj7mKrwHNje+DZUV1hZylHTmF5owXTBEFAVl45TmTla5L8M9lFqKxWixKfQi5FR0creDhaw8nGAttP38Ddv7QlAA4ufthoE7y9F24hbP2vEATg7yEDMGNI/USOtNPU59BUREdHY9asWfBe5d3sl9j0xemIjo5u0zMvRGS+Kioq0LFzR6i6qhpMfoGavfBZa7IguyprNPkVkxgt9sT6PT9jxgzsOL0D3d7p1mzcGR9mYFLfSdi6dWvzT9KE6JKHapXUDxo0CAqFArNnz8bUqVPh6Vm3D6JSqcShQ4ewadMmbN26FV988QVCQkJa9iyMBJN6MmWF5VVYtPV3/Hj6BgBgYp/2+Dh4AJxtFQaOzPAqq9WIPZaFL/ZcwvWCmmS+nZ0Cz4/rgZkju8JGcf+7kyqr1Th3o6gmyc8swKFLd5BT1HABF3cHS3R0skZHR2t0dKpJ3js61fx/RydruNoq6pyI2fxbpmbGtta6sKF4uLf7fcerL9kF5fD/bB/yy6rw1PAuWBnUz9AhkYEZ45dYYyVGX2YiMm5JSUkICAhoOInOUSI3tiaJ1mXp/P0S6/ezWMk4TwLrIalPTU3VuqXMnTt3kJGRgSFDhmgXrZFjUk+mThAEfHv4KpYnn0WlSg0PRyt89tQgDDPyyuP6oqxWIea3LPz750vILqxJtN3sLfHCuB54ZkRXWCu0W+qli5zCcoxetbvOnmipBPh5/nh0cbW9r/Eybpdh02+Z2JaWDXtLORLmjUZPNzsRo26Zymo1Qr86hLSsAvTt5IAtL/rCykL815ZMjzF9iTVWDS5/LVBp9sY2t/yViEzHvf/e790L31r/3sVKoic8PAEnSk/A82XPBu5dV+YXmRhsOxh7du+pdx1PAuuWh2o1FaVLj1hXV1e4urpqfXsi0i+JRIJnR3XD4K7OePV/J3D5dime/M9hvPmoD156qCekjVQUNQd3F6ZztlFg85/J/I0/Z83dHSzx4kM98dTwLnpNOBvbE30/CX3teB6O1hjS1RnX88tx9Go+ntt4FAmvjDaaoogf/nAWaVkFcLCS49/PDGFCTxpiF3QyN2L3ZSai+oxpJYxYe+FbSqzCdGIVAKyt6h8QEICsNVnNngQ2t4ReV1rvqc/Ozsann36KpUuX1jtTUFhYiBUrVmD+/Plwdze+JaAtwZl6MiclympExp9Cwp9V28d6t8OnoQPhZt/0L3BTtPm3TE2PeQkAO0s5ipXVAAAPRyu8NL4nQod6tmqyqY890beKlZi2Zj9yCivwcO/2+HrWUMgMfKIm6WQ2Xv3+BABg7eyheKSPef1dIHFUVFTU/RLr7ILAwNb9EmtsODNFpH9cCdMwsWbYxV42bywrGQxB9OX3ADB//nwUFRXhP//5T4PXv/jii3B0dMRHH32ke8RGjEk9mRtBEBB77Bre3XYG5VUqtLOzxNKpfdDOzlLrVmvG7uqdUoz/5Od6leM7OFhh3sNeCBnaGZZy85k5/v1aAUK+PARltRqvTOiJt/16GyyWizdLMH3NfpRWqvDy+J5YMNlwsRCZGu4hJdIvMQrBmSux9sLr4+RkWz0JrJekvm/fvvjyyy8xZsyYBq8/ePAgnnvuOZw5c0b3iI0Yk3oyV+m5xZj3vxM4n1usOSaVACuD+uGJYV0MGJnuVGoBf2QX4cCl2zhw8TYOX76DKlX9X23R4cMx1sfNABHqX/yJa3hj80kAwOdPD4Z/f49Wj6FUWY2Azw8g/WYJRvVwRfTc4ZDLpK0eB5Gp0ke1Z2NaZkxkSFwJ0zQxTyqydoo4dMlDtf62deXKFXTp0vgX/c6dOyMjI0PrIInIsLzd7fHlzLoFLdUC8E7caeQUlhsoKu0IgoArt0sRffgqXvr2GIas2Impa/Zj1Y/nsC/9doMJvUwigZe78RSSE1vgoM74vzHdAQDzY0/ij+yiVn18QRDwt/hTSL9Zgvb2lvjsqUFM6Il0JHZf5sTERHTs3BGzZs3CjtM7cKL0BHac3oFZs2ahY+eOSEpKEiNsIpMQGxuL/Dv5cA91bzChBwCJVAL3EHfk38nHli1bWjlCwwoJCYGzqzNyY3IhqBue8xXUAnJjc+Hs6ozg4OBGx6qtnSK7KkP6onRkfJiBzC8ykfFhBtIXp0N2VcaEXmRa92yytrZGRkZGo4l9RkYGrK1Nf9kuUVuSU1Q/eVcJAjJulxl0Gf7dBe5q47hZXIGDF+/gwMWa2fjayvW17CzlGNnDBaO92mG0Vzscv5qPv8XXLUxnDlsLmrLosd44n1uMfem38Xz0USTOGwOXVmhfmFNYjv/8chkJadmQSSVY8/Rgs6zTQManuLgYERERCA0NrVPUNzU1FTExMYiKioK9vb0BI9SNWAWmABbcI7qXWIXgzJXYhemMpQBgW6F1Uj9ixAhER0dj3LhxDV6/ceNGDB8+XLTAiEj/urezhVQC3HtCtouL4ZLfOgXuJIBvT1fcKlbiQm5JndtZyCQY3MUZY7zawderHQZ0dqwzM+zjbo+HermJXpjOmMllUvzrqUGYtuYAMvPK8Mp3x7Fx7nBY6HHGfPNvmVgUd0pTv2Dygx0wvHvbbJdIrau4uBiTJz2Kg4eP4NvojYiLT4C/vz9SUlIQFBiAyqpqnPvjDLbv2GkyiX1AQADi4uKgvKFsdvlryYUSBC4JbPD6iooKhIWHwW6gXYPLjC07WMJzniey1mQhLDyszS0zJtPVku0kYq+EMUdidyexsrLCzJkz29TJEUPR+pve/PnzsX79esyfPx+5ubma47m5uXjrrbfwzTffYP78+XoJkoj0o7bVmkxS9wvf9jO5jdxDv3IKyzUJPQAIAnDg4h1cyC2BRAI82NEBL4zrgQ3hw3Hy3UnY/MIovPqIN4Z0dW5wqbeHozVG9XRtEwl9LScbBb6eNRQ2ChkOXb6DD1LO6u2xsvJKsWjrqToFCbefzjH67Rtk+moT+tMnj2LfHBs81lOKoMAALFmyBEGBAXjcS4p9c2xw+uRRTJ70KIqLi5sf1AiItfyVy4zJHLV0O4mLswtUBTqshHFumyeoa2fYo6OjManvJAy2HYxJfSchOjoa2deyuWTeSGldKA8AvvrqK7z++uuoqqqCg4MDJBIJCgsLYWFhgX/84x946aWX9BmrQbBQHrUFta3WTmTlY/X287CUS/HD62PR061196AfvHQbT399pN7x1x/xxmzfbq2ylNxcbD99Ay9+ewwAsDq4P0KHNt+iRhdHLt/B/NiTyMqvn8B//9xIjOrpKurjEd1t7ty5WLduHfbNscGYLnJUqgSEblFi27lKBPRRYPMMSyhkEuzPrMbY9WUIDw/H2rVrDR22VsQoMKWPgntEhiRG1Xp2lyBTo5fq97WuX7+OmJgYXLx4EYIgwMfHB8HBwejcuXOLgjZWTOqpLREEAbPW/Yp96bcxqIsTtrzo26o9z1NP5+CFb4/XOSaTSLB/0YQ2Ndsulk93XsBnP6VDIZNi8wsjMaiLc4vHvFFYgZU/nsW2tOwGr+f7Ra0hNTUV06ZOweNeUk0CX6kSkHKhGv4+cs3PoVuU+PGSGolJyXX23Bu7lvZlFqvfNJExEKtqPavfk6nRS/X7Wp06dcIbb7yBzz//HF988QUiIiLMNqEnamskEgk+mtEf9pZynMgswNf7LrfaY98qVmJpYk1LzNo/s22lwJ2+RDzijUcfcEelSo0Xvz2Gm0UVzd+pEZXVany59xIe/vvP2JaWDYkEeGZEFyyd8oBm+wbfL2otfn5+iItPwA8X1XhiqxKVKgEKmQSBfSzqJfRx8QnNJvTFxcWYO3cuUlNT6xxPTU3F3LlzW335fkuXv3KZMRmbiooKREdHY8aMGZjw8ATMmDED0dHRqKho/u+SWNtJagvBlaSVIGtNFpQ3lHWuV+YokbUmCyVpJdiwfoNWCX1LnheRmHSeqU9MTGx4IIkEVlZW8PLyQvfu3UUJzhhwpp7aopijWViw5XcoZFIkvzYGPu76LTJVrVJj5tojOHw5D97t7fDlzCG4WaxsMwXu9KlEWY3AP3vHD+rihE3Pj4SlXLtCQbV+uXAL7yWdweVbpQCAwV2c8P70vujbyRHAX9s3+H5Ra1uyZAlWrFiBuFBrBPax0ByPP1uFoJhyREZGYvny5U2OcXfBPYWFvMGCe74jR5hUwT0uMyZjcu/KE5mTDKoCldYrT8TeTtLSlTBiPS+i5uh1+b1UKoVEIsG9d6s9JpFIMGbMGCQkJMDZueVLPQ2NST21RYIg4P82HMVP526iXydHxL3sq9cK6it/OIuvfrkMW4UM2+aNgVd78+0nbwgZt0sxbc1+FFVUI3RoZ3w0oz8kkua3VWTllWFFyh9I/bNwYjs7Syx+rDcCB3WCtBW3ZRA1pDbpvnsJfq17Z+r9/f0bHOPugnspT1rik0PV+PGSGgsWLsLqj1bhcS8p3hoph/8mJfoOGGoyib0+lhm3pOo4tV1i7IXXx3aSioqKuq3WnF0QGKh9qzUxnhdRc/Sa1P/000/429/+hg8++EDTwu7XX3/FkiVLEBkZCUdHR7zwwgsYMWKEyRSlaQqTemqrcosqMOkfv6CwvApvPeqDVx/x1svj/HgqBy99V7OP/otnBuPxfh56eZy2bu+FW5iz/leoBWDZtAcx27dbo7etqFLhq72X8cXPF6GsVkMmlSDMtxten+gNByuLRu9H1FrE2lPPgntNF9yrxRlJ02MMJ2HEOrlkbIUfuTefWote99S//vrr+PTTT/HII4/A3t4e9vb2eOSRR/Dxxx/j7bffxujRoxEVFYWdO3fe9xMgIsNzd7DCsmkPAgA+252OP7KLRH+MS7dK8PaW3wEAz43tzoRejx7yccPCyb0BAO8n/4FDl+7Uu40gCNhx5gYmfroX/9h1AcpqNXx7uuLH18diyZQHmNCT0YiJiUFlVTXeGlk3gQ+KKa+zx37+KDkqq6oRExPT4DihoaFQWMjx98PVmvvEBFsiLtS6zsmCTw5VQ2EhR2hoaCs/0/tX229adlWG9EXpyPgwA5lfZCLjwwykL06H7KpM64Q+MDAQqq4qeK/yRrd3usHzZU90e6cbvFd5Q9VVhYCAgEa3Z1Lra2nrt7sZw174gIAAlFwoqbcH/l7KHCVKLpQgMDCw+SfWAmwZScZI55l6a2tr/Pbbb+jbt2+d46dOncLw4cNRXl6Oq1evok+fPigrKxM1WEPgTD21ZYIg4MVvjyH1TC56d7BH4rwxUMjFWYZfqqxGwJ97vUd0d8F3/zeiwV7zJB5BEBCxOQ3b0rLhYqtA4rzR6OxsAwC4fKsEy5L+wN4LtwAAHo5WiPR/AI/366DVUn2i1iTmsnkxlvEbs5YsM+aMZOtr6Qy7mMvCjWUvvLF9Do1t5QCZL73O1A8ZMgRvv/02bt26pTl269YtLFiwAMOGDQMApKenw9NT3J7IRNT6JBIJPgjsBxdbBc7dKMaa3emijCsIAhbFnUL6zRK0t7fEv54exIS+FdR2N+jbyQF5pZWYs/43bD+dgyUJp+EX9Qv2XrgFhUyKVyb0xE9vPQT//h5M6Mko2dvbY/uOneg7YCjGri/TJN3Lly/XVMUfu75Mq33w/v7+WLBwERLOViLlQnWd61IuVGPbuUosWLjIJBN6oKbi98yZM7F161bs2b0HW7duxcyZM7VKejgjqR2xuids2rQJjk6ODc6wOzo5YvPmzU3ev6KiAmHhYbAbaAfPeZ71iiRadrCE5zxP2A20Q1h4WJOz7WKs0MjLz4PMSbvCrFInKfLy8xq8Th9V61tCrOdFJCadv0WvXbsWV65cQefOneHl5QUvLy907twZGRkZ+O9//wsAKCkpQWRkpOjBElHra2dnieXTa1bmfP7zJfx+raDFY35zMANJJ7Mhl0rwxTOD0d6eMzutxcpChq+eHQpbhQzpN0vw4rfHEX34KqpUAib0csOON8bhbb/esFHIDR0qUZNqE/vw8HAkJiVrkm5/f38kJiUjPDxcq8J2KSkpWP3RKgT0UcDfp+7n3t9Hjum9FVj90SqkpKTo7bkYq4SEBNj52DVZQR8ALD0sYedjh/j4+FaKzHjUrhpZt24dpk2dovmcpKSkYNrUKVi3bh0mT3q02cR+06ZNmPn0U6hUVkIqA1wfd4Xny55wfdwVUhlQqazEM089iU2bNjU6Ru1JGLfpbri+/jqKT9V9zOJTxbi+/jrcprk1eRJGrJMDYrZWFGs7iRjYMpKMkc5Jfa9evfDHH39g27ZteO211/Daa68hMTERZ86cgY+PD4CavS/PPvus6MESkWH49/fAlP4eUKkFvBVzEhVV2v0xa8jRjDx8kHIWAPDO430wtBv/2LU2qQQou+c9lEqAD4P6oVs7WwNFRaQ7e3t7rF27tl4RPD8/P6xdu7bZhD41NbXe0vtKlYD4s1V19tg/1lOKoMCAejOx5o4zkk27exvIvjk2ms/JkiVLNJ+rfXNscPrk0SYT+1u3bmH2rJmwsgD2zbGBv5ccWWuuIndrLrLWXMUUbzn2zbGBlQUwe9bMOqtl75aQkABbL1vkRmejYF8Bsv55FcVpNY9ZnFaMrH9eRcG+AuR+mw1bL9tGT8IY6174adOmIftaNqKjozGp7yQMth2MSX0nITo6GtnXslutWKOx7fEnAu4jqQdq2tpNnjwZzz//PF599VX4+flBKuXSWSJztnx6X7Szs0T6zRJE7bq/Zfg3iyvw8nfHUa0WMKW/B+aM7iZukKSVK7dLcW81FbUAZNw2/TooRLoQq+CeueKMZNMiIiJw8PARpDxpiTFd5JoTQCtWrNCcKBrTRY6UJy1x8PARRERENDhOcHAwKqtU2P5MTReGLSHW8O8px62kW5jiJUdssDXGdJFj+zM2qKxSITg4uMFxbt66iarcCiCroubkQM97Tg541ZwcQFYFqnIrcPPWzQbHEWuFRkhICJxdnZEbkwtB3XAJL0EtIDc2F86uzo0+r7u1ZDuJWPTxvIhaSudMXK1WY/ny5ejUqRPs7Oxw5coVAMCSJUv02ublgw8+gK+vL2xsbODk5KTVfQRBwNKlS+Hh4QFra2tMnDgR6eni7AkmamucbRX4MLBmGf5/frmE45n5Ot2/WqXGq/87gZvFSni3t9O6VzqJr3s7W9w7+SKTSNCtnY1hAiJqgZZU546KioLvyBHw36TE/sxqTVG8yMhI/HBRjSe21hz336SE78gRiIqK0v8Tgnh7tFuKM5JNE6t7gkqlglQCfHyoUjPOlhBrxIVaIzbYWjPO6oOVkEpqbt+QrMwsVBar8OPT1k2eHPjxaWtUFquQlZnV4DjmuhdeLOb6vMi06ZzUr1ixAt988w1Wr14NhUKhOd63b1/Nnnp9qKysREhICF566SWt77N69Wp89tln+PLLL3HkyBHY2trCz89Pqz/0RFTfpAc7IGhQJ6gFYH7MSZRXar8Mf3XqeRy5kgc7Szm+fHYIbC25Z9tQPBytsTKoH2R/nlSRSST4MKgvPBytDRwZkW5a2rpLzIJ7YhFrj7YYOCPZND8/P83n5O6VHYF9LOqs/Kj9XN27TaSWhcICVt42SL5YjZAt5Q2OExxbjpRL1bD0toaFouH2oiEhITqdHGjsJIO57oUXk7k+LzJdOif1GzduxH/+8x8888wzkMn+Oos3YMAAnDt3TtTg7rZs2TK88cYb6Nevn1a3FwQBUVFRiIyMxPTp09G/f39s3LgR2dnZSEhI0FucRObu3akPwt3BEpdvl+KTHee1us8Pp3Lwn18uAwA+Du6Pnm52+gyRtPDEsC7Yv2gCvn9uJPYvmoAnhnUxdEhEOhGrf7pYBffEINYebbFwRrJ5/v7+CAgMarJ7QkBgUJPdE1ycXSCFFK6PuSHxXHWD4ySdr4brY26QQdZoEr18+XLY2Nkh+XwzJwcuVMPGzg7vv/9+g+OY6154sZnr8zJXxrICSl/uq0/9uXPn0LVrV9jb2+PkyZPo0aMH/vjjDwwfPhwlJSX6ihUA8M033yAiIgIFBQVN3u7y5cvo2bMnTpw4gYEDB2qOP/TQQxg4cCD++c9/Nng/pVIJpfKvX2JFRUXw9PRkn3qiu+w5fxNz1v8GiQTY/PwoDO/e+Fn6izdLMH3NfpRWqvD8uB545/E+rRgpEZkjY+tbLZa5c+di3bp12DenZm917UzvtnOVCOij0Czp3p9ZjbHryxAeHt7k1sfi4mJEREQgNDS0zixxamoqYmJiEBUVpdXJinv7lUudpFAXqLXuV26sxHh9li5dig9WLMcUHzliQ2pmw2tVqgQEx5QjJb0af4tc0mgSHR0djVmzZkEqA6Z4yzWz6nXGiS1HysVqqFU1t585c2aDYyUlJWn6z8eFWiOwz1+z+vFnqxAUUw6g5j1t7D0z139f1HbVnjA9ePgIFBZyxMUnwN/fHykpKQgKDEBlVTV8R45otRO42tJrn/oHHngA+/btq3d8y5YtGDRokK7D6c2NGzcAAO7u7nWOu7u7a65ryMqVK+Ho6Ki5eHp66jVOIlM0oVd7PDHUE4IAzI89iVJldYO3K1VW48Vvj6G0UoUR3V2wwK9XK0dKRObIWPunFxcXIywsDG+//XadPf5vv/02wsLCmp0JEmuPdm0sYi3jN8cZSTFen6SkpHoJ/b3dE7aEWsPfW44PVixvdDuIk5MTpBJo9r03OM6f++OlEsDR0bHRmKRSKSzkMkzrJW+wReNUHzks5LImC1xzhQaZE2NbAaU3go4SEhIER0dHYdWqVYKNjY3w8ccfC//3f/8nKBQKYceOHTqNtXDhQgFAk5ezZ8/Wuc/69esFR0fHZsc+cOCAAEDIzs6uczwkJEQIDQ1t9H4VFRVCYWGh5pKVlSUAEAoLC3V6bkTmrrC8Uhj14S6h68JkITL+VL3r1Wq18Mp3x4SuC5OF4R/sFG4WVRggSiIyR0FBQYKdj53Q95u+zV7sfOyEoKAgvcdUVFQk9OnlIwAQpBIIVh2tBMfhjoJVRytBKqn5TtOnt49QVFTU5DjJycmCwkIuBPRRCMpIe0F410FzUUbaC9N7KwSFhVxITk5uMhbfkSMEB2uZsG+OjeY+kZGRmrH3zbERHKxlgu/IEc3GJJaioiIhPDxc2L59e53j27dvF8LDw1s1jrtfn2m9LASZVCJ07dpVkEklwvTeFlq9PuPGjRMACPvm2Gjen6m95AIAYVpvueb92zfHRgAgjBs3rsFxwsPDdRonPDy8wXG2b99e77OjjLQX4kKt6/xc+3m493241/fffy8oLBUCAMHOx05wGO4g2PnYCQAEhaVC2LRpk24vPNF9aOnvjYb+fU3vXfO5vvvfSnP/vgyhsLBQ6zxU55n66dOnIykpCbt27YKtrS2WLl2Ks2fPIikpCY8++qhOY7311ls4e/Zsk5cePXroGiIAoEOHDgCA3NzcOsdzc3M11zXE0tISDg4OdS5EVJ+DlQVWBw8AAEQfvooDF2/XuX79gQwk/54DuVSCL54ZDDf7plvjEBFpSx/901tSRb+4uBgjhg1F5uULNa3EfOSovFkBhbsClTcrMKVXTSuxzEsXMGLY0CZngvz9/bFg4aIm92gvWLioyT3aYrVau/v5tXQvqjEVALz39YkNscLjXjJcvXoV/t4yxARbafX6ODo6wsJaisf+V479mdWaYnZuU900Re/2Z1bjsf+Vw8Ja2ugMe20Xhse/r6gZJ6Zm37uio6Jmf3xMzTiPf1/RZBcGMVs0FhcX41//jEKlshIWchn6ufbDYNvB6OfaDxZyGSqVlfgs6h+mO6tJJkGM3xtiroAyaq1wkkFU2s7Uq9VqoUOHDsInn3yiOVZYWChYWloK33//vdaPp8sZEqK26G/xvwtdFyYLvit/EorKKwVBEIRfr9wRei5OEbouTBbW7b9s4AiJyNyIPVO/bds2wdnVWTMj6TjcUTMj6ezqLCQmJjZ5/9mzZ+s00zp79uxGxxJjpl7MGdvaWW0AdR63Nk4Azc72i71yoKUzd9u3bxcs5DJhmo+8yddnqo9csJDLGn19xk8YLzgMcRDsvKxrVmjIIXSN6Cr0/aav0DWiqyCV16zQsPOyFuyH2AvjJ4xv9jUCIFjIZcKoUaOE8RPGC6NGjRIs5LJWfZ2NdaUHtS1ifg7F+L1qCHqdqTeUzMxMpKWlITMzEyqVCmlpaUhLS6tTmK93796Ij48HAEgkEkRERGDFihVITEzEqVOnalrcdOyIgIAAAz0LIvOz+LE+8HSxxvWCcvwt/hR+OJWNF6OPoVotYNqAjgjz7WboEInIzIhZnVuMKvpubm46tRJr3759g+OkpqZq9njePYN0997q2ln3oMCAejPntcRqtSbWXlQxVw7cPXM3dYo/fH19MeHhCfD19cXUKf5azdw99NBDsLS2RnJ6M1Xi06thaW2Nhx56qMFxXJxdoC5Ww/OtbnAa6wTP17vCfmBNkS37gfbwfL1rzfG3ukEoFpps/XZ3F4ak5BQcPHgQe3bvwcGDB5GUnKJVFwaxWjSKvdKD6H6I+TkUYwWUsdMqqXd2doaLi4tWF31ZunQpBg0ahHfffRclJSUYNGgQBg0ahKNHj2puc/78eRQWFmp+XrBgAV599VU8//zzGDZsGEpKSrB9+3YW9CASka2lHB//uQw/8WQOXv7uBO6UVqK9vSVWBvWDRNJwESsiovslVv/0iooKhIWHwW6gHTznecKyQ91tQpYdLOE5zxN2A+0QFh7W6FL8y5cvQ+FhpVWfcYWHFS5dutTgOGIunzamZfxiLX+tTehPpf2GfXNsMLmHBEcOH8Kh84dw5PAhPNZDgn1zbHAq7bcmE/vY2FiUFJfAaYJLky3knMa7oKS4pNFCi7Unl6oLq9F5bmfY96ubJNv3s0fnuZ1RXVCtVes3e3t7rF27tt5JFj8/P6xdu1arqtxitGhsM8uVyaiJ+TlMSUnB6o9WIaCPosECktN7K7D6o1Wa5f2mSKuWdhs2bND8/507d7BixQr4+flh1KhRAIBDhw4hNTUVS5YswRtvvKG/aA1Al1YCRG1VTmE5fFfuxt2/TKQS4MCih+HhaG2wuIjIfCUlJSEgIAB2A+3gHupeJyFX5iiRG5uLkrQSJCQkNFqdvbaVmPcq73oJ/d2UOUqkL05vtJXYhIcn4ETpCSjcFbiVdKvRVmJuU92gzFVisO1g7Nm9p944d8+MpzxpiU8OVePHS2osWLgIqz9ahce9pHhrpBz+m5TNzrbWtmq6e9a/1r0z9Y0l9qmpqZg2dUq9lQMpF6rh7yOvN+ufmJTc6Ky/GPE01PIvOLYcSeerMa33X5Xjm2v5N2PGDPxw+IeaegdeTbSQu1QNRXsrPD7ycWzdurXeOObc+k2M94uopYzt91hrE72l3ezZszWXAwcO4P3338f333+P1157Da+99hq+//57vP/++9i7d68oT4CITMuV26W49+ygWgAybpcZJB4iMn9Tp05FfHw8ZFdlSF+UjowPM5D5RSYyPsxA+uJ0yK7KmkzoASAhIQF2PnZNJvQAYOlhCTsfO80Wv3u5OLtAeU2JOz/ewrTejbQS6yXHnR9vofJaZaPLsMVaPm1sy/gBcVYOBAQE1GxzONjMNocDNdscGttuefHiRVTeqNCqhVzljQpcvHixwXHMufVbW1iuTPolRoFNMT6HYq6AMmY676lPTU3F5MmT6x2fPHkydu3aJUpQRGRaurezxb0TFDKJBN3a2RgmICJqE1raP12sKvo9evRAZY6WSWJOBXr27Nno44ixfNrYlvED4ix/LSgogFqAVtsc1ALqbMm8W2FhIdRq4O1Rijr3C4oprzPuAl8F1OrGxwHEOblkjNrCcmXSH7G6XYjxOaztLuG/SYn9mdWaE5GRkZGaE5b7M6vhv0nZZHcJY6dzUu/q6opt27bVO75t2za4urqKEhQRmRYPR2usDOoH2Z/752USCT4M6sul90Skd1ZWVpg5cya2bt2KPbv3YOvWrZg5c6ZWs6Iuzi5QFai0ehx1gbrRGfZbt25BLWiZJArAzZs3m3yslu6tFvNLrBhfqsVaOVC7ssL1cbcm98K7Pu7W5MqKd955B1IJMLmZVnST/1cOqQT429/+1uhzA1p+csnYiPV+UdskVoFNsT6HYq2AMnq6ltZfv369IJPJhClTpgjLly8Xli9fLkyZMkWQy+XC+vXrda/Vb+TY0o5Ie9kFZcLBi7eF7IIyQ4dCRNSsjRs3CgAE71XeTbbF817pLQAQoqOjGxynqKhI6NPbR7C1qGlrN7WXXJDKIbhNdROk8pq2dvvm2Ai2FhD69PZplRZgYrSiE6s1Xnh4eP2Wfz5/tvzrVb/lX3h4eIPjjJ8wXrDxsdG8pg21pqp97a19rBttIVdeXi44uTgJCjtZk63oFHYywcnFSSgvL9fx1TdtDb1f03srBAB1PgvNvV/UNon1+RH7c9jSVpiGoEseqlWhvHsdOXIEn332Gc6ePQsA6NOnD1577TWMGDGiRScYjBEL5REREZknMQudFRcXY8SwoTh7/gKkEkDhYQVFZwUqr1WiMqcCagHo09sHR3492mozQcXFxYiIiEBoaGidWf/U1FTExMQgKiqqyVgaKkwXukWJbecqEdBHoZk9a64wXe1rk3n5ArbPtMHqg5VIuVQN18fccOfHW5jiJcfboxSY/G0ZuvTwwZHfGn6NxowZg0MHD2BKr7rbHO4teBUcW46UC9UY5Tsa+/fvb/C5JSUlYfr06ZC7yOE23Q0u4/5ahZG3Nw+3Em+hOq8a27ZtM7mZ9pYSs2AjtT1iFabj51C3PPS+kvq2hEk9ERGR+RKjin6t4uJivPrqq2jfvj0uXbqEvPw8uDi7oGfPnrh58yb+9a9/mdSXTrG+VFdUVMCjkwfKKotRWaKCVA54zqvp6V6cVoysNVehrgYUdjLYKOyRcz2nwZMnDz30EH755Retq9+PGzeuySLOiYmJCAsPQ/6dfNj52EHqJIW6QI2SCyVwdnXGhvUb2lxCX6v2vT94+AgUFnJNdfHaauSVVdXwHTnCLBMpajmxuie09c+h6El9aWkpbG1ttQ5A19sbMyb1RERE5o3JXePE+FJd2zqw57KeuLPrDhyHO9bp6V58qhiFvxbC9RFXXHrvUqOtA2/duoXOnTxgIVFh+zNNzPh/V4YqQYZr13Pg5ubW5POrqKjAli1bEB8frzkJExgYiODgYJOqVq8PLV3pQW3bkiVLsGLFikZbfEZGRmL58uXNjtOWP4eiJ/UeHh54/fXXMXv2bHh4eDR4G0EQsGvXLnz66acYN24cFi9efH/RGxkm9UREROaPyV3jWvqlesaMGdhxege6vdOt2cfK+DADk/pOarAvPABs3rwZzzz1JFQCIJUBnq/eNeP/r6tQqwCZBPju+0144okndH6uRNRyYs3Ut3WiJ/Xnz5/HO++8g5SUFAwYMABDhw5Fx44dYWVlhfz8fPzxxx84dOgQ5HI5Fi9ejBdeeAEymXYtYowdk3oiIiKi+zfh4Qk4UXoCni97NnvbzC8yMdh2MPbs3tPobTZt2oTZYbNRqayst7JCYanAxg0bmdATGYhYe+pJtzxU3uS1f+rVqxe2bt2KzMxMxMbGYt++fTh48CDKy8vRrl07DBo0CF9//TUee+wxs0nmiYiIiKjlXJxdoLquQ+vAzg23Dqz15JNPIiAgoO7Kis4uCFzClRVEhhYTE4PKqmq8NdKmTgJ/b4HN+aPk2HauDDExMUzqRcBCec3gTD0RERHR/avdU++9yrtOIcJ7KXOUSF+c3uieejJNbXlPdFvEqvXi0SUPlbZSTERERETUBoWEhMDZ1Rm5MbkQ1A3PJQlqAbmxuXB2dUZwcHArR0j6UpvgrVu3DtOmTkFKSgqAmj3X06ZOwbp16zB50qMoLi42cKRUq7i4GHPnzkVqamqd46mpqZg7d26z75W9vT2279iJvgOGYuz6Ms3e+eXLlyMuPgE/XFRj7PoyJvQiY1JPRERERHpjZWWFDes3oCStBFlrsqC8oaxzvTJHiaw1WShJK8GG9Ru4fN5M3D1ju2+ODR7rKUVQYACWLFmiKaK2b44NTp88ysTeSIh1EqY2sQ8PD0diUrKmGJ6/vz8Sk5IRHh7OhF5kXH7fDC6/JyIiImo5tg5sW+bOnYt169Zh3xwbjOkib3Rv9f7MaoxdX4bw8HCsXbvW0GG3WVw2b3xEr37fljGpJyIiIhIHWwe2HayCblp4Esb46CWpf//99zF//nzY2NiIEqSpYFJPRERERKQ79is3HTwJY3z0Uihv2bJlKCkpaXFwRERERERk/vz9/bFg4SIknK1EyoXqOtelXKjGtnOVWLBwERN6I+Dn56cpZPfEViUqVQIUMgkC+1jUS+jj4hOY0BsZrZN6rtInIiIiIiJtpaSkYPVHqxDQRwF/H3md6/x95JjeW4HVH63SFGQjw+JJGNOlU/V7iUTS/I2IiIiIiKhNS01Nrbf0vlIlIP5slWYWOCbYUlMV/94WatT6eBLGdOmU1Pv4+MDFxaXJCxERERERtW0xMTGorKrGWyPr7scOiimvs7x7/ig5KquqERMTY+iQTVpL+8vzJIxpkzd/k78sW7YMjo6O+oqFiIiIiIjMQFRUFM79cQb+m44i5UloWqRFRkZi9Uer8MRWpaZFmu/IEYiKijJ0yCarth3dwcNH8G30Rk3hwdpChZVV1Tj3x5km29D9dRLGps5JmHur388fJce2c2WIiYnhvnojonX1e6lUihs3bqB9+/b6jsmosPo9EREREZHu7k42FRbyBpNN35Ej2PO8BcTqL88+9cZHLy3tZDIZcnJymNQTEREREZFWiouLERERgdDQ0Dozu6mpqYiJiUFUVBSTwxYQs788T8IYF70k9ZypZ1JPRERERETGQ+z+8jwJYzz0ktS3VUzqiYiIiIjIWNXOpN+d2Ne6t78829GZDl3yUJ2q3xMREREREZHxYH95YlJPRERERERkothfnpjUExERERERmSD2lyeAST0REREREZFJ+qu/fN2ieEEx5Xhiq1KT2M8fJUdlVTViYmIMHTLpAZN6IiIiIiIiExQVFQXfkSPgv0mJ/ZnVmqJ4kZGR+OGiGk9srTnuv0kJ35EjEBUVZeiQSQ/kzd+EiIiIiIiIjI29vT2279iJyZMexdj1dfvLjxw5EkGBAUg4W8b+8maOM/VEREREREQmqjaxDw8PR2JSsqbKvb+/PxKTkhEeHs6E3syxT30z2KeeiIiIiIiIWhP71BMRERERkdkoLi7G3Llz61VvT01Nxdy5c1FcXGygyIgMj0k9EREREREZreLiYkye9CjWrVuHaVOnaPqtp6SkYNrUKVi3bh0mT3rUJBN7nqwgMTCpJyIiIiIio1Sb0J8+eRT75tho+q0vWbJE05993xwbnD55VKvEXqwkWoxxzPlkBbUuJvVERERERGSUIiIicPDwEaQ8aYkxXeSICbbEYz2lWLFiBR73kmLzjJrjKU9a4uDhI4iIiGh0LLGSaDHGEftkBbVtTOqJiIiIiMgohYaGQmEhx98PV6NSJUAhkyAm2BJxodbYPMMSCpkElSoBnxyqhsJCjtDQ0AbHESuJFmscMU9WEDGpJyIiIiIio+Tn54e4+AT8cFGNJ7YqNYl9YB8LTUIfukWJHy+pERefAD8/vwbHESuJFmscsU5WEAFM6omIiIiIyIj5+/tjwcJFSDhbiZQL1XWuS7lQjW3nKrFg4SJNf/aGiJVEizWOWCcriAATSuo/+OAD+Pr6wsbGBk5OTs3evqqqCgsXLkS/fv1ga2uLjh07YtasWcjOztZ/sEREREREJIqUlBSs/mgVAvoo4O8jr3Odv48c03srsPqjVZq97Q0RK4kWMxkX42QFEWBCSX1lZSVCQkLw0ksvaXX7srIyHD9+HEuWLMHx48cRFxeH8+fPY9q0aXqOlIiIiIiIxJCamqrZq373THj82ao6M+W1e9vvrUZ/N7GSaLHGEeNkBRFgQkn9smXL8MYbb6Bfv35a3d7R0RE7d+5EaGgoevXqhZEjR2LNmjU4duwYMjMz9RwtERERERG1VExMDCqrqvHWSHmdmfCgmPI6M+XzR8lRWVWNmJiYRscSK4kWYxwxT1YQmUxSL4bCwkJIJBKtlu8TEREREZFhRUVFwXfkCPhvUmJ/ZrVmaXtkZKRmCfz+zGr4b1LCd+QIREVFNTiOWEm0WOOIebKCqM0k9RUVFVi4cCGeeuopODg4NHo7pVKJoqKiOhciIiIiImp99vb22L5jJ/oOGIqx68s0e9WXL1+u2ds+dn0Z+g4Yiu07dsLe3r7BccRKosUaR6yTFUQAAMGAFi5cKABo8nL27Nk691m/fr3g6Oio0+NUVlYKU6dOFQYNGiQUFhY2edt33323wTiaux8REREREelHUVGREB4eLmzfvr3O8e3btwvh4eFCUVFRs/f3HTlCcLCWCfvm2AjTeysEhYVciIyMFBQWciGgj0LYN8dGcLCWCb4jRzQ6nljj3D0WAEFhIReSk5MFQRCE5ORkQWEhFwA0OwaZr8LCQq3zUIkgCELrn0qocevWLdy5c6fJ2/To0QMKhULz8zfffIOIiAgUFBRo9RhVVVUIDQ3F5cuXsXv3bri6ujZ5e6VSCaVSqfm5qKgInp6eKCwsbHKGn4iIiIiIjFdxcTEmT3oUBw8fgcJCjrj4BPj7+yMlJQVBgQGorKqG78gRTc74izlO7VgREREIDQ2tUyk/NTUVMTExiIqKanYMMk9FRUVwdHTUKg81aFJ/P3RJ6msT+vT0dOzZswdubm46P54uLyYRERERERkvsZJoJuOkb2aZ1GdmZiIvLw+JiYn4+OOPsW/fPgCAl5cX7OzsAAC9e/fGypUrERgYiKqqKgQHB+P48eNITk6Gu7u7ZiwXF5c6s/9NKSwshJOTE7KyspjUExERERERkd7VrhgvKCiAo6Njk7eVN3mtEVm6dCk2bNig+XnQoEEAgD179mD8+PEAgPPnz6OwsBAAcP36dSQmJgIABg4cWGesu+/TnOLiYgCAp6dnC6InIiIiIiIi0k1xcXGzSb3JzNQbilqtRnZ2Nuzt7SGRSAwdTqNqz+RwRQGZA36eyZzw80zmhJ9nMif8PJMxEwQBxcXF6NixI6TSppvWmcxMvaFIpVJ07tzZ0GFozcHBgb+UyGzw80zmhJ9nMif8PJM54eeZjFVzM/S12kyfeiIiIiIiIiJzw6SeiIiIiIiIyEQxqTcTlpaWePfdd2FpaWnoUIhajJ9nMif8PJM54eeZzAk/z2QuWCiPiIiIiIiIyERxpp6IiIiIiIjIRDGpJyIiIiIiIjJRTOqJiIiIiIiITBSTeiIiIiIiIiITxaTeTHz++efo1q0brKysMGLECPz666+GDomoWb/88gumTp2Kjh07QiKRICEhoc71giBg6dKl8PDwgLW1NSZOnIj09HTDBEvUhJUrV2LYsGGwt7dH+/btERAQgPPnz9e5TUVFBV555RW4urrCzs4OM2bMQG5uroEiJmrcv//9b/Tv3x8ODg5wcHDAqFGj8OOPP2qu52eZTNmqVasgkUgQERGhOcbPNJk6JvVmYPPmzXjzzTfx7rvv4vjx4xgwYAD8/Pxw8+ZNQ4dG1KTS0lIMGDAAn3/+eYPXr169Gp999hm+/PJLHDlyBLa2tvDz80NFRUUrR0rUtL179+KVV17B4cOHsXPnTlRVVWHSpEkoLS3V3OaNN95AUlISYmNjsXfvXmRnZyMoKMiAURM1rHPnzli1ahWOHTuGo0eP4uGHH8b06dNx5swZAPwsk+n67bff8NVXX6F///51jvMzTSZPIJM3fPhw4ZVXXtH8rFKphI4dOworV640YFREugEgxMfHa35Wq9VChw4dhI8//lhzrKCgQLC0tBS+//57A0RIpL2bN28KAIS9e/cKglDz2bWwsBBiY2M1tzl79qwAQDh06JChwiTSmrOzs/Df//6Xn2UyWcXFxYK3t7ewc+dO4aGHHhJef/11QRD4+5nMA2fqTVxlZSWOHTuGiRMnao5JpVJMnDgRhw4dMmBkRC1z5coV3Lhxo85n29HRESNGjOBnm4xeYWEhAMDFxQUAcOzYMVRVVdX5PPfu3RtdunTh55mMmkqlwqZNm1BaWopRo0bxs0wm65VXXoG/v3+dzy7A389kHuSGDoBa5vbt21CpVHB3d69z3N3dHefOnTNQVEQtd+PGDQBo8LNdex2RMVKr1YiIiMDo0aPRt29fADWfZ4VCAScnpzq35eeZjNWpU6cwatQoVFRUwM7ODvHx8XjggQeQlpbGzzKZnE2bNuH48eP47bff6l3H389kDpjUExERieiVV17B6dOnsX//fkOHQnTfevXqhbS0NBQWFmLLli2YPXs29u7da+iwiHSWlZWF119/HTt37oSVlZWhwyHSCy6/N3Ht2rWDTCarV6EzNzcXHTp0MFBURC1X+/nlZ5tMybx585CcnIw9e/agc+fOmuMdOnRAZWUlCgoK6tyen2cyVgqFAl5eXhgyZAhWrlyJAQMG4J///Cc/y2Ryjh07hps3b2Lw4MGQy+WQy+XYu3cvPvvsM8jlcri7u/MzTSaPSb2JUygUGDJkCH766SfNMbVajZ9++gmjRo0yYGRELdO9e3d06NChzme7qKgIR44c4WebjI4gCJg3bx7i4+Oxe/dudO/evc71Q4YMgYWFRZ3P8/nz55GZmcnPM5kEtVoNpVLJzzKZnEceeQSnTp1CWlqa5jJ06FA888wzmv/nZ5pMHZffm4E333wTs2fPxtChQzF8+HBERUWhtLQUc+bMMXRoRE0qKSnBxYsXNT9fuXIFaWlpcHFxQZcuXRAREYEVK1bA29sb3bt3x5IlS9CxY0cEBAQYLmiiBrzyyiv43//+h23btsHe3l6zD9PR0RHW1tZwdHTE3Llz8eabb8LFxQUODg549dVXMWrUKIwcOdLA0RPVtXjxYjz22GPo0qULiouL8b///Q8///wzUlNT+Vkmk2Nvb6+pb1LL1tYWrq6umuP8TJOpY1JvBp544gncunULS5cuxY0bNzBw4EBs3769XoExImNz9OhRTJgwQfPzm2++CQCYPXs2vvnmGyxYsAClpaV4/vnnUVBQgDFjxmD79u3cE0dG59///jcAYPz48XWOr1+/HmFhYQCAf/zjH5BKpZgxYwaUSiX8/PzwxRdftHKkRM27efMmZs2ahZycHDg6OqJ///5ITU3Fo48+CoCfZTI//EyTqZMIgiAYOggiIiIiIiIi0h331BMRERERERGZKCb1RERERERERCaKST0RERERERGRiWJST0RERERERGSimNQTERERERERmSgm9UREREREREQmikk9ERERERERkYliUk9ERERERERkopjUExEREREREZkoJvVEREREREREJopJPREREREREZGJYlJPREREREREZKKY1BMRERERERGZKCb1RERERERERCZKbugAjJ1arUZ2djbs7e0hkUgMHQ4RERERERGZOUEQUFxcjI4dO0IqbXounkl9M7Kzs+Hp6WnoMIiIiIiIiKiNycrKQufOnZu8DZP6Ztjb2wOoeTEdHBwMHA0RERERERGZu6KiInh6emry0aYwqW9G7ZJ7BwcHJvVERERERETUarTZAs5CeUREREREREQmikk9ERERERERkYliUm8mcgrLcfDSbeQUlhs6FCIiIiIiImol3FNvBjb/lonFcaegFgCpBFgZ1A9PDOti6LCIiIiIiIhIzzhTb+JyCss1CT0AqAXgnbjTnLEnIiIiIiJqA5jUm7grt0s1CX0tlSAg43aZYQIiIiIiIiKiVsOk3sR1b2cL6T1dDiQAurWzMUg8RERERERE1HqY1Js4D0drrAzqB9ld/QulEgkqq9UGjIqIiIiIiIhaA5N6M/DEsC7Yv2gCvn9uBIZ3c4ZKELA8+ayhwyIiIiIiIiI9Y1JvJjwcrTGqZzt8GNQPcqkEu87m4ufzNw0dFhEREREREekRk3oz49XeHmG+3QAA7yf9wWX4REREREREZoxJvRl6baI32tlZ4vLtUnxz8IqhwyEiIiIiIiI9YVJvhhysLLBwci8AwD93peNmUYWBIyIiIiIiIiJ9MJmk/oMPPoCvry9sbGzg5OSk1X0EQcDSpUvh4eEBa2trTJw4Eenp6foN1EjMGNwZAzydUFqpwqrt5wwdDhEREREREemByST1lZWVCAkJwUsvvaT1fVavXo3PPvsMX375JY4cOQJbW1v4+fmhosL8Z66lUgmWTXsQABB3/DqOXc03cEREREREREQkNpNJ6pctW4Y33ngD/fr10+r2giAgKioKkZGRmD59Ovr374+NGzciOzsbCQkJ+g3WSAz0dELo0M4AgPcSz0ClFgwcEREREREREYnJZJJ6XV25cgU3btzAxIkTNcccHR0xYsQIHDp0qNH7KZVKFBUV1bmYsrf9esPeUo5T1wsRezTL0OEQERERERGRiMw2qb9x4wYAwN3dvc5xd3d3zXUNWblyJRwdHTUXT09Pvcapb272lnh9ojcAYHXqeRSWVRk4IiIiIiIiIhKLQZP6RYsWQSKRNHk5d651i7wtXrwYhYWFmktWlunPbs/27Qav9nbIK63EP3ZdMHQ4REREREREJBK5IR/8rbfeQlhYWJO36dGjx32N3aFDBwBAbm4uPDw8NMdzc3MxcODARu9naWkJS0vL+3pMY2Uhk+LdqQ/g2bW/IvrwVTw1vAt6dbA3dFhERERERETUQgZN6t3c3ODm5qaXsbt3744OHTrgp59+0iTxRUVFOHLkiE4V9M3FWG83+D3ojtQzuXgv8Qz+99wISCQSQ4dFRERERERELWAye+ozMzORlpaGzMxMqFQqpKWlIS0tDSUlJZrb9O7dG/Hx8QAAiUSCiIgIrFixAomJiTh16hRmzZqFjh07IiAgwEDPwrAi/R+ApVyKQ5fv4MfTjdcVICIiIiIiItNg0Jl6XSxduhQbNmzQ/Dxo0CAAwJ49ezB+/HgAwPnz51FYWKi5zYIFC1BaWornn38eBQUFGDNmDLZv3w4rK6tWjd1YeLrY4IWHeuKzn9LxQcpZTOjVHtYKmaHDIiIiIiIiovskEQSBzcubUFRUBEdHRxQWFsLBwcHQ4bRYeaUKEz/di+sF5XjtEW+8+aiPoUMiIiIt5BSW48rtUnRvZwsPR2tDh0NERER6pEseajLL70kc1goZ/ubfBwDw5d5LyMorM3BERETUnM2/ZWL0qt14+usjGL1qNzb/lmnokIiIiMhIaLX8/s0339R54MjISLi4uOh8P9K/x/p2wKgerjh0+Q4+SDmLL58dYuiQiIioETmF5VgcdwrqP9fVqQXgnbjTGOfjxhl7IiIi0i6pj4qKwqhRo6BQKLQadP/+/Zg3bx6TeiMlkUjw3rQH8fhn+7D9zA3sT7+NMd7tDB0WERE14MrtUk1CX0slCMi4XcaknoiIiLQvlBcfH4/27dtrdVt7e/ZAN3a9Otjj2ZFd8c3BDLyXdAY/vj4WFjLuxiAiMjZdXWzqHZNKgG7t6h8nIiKitkerLG79+vVwdHTUetCvvvoK7u7u9x0UtY43JvrAxVaBizdLsOFghqHDISKiBhy4eKfeMQcrC1hbsHsJERERaZnUz549G5aWlloP+vTTT8PW1va+g6LW4WhjgQV+vQAA/9yVjlvFSgNHREREdyssq8JH288BAF6d4IX/zh6Kjk5WKCivwlsxJ6G+d10+ERERtTlcb93GhQz1RL9OjihWVuPj1HOGDoeIiO7yj10XcKe0El7t7fDaRG9M7OOO/zw7FAq5FD+du4kvf7lk6BCJiIjIwLRK6p2dneHi4qLVhUyLTFpTNA8AYo5eQ1pWgWEDIiIiAMDZnCJsPJQBAFg27UFN3ZO+nRzx/p+/tz9JPY9Dl+ovzyciIqK2Q+vq97Xu3LmDFStWwM/PD6NGjQIAHDp0CKmpqViyZIlegiT9GtLVGUGDOyHu+HUsjjuFyMf7oEd7W1ZVJiIyEEEQsHTbaagFwL+fB0Z71e1Q8sQwT/yakYe449fx6vcn8MNrY9DewcpA0RIREZEhSQRB0GlD3owZMzBhwgTMmzevzvE1a9Zg165dSEhIEDM+gysqKoKjoyMKCwvh4OBg6HD05mZRBcZ8tBuVqpqPg1QCrAzqhyeGdTFwZEREbU/CieuI2JwGawsZdr31EDo51T/JWlZZjcDPD+J8bjFGdHfBd/83AnJ2MSEiIjILuuShOv/1T01NxeTJk+sdnzx5Mnbt2qXrcGQkVIKAKtVf53fUAvBO3GnkFJYbMCoioranuKIKH/xwFgAw72GvBhN6ALBRyPHFzMGwVchw5Eoe/r7zQmuGSUREREZC56Te1dUV27Ztq3d827ZtcHV1FSUoan1Xbpfi3iUbKkFAxu0yg8RDRNRW/Wv3RdwqVqKbqw3+b2z3Jm/b080OHwX3BwD8++dL+OlsbmuESEREREZEqz31d1u2bBn+7//+Dz///DNGjBgBADhy5Ai2b9+Or7/+WvQAqXV0b2cLqaRmhr6WVAJ0a2djuKCIiNqY9NxirNt/BQDw7tQHYSlvvhf9lP4dcTQjH98czMAbm9OQ8tpYeLrwdzcREVFbofNMfVhYGA4cOAAHBwfExcUhLi4ODg4O2L9/P8LCwvQQIrUGD0drrAzqB6nkr2MBgzqxWB4RUSsRBAHvJZ1BtVrAxD7umNC7vdb3fefxPhjo6YSiimq8/N1xKKtVeoyUiIiIjInOhfLamrZSKK9WTmE5Pt9zEd8ezkQPN1vseuMhSO/O9ImISC9+OJWDl787DoVcil1vPIQurrrNtl8vKIf/Z/tQUFaFmSO7YEVAPz1FSkRERPqm10J5AHDp0iVERkbi6aefxs2bNwEAP/74I86cOXM/w5ER8XC0xqLH+sDeSo7Lt0qxi/sziYj0rqyyGiuS/wAAvPhQT50TegDo5GSNqCcGQiIBvj2ciW1p18UOk4iIiIyQzkn93r170a9fPxw5cgRbt25FSUkJAODkyZN49913RQ+QWp+dpRzPjuwKAPjql8sGjoaIyPx9secSsgsr0MnJGi891PO+xxnfqz3mTfACACyOO4X03GKxQiQiIiIjpXNSv2jRIqxYsQI7d+6EQqHQHH/44Ydx+PBhUYMjwwnz7QaFTIpjV/NxNCPP0OEQEZmtK7dL8Z8/T6AunfoArBXNF8drSsREH/j2dEVZpQovfXccpcpqMcIkIiIiI6VzUn/q1CkEBgbWO96+fXvcvn1blKDI8No7WCFocCcAnK0nItIXQRCwLOkMKlVqjPNxw6QH3Fs8pkwqwWdPDYK7gyUu3izB3+JPgeVziIiIzJfOSb2TkxNycnLqHT9x4gQ6deokSlBkHP5vbA8AwK6zubh4s8TA0RARmZ+fzt7Ez+dvwUImwbtTH4BEIk5h0nZ2lljz9GDIpBIkpGXjuyOZooxLRERExkfnpP7JJ5/EwoULcePGDUgkEqjVahw4cADz58/HrFmz9BEjGYhXeztM7OMOQQD+u4+z9UREYqqoUmFZck2B2bljeqCnm52o4w/r5oKFk3sBAN5P+gO/XysQdXwiIiIyDjon9R9++CF69+4NT09PlJSU4IEHHsC4cePg6+uLyMhIfcQIAPjggw/g6+sLGxsbODk5aXWfuLg4TJo0Ca6urpBIJEhLS9NbfObqxYdqZuvjjl/HzeIKA0dDRGQ+/vPLZWTllaODgxVefdhLL4/x3NgemPSAOypVarz83XEUllXp5XGIiIjIcHRO6hUKBb7++mtcunQJycnJ+Pbbb3Hu3DlER0dDJmtZcZ+mVFZWIiQkBC+99JLW9yktLcWYMWPw0Ucf6S0ucze0mwsGd3FCpUqNbw5kGDocIiKzkJVXhs/3XAQA/M2/D2wt5Xp5HIlEgo9DBqCLiw2u5ZfjzZg0qNXcX09ERGRO7vtbRJcuXdClSxcxY2nSsmXLAADffPON1vd59tlnAQAZGRl6iKjteOGhnngh+hi+PXwVL0/wgp2evnwSEbUVK1L+gLJajZE9XDClv4deH8vR2gJfPDMYQf8+iJ/O3cTHO85jrHc7dG9nCw9Ha70+NhEREemfztmZIAjYsmUL9uzZg5s3b0KtVte5Pi4uTrTgDEGpVEKpVGp+LioqMmA0xuHRPu7o0c4Wl2+XYvNvWZg7pruhQyIiMll7L9xC6plcyKQSLJvWV7TieE3p28kRy6Y9iMVxp/Dvny/h3z9fglQCrAzqhyeGtd4JeiIiIhKfzsvvIyIi8Oyzz+LKlSuws7ODo6NjnYupW7lyZZ3n4+npaeiQDE4qleC5cTV769fuu4wqlbqZexARUUMqq9VYllhTHG/2qG7o1cG+1R77IZ92dX5WC8A7caeRU1jeajEQERGR+HSeqY+OjkZcXBwef/zxFj/4okWLmt3vfvbsWfTu3bvFj6WtxYsX480339T8XFRUxMQeQOCgTvj7jgvILqxAyu85CBjE9oVERLpad+AKLt8uRTs7S0Q86t2qj51xp6zeMZUgION2GZfhExERmTCdk3pHR0f06NFDlAd/6623EBYW1uRtxHosbVlaWsLS0rJVH9MUWFnIMGd0N3yceh5f7r2E6QM7tsqSUSIic5FTWI7PfkoHACx+rDccrCxa9fG7t7OFVFIzQ3+3rLwyjOrp2qqxAEBFRQViY2ORkJCAvPw8uDi7ICAgACEhIbCysmr1cYiIiEyVzsvv33vvPSxbtgzl5S1frufm5obevXs3eVEoFC1+HBLHzBFdYaOQ4dyNYuxLv23ocIiITMqHP5xDWaUKQ7o6I9AAq508HK2xMqgfZPeckF0cfwqxR7NaNZbExER07NwRs2bNwo7TO3Ci9AR2nN6BWbNmoWPnjkhKSmrVcYiIiEyZzjP1oaGh+P7779G+fXt069YNFhZ1ZxqOHz8uWnB3y8zMRF5eHjIzM6FSqTQ95728vGBnZwcA6N27N1auXInAwEAA0Nw+OzsbAHD+/HkAQIcOHdChQwe9xGnOHG0s8OSwLlh34Aq++uUSxvm4GTokIiKTcOjSHSSdzIZEAiyb9iCkUsOsdHpiWBeM83FDxu0ydHK2wj93XcTW49fw9pbfkVdaiRce6qn3GBITExEYGAi7gXbwftsblh3+Wh2nvKFEbkwuAgICEB8fj2nTpul9HCIiIlMnEQRBp4a1oaGh2LNnD4KDg+Hu7l5vCfa7774raoC1wsLCsGHDhnrH9+zZg/HjxwOo6ce7fv16zZL+b775BnPmzKl3n3fffRfvvfeeVo9bVFQER0dHFBYWwsHB4X7DNxvX8svw0Mc/Q6UWkPzqGPTtZPrFEYmI9CkzrxTPfH0EWfnlmDmyC1YE9DN0SBqCIGDVj+fw1S+XAQDPj+uBxY/11tv2qoqKCnTs3BGqrip4zvOEpIGTG4JaQNaaLMiuypB9LbvBJfRijXPvmFzGT0RExkKXPFTnpN7W1hapqakYM2ZMi4I0FUzq63t90wlsS8vGtAEd8dlTgwwdDhGR0dr8WyYWbT2F2j+07059AHNGG19b0K/2XsLKH88BAGYM7oyPZvSDXKbzDr1mRUdHY9asWfBeVXdm/V7KHCXSF6cjOjoaM2fO1Ns4tRITExEWHob8O/mw87GDzEkGVYEKJRdK4OzqjA3rN2Dq1Km6PVkiIqIW0CUP1fkvtqenJ5PbNu75P9vbpZzKQVZe/WrKRERUUxhvcdxfCT0ArEg+a5Qt5F54qCc+Du4PmVSCrcev4YXoYyivVIn+OAkJCbDzsWsyEQcASw9L2PnYIT4+Xq/jAH8t41d1VcF7lTe6vdMNni97ots73eC9yhuqrioEBAQgMTGx+SdIRERGqbi4GHPnzkVqamqd46mpqZg7dy6Ki4sNFJk4dE7q//73v2PBggXIyMjQQzhkCh7s6Iix3u2gUgtYu/+KocMhIjJKV26X1qs0X9tCzhiFDPXEVzOHwFIuxU/nbuLZtUdQWFYl6mPk5edB5iTT6rZSJyny8vP0Ok5FRQXCwsNgN9AOnvM8650ksOxgCc95nrAbaIew8DBUVFRo9ZhERCQOMZLx4uJiTJ70KNatW4dpU6cgJSUFAJCSkoJpU6dg3bp1mDzpUZNO7HVO6mfOnIk9e/agZ8+esLe3h4uLS50LtQ0vjKspprT5tyzkl1YaOBoiIuNT1sBMt0wiQbd2NgaIRjsTH3DHt/83AvZWchy9mo/Qrw4ht0i8RNbF2QWqAu1WAKgL1HBxbvh7hVjjxMbGIv9OPtxD3Rvclw8AEqkE7iHuyL+Tjy1btmj1mERE1HJiJOO1Y5w+eRT75tjgsZ5SBAUGYMmSJQgKDMDjXlLsm2OD0yePmnRir3P1+6ioKD2EQaZmtJcrHvBwwB85Rfj28FW8+oi3oUMiIjIaarWAf+2+CACQABBQk9B/GNQXHo7WBo2tOcO6uSD2xVGYtfZXnM8tRtAXBxE9dzh6uNm1eOyAgADExcVBeUPZ7F74kgslCFwSqNdx7mcZf1N784mISBz3JuOfHKpGUGAAFixchNUfrcLjXlK8NdIG/ptqkvHtO3bC3t6+3jgRERE4ePgI9s2xwZgucgzvJEPoFiVWrFiBgD4KbJ5hCYVMgpQngbHrjyAiIgJr1641wDNuGZ0K5VVVVeGFF17AkiVL0L278RX60QcWymvctrTreH1TGlxtFTiw6GFYWWi3FJKIyNzFHM3Cgi2/w85Sju+fG4ESpQrd2tkYfUJ/t6y8Msxa9yuu3C6Fq60C38wZjn6dW9bxxNiq3094eAJOlJ6A58uezcae+UUmBtsOxp7de7R8tkREdL/mzp2LdevWaZLxSpWA0C1KbDtXWScZ359ZjbHryxAeHt5gMp6amoppU6fgcS+p5j6VKgEpF6rh7yPX/By6RYkfL6mRmJQMPz8/Azzj+vRWKM/CwgJbt25tUXBkPvz7eaCTkzXulFZi6/Frhg6HiMgoFFVUYfX2mkryrz3ihX6dnTCqp6tJJfQA4Olig9gXR6FvJwfcKa3Ek/85hAMXb7doTCsrK2xYvwElaSXIWpMF5Q1lneuVOUpkrclCSVoJNqzf0GgrObHGEWsZPxERiSs0NBQKCzn+frgalSoBCpkEMcGWiAu1rpOcf3KoGgoLOUJDQxscx8/PD3HxCfjhohpPbFVqxgrsY1EvoY+LTzCahF5XOu+pDwgIQEJCgh5CIVMjl0nxf2NrVmz8d98VqO6tCEVE1AZ9tisdt0sq0cPNFmG+pr2qrZ2dJb5/biR8e7qitFKFOet/Q8rvOS0ac+rUqYiPj4fsqgzpi9KR8WEGMr/IRMaHGUhfnA7ZVRkSEhKabSEnxjgBAQEouVBS76TAvTTL+AMbXsZPRETiEjMZ9/f3x4KFi5BwthIpF6rrXJdyoRrbzlViwcJF8Pf31/fT0hud+9SvWLECf//73/HII49gyJAhsLW1rXP9a6+9JmqAhsbl900rVVbDd9VuFJZX4cuZgzG5r4ehQyIiMpiLN4sxOWofqtUCvpkzDON7tTd0SKJQVqvwxuY0/HDqBiQS4P3pfTGxT3tcuV2K7u1s72sVQkVFBbZs2YL4+Hjk5efBxdkFgYGBCA4ObnRmXexxxFrGT0RE+rFkyRKsWLECcaHWCOxjoTkef7YKQTHliIyMxPLly5scIyUlRVMUr3aWv9a9JweMKbHXJQ/VOalvai+9RCLB5cuXdRnO6DGpb97fd5zHv3ZfxEBPJ8S/7AuJpOEKwkRE5kwQBDy79lfsv3gbE/u447+zhxo6JFGp1AKWbjuN745kAvirAKBUAqwM6ocnhnUxaHz3KykpCQEBAbAbaAf3UPc6RfOUOUrkxuaiJK1Eq9UDRERUo7i4GBEREQgNDa0zi56amoqYmBhERUU1WNjubmIk421lT73OSX1bw6S+ebeKlRj90W5UVqsR88IoDO/OPYdE1PaknrmBF6KPQSGXYucb49DV1bb5O5kYQRCwPPkPrDuQUee4TCLB/kUTTK5uQK3ExESEhYch/04+7HzsIHWSQl2gRsmFEji7OmPD+g1tPqGvqKhAbGwsEhISNCsiAgICEBISwtULRkis94vvO92P2sr1Bw8fgcJCrkm6a5P0yqpq+I4c0WjFekC8ZFysgnuGoLdCefcSBAE8J0Bu9paYMbgzAOA/v1wycDRERK2vokqF5cl/AACeH9vDLBN6oGZF3sQH3OsdVwkCMm6XGSAicUybNg3Z17IRHR2NSX0nYbDtYEzqOwnR0dHIvpatU0JfUVGB6OhozJgxAxMenoAZM2YgOjoaFRUVenwG+pWYmIiOnTti1qxZ2HF6B06UnsCO0zswa9YsdOzcEUlJSYYOke4i1vvF953uh1h94WNiYlBZVY23RtZN4INiyuvssZ8/So7KqmrExMQ0OE5UVBR8R46A/yYl9mdWa04CREZGavbr78+shv8mJXxHjjDZ9u33NVO/ceNGfPzxx0hPTwcA+Pj44O2338azzz4reoCGxpl67Vy+VYJHPt0LQQB2vjEO3u5NL6chIjInn/2Ujk93XkAHByvsnv8QbBRyQ4ekNzmF5Ri9ajfuro1q6jP1Yrl3xl/mJIOqQGXSM/6JiYkIDAxseHvCDSVyY2q2J8THx2PatGkGjJQA8d4vvu90v8SaGb/75EDKk5b45FA1frykvqdPvRz+m5ToO2Bok7P+YqwcMAS9Lr//9NNPsWTJEsybNw+jR48GAOzfvx+ff/45VqxYgTfeeOP+IzdCTOq190L0UaSeyUXo0M5YHTzA0OEQEbWKa/llmPjpXlRUqfHZU4MwbUBHQ4ekd5t/y8Q7caehEgTIJBJ8GNTXZPfUi8UckyAWEjQtYr1ffN+pJcTcwy5mMi7GHv/WpvdCecuWLcOsWbPqHN+wYQPee+89XLlyRfeIjRiTeu0dz8xH0BcHYSGTYP/Ch+HuwF/wRGT+XvnuOFJO5WB4dxdsfn5kmykWmlNYjozbZejWzqbNz9CbaxIUHR2NWbNmwXuVd52TFPdS5iiRvjgd0dHRmDlzZitGSHcT6/3Sx/vOvflti5jV5k0xGReLXvfU5+TkwNfXt95xX19f5OS0rHctmbbBXZwxrJszqlQC1t9TRImIyBwdvHQbKadyIJUA7019sM0k9ADg4WiNUT1d23xCDwCxsbHIv5MP91D3BhN6AJBIJXAPcUf+nXxs2bKllSO8PwkJCbDzsWsysQMASw9L2PnYIT4+vpUio4aI9X6J/b5zb37bI2ZfeHt7e6xdu7bebL6fnx/Wrl1rtgm9rnRO6r28vBosRLB582Z4e3uLEhSZrhfG9QQAfHfkKoorqgwcDRGR/lSr1FiWWFMcb+bIrnigI1dztVXmmvzm5edB5iTT6rZSJyny8vP0HBE1Raz3S8z3vXZbiqqrCt6rvNHtnW7wfNkT3d7pBu9V3lB1VSEgIACJiYlaPR6ZhpSUFKz+aBUC+ijg71O3xoy/jxzTeyuw+qNVSElJMVCE5kfnpH7ZsmVYunQpJk+ejOXLl2P58uWYPHkyli1bhvfff18fMZIJebh3e/R0s0VxRTVW/XgOOYXlhg6JiEgvvj18Fedzi+FkY4E3H/UxdDgmpbi4GHPnzkVqamqd46mpqZg7d26j1ZCNlbkmvy7OLlAVqLS6rbpADRfn1mtpK1aXAXPqViDW+yXWOBUVFQgLD4PdQDt4zvOsd9LLsoMlPOd5wm6gHcLCw0zyNaf6UlNT6y29r1QJiD9bpalYHxNsqamKf+/fAbo/Oif1M2bMwJEjR9CuXTskJCQgISEB7dq1w6+//orAwEB9xEgmRCqVYJCnMwDguyOZGL1qNzb/lmngqIiIxHWnRIlPd14AAMyf1AtONgoDR2Q6agsfrVu3DtOmTtHM1KSkpGDa1ClYt25dk22OjJExJ78tERAQgJILJVDeUDZ5O2WOEiUXSrT6HihGEs2WbQ0T6/0Saxxz3ZZCTROrFR3p5r5a2rUlLJSnG7Y6IqK2YHHc7/j+1yw84OGApFfHQNbIF1aqS8wWRcbEXAuLiV0AUIyWf+besq0l77uxVb+fMWMGdpzegW7vdGv2eWd8mIFJfSdh69atzd6WjJu5/p43BL1WvwcAtVqNixcv4ubNm1Cr1XWuGzdunK7DGTUm9bo5eOk2nv76SL3j3z83EqN6uhogIiIicZ26Vohpn++HIACxL47CsG6mMetqDMTqX2xsjDH5FUtSUhICAgIaTn5zlMiNrUl+ExISmoxJjCTa2JJWsYnxvov1fokxzoSHJ+BE6Ql4vuzZ7HPP/CITg20HY8/uPc3eloyfqfaFNza65KHyJq9twOHDh/H000/j6tWruPd8gEQigUql3fIzMk/d29lCKkGdmXoA6OLCWXoiMn1qtYB3E09DEIDpAzsyoddRaGgovo3eiL8frsbwTjLN3sqUC7I6/Ys/OVQNhYUcoaGhhg5ZK1ZWVtiwfgMCAgKQtSar2SSouYS+Nvn1ftu7weQ3ICBA6xnkls74T506FfHx8QgLD0P6onTY+dhB6iSFukCtSTabSxDv3Vt9bxJdu7c6a00WwsLDGk2ia5dze7/t3exy7vTF6diyZUuDKyLEGufe59iS11ms912M90uscVycXaC6rsO2lM78fWou7O3tsX3Hznqt6Pz9/ZGYlGz2regMQec99S+++CKGDh2K06dPIy8vD/n5+ZpLXp7+Cr988MEH8PX1hY2NDZycnJq9fVVVFRYuXIh+/frB1tYWHTvW7JnKzs7WW4xU0+JoZVA/yO5p67Tr7E0DRUREJJ6EtOs4nlkAG4UMix/rY+hwTI6fnx/i4hPww0V1nb2VgX0s6uy9rO1ffG8Lo3sZU8G92iRIdlWG9EXpyPgwA5lfZCLjwwykL06H7KpM5+S3pYXFxNozPm3aNGRfy0Z0dDQm9Z2EwbaDManvJERHRyP7WnazCaJYe6vNtWWb2O97S98vscbRR00G0j+xfq+yFV3r0nn5va2tLU6ePAkvLy99xdSgd999F05OTrh27RrWrl2LgoKCJm9fWFiI4OBgPPfccxgwYADy8/Px+uuvQ6VS4ejRo1o/Lpff35+cwnJk3C7D0at5+PuOC7BRyJAaMQ6eLjaGDo2I6L6UKKsx4ZOfcatYiQWTe+Hl8a37d9CcLFmyBCtWrEBcqDUC+1hojsefrUJQTDkiIyOxfPnyJscw1uWdFRUV2LJlC+Lj4zUztoGBgQgODm52xlbMvfnGtGdcrL3VYi3nFnNZuBivsz5qMhgDY93mQI0z1t+rbZUueajOM/UjRozAxYsX7zu4+7Vs2TK88cYb6Nevn1a3d3R0xM6dOxEaGopevXph5MiRWLNmDY4dO4bMTFZj1zcPR2uM6umKV8Z7YUR3F5RVqrBw6+/1tmwQEZmKf/2UjlvFSnRztcHcMd0NHY7JEqN/8d2FmPbNsdG0RlqyZImmldK+OTY4ffJoq1fSt7KywsyZM7F161bs2b0HW7duxcyZM7VKVsSaQTa2VmJitfwz15ZtYq8cMBa121JK0kqQtSar3oy9MkeJrDVZKEkrwYb1G7T6N2JOLQiNjTH/XqXm6ZzUv/rqq3jrrbfwzTff4NixY/j999/rXIxZYWEhJBKJVsv3SRxSqQQfzegPKwspDl66g//9yhMqRGR6Lt0qwboDVwAAS6c+AEu5dgkK1SVW/+KIiAgcPHwEKU9aYkwXueY+K1as0Iw9poscKU9a4uDhI4iIiGjdJ3qfxEp+ja2VmFhJtLm2bBPrfTdGYmxLqWVuLQiNjbn+Xm0r7qtP/dmzZxEeHo5hw4Zh4MCBGDRokOa/xqqiogILFy7EU0891eTyBaVSiaKiojoXaplu7Wzxtl9vAMDKH87hekG5gSMiItKeIAh4P+kPVKkETOjlhod7uxs6JJMlVv/i0NBQKCzk+Pvh6jonA+JCreucLDC1gntiJb/GNvMrVhIdEhICZ1dn5MbkQri3Iu+fBLWA3NhcOLs6Izg4WK/jiPU6i/W+Gysx9vjXbnNQdVXBe5U3ur3TDZ4ve6LbO93gvcobqq4qBAQEIDExsRWekXky19+rbYXOSf2VK1fqXS5fvqz5ry4WLVoEiUTS5OXcuXO6hlhPVVUVQkNDIQgC/v3vfzd525UrV8LR0VFz8fRsfr8VNS/MtxuGdHVGibIai7gMn4hMyE9nb2LvhVuwkEmwdOqDhg7HpEVFRcF35Aj4b1Jif2a1piheZGSkpnje/sxq+G9SwnfkCERFRTU4jtgF94yFWMmvsc38ipVEi7WcW6xxxHqd20JBuZZsSzG27STmylx/r7YVOif1Xbt2bfKii7feegtnz55t8tKjRw9dQ6yjNqG/evUqdu7c2WyRgcWLF6OwsFBzycrKatHjUw2ZVILVwf1hKZdiX/ptxB69ZuiQiIiaVVGlwvvJfwAA5o7pge7tbA0ckWmrbXPUd8BQjF1fpvlyuHz5cs2XybHry9B3wNBmCzH5+/tjwcJFSDhbiZQL1XWuS7lQjW3nKrFg4SL4+/s3G5exVNEXK/k1tplfMfdWi7WcW4xxxHqdxXrfzZWxbScxZ2L+XqXWpVVSn5iYiKqqKq0H/eGHH1Be3vwSazc3N/Tu3bvJi0Kh0Ppx71Wb0Kenp2PXrl1wdXVt9j6WlpZwcHCocyFx9HSzw5uP+gAAlqf8gRuFPJNKRMYrp7Ac7247g8y8MrS3t8S8h1ntXgy1iX14eDgSk5I1Xw5r+xeHh4drVVlZjIJ7wF/FodatW4dpU6dobp+SkoJpU6dg3bp1rVYUSqzk1xhnfsXcW21uLdv0UVDOnBjbdhJzJtbvVWp9WrW0k8lkuHHjBtzc3LQa1MHBAWlpaS2eZb9bZmYm8vLykJiYiI8//hj79u0DAHh5ecHOzg4A0Lt3b6xcuRKBgYGoqqpCcHAwjh8/juTkZLi7/7UH0sXFReuTBWxpJ65qlRoz/n0QJ68V4uHe7bF29lBIJA2fdSUiMpTNv2Vicdwp1E6aPTnME6tm9DdsUKSRmpqKaVOn1Cu4l3KhGv4+8npLRROTkhtcKnp3teeUJy3xyaFq/HhJjQULF2H1R6vwuJcUb42Uw3+TUqvVA2JJTExEWHgY8u/kw87HDlInKdQFapRcKIGzqzM2rN/QbL97Y20l1pKWf8ZG7Ne5pe+7uRKzBSE1TqzfqyQeXfJQeZPX/kkQBISFhcHSsukzZLX0sZdl6dKl2LBhg+bn2qJ8e/bswfjx4wEA58+fR2FhIQDg+vXrmmIZAwcOrDPW3feh1iWXSfFxyABM+Ww/dp+7ifgT1xE0uLOhwyIi0sgpLK+T0ANA7NEsvD7RGx6O1oYLjDT+KrhnU+eL5rZzlQjoo9B8IZ0/So5t58oQExPT4JfP2mrP++bYYEwXOYZ3kiF0ixIrVqyoM07Kk8DY9TXVnteuXav351c7g1wn+e3sgsAl2iW/tTO/AQEByFqTVb9/eo4SubE1/dMTEhJaNZmu3VttCn3WmyP269zS991cuTi7QHVdh20OnZvfTlJRUYHY2FgkJCRoTi4FBAQgJCSkzb7OYv1eJcPQaqZ+zpw5Og/88ccfo127dvcVlDHhTL1+rNmdjk92XICjtQV2vjEO7R3a5i9QIjI+By/dxtNfH6l3/PvnRmJUz+a3cZH+iTXDbu4zU5z5bR18nfUrOjoas2bNgvcq7yaX4CtzlEhfnI7o6OgmTxrd+37JnGRQFaju6/0yp5MDxrpyqS3TJQ/VKqlvy5jU60eVSo2Azw/gTHYRJj3gjq+eHcJl+ERkFC7kFmPSP36pc0wmkWD/ogmcqTcitV9ADx4+AoWFHHHxCfD390dKSgqCAgNQWVUN35Ejmv3iWXv7uxP7WvdWezbF4lDmtNzdmPF11h8xtznUtsazG2hXf2XFDSVyY2pWVsTHx2PatGlNxiXmyQFjIdbvVRIHk3oRManXnz+yizBtzX5UqwX866lBmDqgo6FDIiLCwi2/Y/PRvzqfyCQSfBjUF08M62LAqKghxcXFiIiIQGhoaJ0Z9NTUVMTExCAqKkqrL55LlizBihUrEBdqjcA+Fprj8WerEBRTjsjISCxfvlwvz4GImpeUlISAgICGk/F7tjk0lkgb68kBYyPW71VqOSb1ImJSr1//2HkB//wpHS62Cux8Yxxc7bSr20BEpA+/XLiFWet+hUQCfPH0YDjZKNCtnQ1n6M2YmDP1/DJMpD8t3eYg1jJ+Yy5ESeZFlzxU5z71RGJ6ZYIXenewR15pJZYmnjF0OETUhpUoq7E47hQAYPaobnisnwdG9XRlQm/GUlNT6yX0lSoB8WerUKkSoJBJEBNsicd6ShEUGFCvj/3djKk1HpE5amkLQrFa48XGxiL/Tj7cQ90bTOgBQCKVwD3EHfl38rFlyxbtniBRCzCpJ4NSyKX4JGQAZFIJUn7PwfbTOYYOiYjaqJU/nMX1gnJ4ulhjweRehg6HWsFf1Z7rFsULiinHE1uVmsR+/ig5KquqERMT0+A4dxeY2jfHRnMSYMmSJZqTBvvm2OD0yaNM7IlaoLZ7wtatW7Fn9x5s3boVM2fO1GomPC8/DzInmVaPI3WSIi8/r8HrxDo5QCQmJvVkcH07OeLFh3oAACITTiO/tNLAERFRW3Pw4m18dyQTAPDRjP6wUWjV8ZVMXFRUFHxHjoD/JiX2Z1ZrltpHRkbih4tqPLG15rj/JiV8R45AVFRUg+PUtsZLedISY7rINbP7K1as0KwCGNNFjpQnLXHwcE1rPKJ7FRcXY+7cufVWhKSmpmLu3Lk8GdRCLs4uUBXo0BrPueHWeGKdHCASk87fWq5cuYJ9+/bh6tWrKCsrg5ubGwYNGoRRo0Zxvwjdt1cf9kbqmVxcvFmCZUlnEPXkIEOHRERtRKmyGgvjfgcAPDOiC3x7mn47X9IYAgAANv9JREFUVtKOvb09tu/YicmTHsXY9XWrPY8cORJBgQFIOFvWbLXn0NBQfBu9EX8/XI3hnWSaZfspF2R1WuN9cqgaCgs5QkNDW/mZkrG7u+r4t9EbG6w6fu6PM6w63gIBAQGIi4uD8oay2T31JRdKELgksMHrXZxdoLquw8mBzg2fHLibWK3xzKnFHulG65n67777DsOHD0fPnj2xcOFCJCQkYN++ffjvf/+LyZMnw93dHS+//DKuXr2qz3jJTFlZyPBxcH9IJUBCWjZ2/ZFr6JCIqI34OPU8svLK0cnJGosf72PocKiV1Sb24eHhSExK1hTD8/f3R2JSMsLDw5tNpPz8/BAXn6CZ3a9dth/Yx6Jer/u4+IRme91zxrZt4faN1hESEgJnV2fkxuRCUDdcJ1xQC8iNzYWzqzOCg4MbvE1AQABKLpRAeUPZ5ONpTg4ENnxyoFZiYiI6du6IWbNmYcfpHThRegI7Tu/ArFmz0LFzRyQlJWn1/MQah0yTVtXvBw0aBIVCgdmzZ2Pq1Knw9PSsc71SqcShQ4ewadMmbN26FV988QVCQkL0FnRrYvX71vXhD2fxn18uo729JXa+8RAcbSyavxMR0X369UoeQr86BADYED4cD/m4GTgiMmVitMZjn2jT09KuB3PnzsW6deuwb44NxnSRa04CbTtXiYA+Ck0Rx/2Z1Ri7vgzh4eFYu3at3uIxZ+baGi8xMREBAQGQu8jhNt0NLuP+Wh2Q90sebm27heq8aiQkJJhci722TPSWdqmpqc2eVa51584dZGRkYMiQIdpFa+SY1LeuiioVHv/nPly+XYrgIZ3xScgAQ4dERGaqvFKFxz/bhyu3SxE6tDNWB/P3Dd0/MVrj3T1jm/KkJT45VI0fL6mxYOEirP5oFR73kuKtkXL4b1Ki74ChTOyNgBgnYVJTUzFt6pR6XRhSLlTX2b5R+xlKTEpu9Hs5Two1r6Wt8QDjOjlQUVEBj04eKKssRmWJClI54DmvK+wH2qM4rRhZa65CXQ0o7GSwUdgj53oOl+KbCNFb2mmb0AOAq6ur2ST01PqsLGRYHdwfEgmw5dg17Dl/09AhEZGZ+nTneVy5XQp3B0v8zf8BQ4dDJkys1ngsuGdaxFo2L9b2DS7j105LW+MBwNSpUxEfHw/ZVRnSF6Uj48MMZH6RiYwPM5C+OB2yq7ImE3pAvNZ4GzduRFF+ASyq1Ng3xwb+PeXIWnMVuVtzkbXmKqZ4ybFvjg0sqtQoyi9AdHS0di8UmRSt99RnZ2dj/vz5KCoqqnddYWEh3n77beTmch80tdzQbi4I8+0GAFi45XfsOpuLnMJywwZFRGbleGY+1u6/AgBYGdQPjtbc6kP3T6zWeKGhoVBYyPH3w9V1TgbEhVrXOVnAgnvGQcyTMP7+/liwcBESzlYi5UJ1netSLlRj27lKLFi4qNFVHmLHY+5a0hqvVktPDojVGu/DDz+EWgC2P22NMV3k2BJiDf+ectxKuoUpXnLEBtcc3/60NdQC8MEHH2j9HMl0aJ3Uf/rppygqKmpw6t/R0RHFxcX49NNPRQ2O2q63/XrBxVaBm8VK/N+Goxi9ajc2/5Zp6LCIyAxUVKnwduxJqAUgaFAnPNzb3dAhkYkTqzWe2AX3SL/EPAmTkpKC1R+tQkAfBfx96jan8veRY3pvBVZ/tAopKSmtEg9ppyUnB8Rqjefo6AipFPj4UKXmfd8SYo24UGvEBltr3vfVByshldbcvjkVFRWIjo7GjBkzMOHhCZgxYwaio6NRUVGhVbzU+rRO6rdv345Zs2Y1ev2sWbOQnJwsSlBEheVVyC/7q1+9WgDeiTvFGXsiarF//pSOS7dK4WZviaVTueyeWq62gn7fAUMxdn2ZJulevny5Jkkfu75Mq33wYszY1mIV/aa19PUR6ySMWNs3eFLItLg4u0BVoENrPOeGW+N5eXlB0cEKyRerEbKlvMH3PTi2HCmXqqHoYAUvL68mH4tV9E2T1kn9lStX0KVLl0av79y5MzIyMsSIiQhXbpfi3hKOKgE4m11/+wcRkbZ+v1aA//xyGQCwIqAvnGwUBo6IzIUYrfEAcWZsgb/2V69btw7Tpk7R3D4lJQXTpk7BunXr2vS+arFeHzFOwoi1fUOseKh1iNUaLyAgABXZFXAa54LEc9UNvu9J56vhNNYFFdkVTbbYq63Gr+qqgvcqb3R7pxs8X/ZEt3e6wXuVN1RdVQgICEBiYqLuT5j0Suuk3trausmkPSMjA9bW1mLERITu7WzRUM2QZUlncPFmSesHREQmT1mtwtuxv0OlFjB1QEf4PdjB0CGRmbG3t8fatWvrzYD6+flh7dq1zSb0Ys3YsmBa08R8fcQ4CSPW9g2x4rn7deJKD/0JCQmBs6szcmNyIagbbkYmqAXkxubC2dUZwcHBjY5jZ2+Hgj15mNZb3uD7PrWXHAU/58HO3q7RcSoqKhAWHga7gXbwnOdZb6+/ZQdLeM7zhN1AO4SFh3EpvpHROqkfMWJEk9USN27ciOHDh4sSFJGHozVWBvWDTFKT2UslgIOVHFfzyhHw+QFsP33DwBESkan5fPdFnM8thqutAsumPWjocIjqEWvGlgXTmibW6yPWSRixtm+IFQ/AlR6twcrKChvWb0BJWgmy1mTVm7FX5iiRtSYLJWkl2LB+Q6P79Pfu3QtleTmmeMvr7KG/+33fEmINf285lOXl2Lt3b4PjiFWNnwxD66R+/vz5WL9+PebPn1+nyn1ubi7eeustfPPNN5g/f75egqS26YlhXbB/0QR8/9xIHFj0MH56azxGdHdBibIaL357DKu3n4OqkTObRER3O5NdiC9+vgQAWDb9QbjYctk9GR+xZmzFLphmbjO2Yr0+Yi6bF2P7hljxcKVH6xGjNV5MTAyqqlV4e7Tirz30MeUIiilHSOxfe+wXjFagqlrV6PsuVjV+MhBBB19++aVgaWkpSKVSwcnJSXB2dhakUqlgaWkpfPHFF7oMZTIKCwsFAEJhYaGhQyFBECqrVcLypDNC14XJQteFycLM/x4W8kqUhg6LiIxYZbVKeCzqF6HrwmThhY1HBbVabeiQiBpVVFQk+I4cIQAQFBZyITk5WRAEQUhOThYUFnIBgOA7coRQVFTU5Di1tw/ooxCUkfaC8K6D5qKMtBem91bUGV/f8dSOFR4eLmzfvr3O8e3btwvh4eFajSHWOGK8PrWvjYO1TNg3x0Zzn8jISM3Y++bYCA7WMq1fo5YQK57w8HABgLBvjk2d1wNAnddr3xwbAYAQHh6u1+fVFpSXlwvR0dFCUFCQMH7CeCEoKEiIjo4WysvLm73vve/7tF4WgkwqEbp27SrIpBJhem8Lrd738RPGC47DHYW+3/Rt9uIw3EEYP2G82C8D3UOXPFSnpF4QBOHatWvCp59+Krz88svCSy+9JPzjH/8QsrKy7itQU8Ck3jhtS7su9I78Uei6MFkYveon4dS1AkOHRERG6rNdF4SuC5OFActShZtFFYYOh6hZYiW/kZGRAgAhLtS6TtIaF2otABAiIyObjUOspFWskwNinmRo6esjdjxiECOe7du31zvhoYy0F+JCrev8XPt5uPdzSq1PjPc9KChIsPOx0yqpt/OxE4KCglrr6bVZek3q2xom9cbrbE6hMG71bqHrwmTB528/CFuOmu/JJSK6P+dyigSvd1KErguThfjj1wwdDlGrEWMmWqwZW7FODoh5kkGslQy1cYlxEkYsxrKSgVpXS9/3jRs3CgAE71XeTSb03iu9BQBCdHR0szGVl5cLGzdurLMCYePGjVqtQCDd8lCJINzbOKxpjbUwkEgksLKq6X3YvXt3XYY0akVFRXB0dERhYSEcHBwMHQ7do7C8Cm9sTsPuczcBALNGdUWk/wNQyLUuF0FEZqpapUbQvw/i92uFmNinPb6eNRQSScPFf4jMSWpqKqZNnVKvYFrKhWr4+8jr9SxPTEpusGe5WOPMnTsX69atw745NhjTRa65z7ZzlQjoo9CMvT+zGmPXlyE8PBxr167V2zhiPS9zt2TJEqxYsQJxodYI7GOhOR5/tgpBMeWIjIzE8uXLDRghiamiogIdO3eEqqsKnvM8GyyWJ6gFZK3JguyqDNnXshst3gfU5Ixh4WHIv5MPOx87yJxkUBWoUHKhBM6uztiwfkOTtQJItzxU58wnICAAgYGBCAgIqHfx8/ODl5cXHnroIeTn59/3E2jIBx98AF9fX9jY2MDJyUmr+7z33nvo3bs3bG1t4ezsjIkTJ+LIkSOixkWG5Whtgf/OGoqIid4AgI2HruKprw8jt4htNojauq/3XcHv1wrhYCXHB4H9mNBTmyFWwTQ/Pz9N9fW77xfYx6Je4hsXn9Bo4itWYTpjLHBnrsRsjUemQaxq/AD73RuCzkn9zp07MWzYMOzcuROFhYUoLCzEzp07MWLECCQnJ+OXX37BnTt3RK+EX1lZiZCQELz00kta38fHxwdr1qzBqVOnsH//fnTr1g2TJk3CrVu3RI2NDEsqlSBiog/Wzh4Keys5jl3Nx5R/7cdvGXmGDo2IDOTizRL8Y9cFAMCSKQ/A3aHxLx9E5kbMvuf+/v5YsHAREs5WIuVCdZ3rUi5UY9u5SixYuEhTrb0hYp0cEGscMV8fcyRmazwyLWJU49dHv/uKigpER0djxowZmPDwBMyYMQPR0dFa3bfN0HVt/4MPPigcOHCg3vH9+/cLDzzwgCAIgrBz507B09NT16G1sn79esHR0fG+7lu7L2HXrl0634d76k3DlVslwqRP9wpdFyYLPRenCN8cuMJK10RtTFZeqfDI3/cIXRcmC7PXHeHvAGqTjK2KviCIU5hOrHGMrcCdMWH1+9ZlbDUZBKFl1fjF3pu/bds2wdnVWQAg2PnYCY7DHQU7HzsBgODs6iwkJiaK9bSNji55qM4z9ZcuXWpwTb+DgwMuX74MAPD29sbt27d1HVqvKisr8Z///AeOjo4YMGBAo7dTKpUoKiqqcyHT0a2dLeJf8cXUAR1RrRbwbuIZvBVzElduleLgpdvIKSw3dIhEpEebf8vE2I/24OLNUgDAqB6uXHZPbZIYfc/FnLEVazm3WOOI8fqYK7FXMhQXF2Pu3Ln1Ph+pqamYO3dum+5zX1xcjMmTHsW6deswbeoUzec2JSUF06ZOwbp16zB50qOt/hpZWVlh5syZ2Lp1K/bs3oOtW7di5syZTS65ryVmv3su49eezoXyxowZA3t7e2zcuBFubm4AgFu3bmHWrFkoLS3FL7/8gl27duGVV17B+fPnRQ/4m2++QUREBAoKCrS6fXJyMp588kmUlZXBw8MDCQkJGDZsWKO3f++997Bs2bJ6x1koz7QIgoC1+69g5Y/noFL/9RGXSoCVQf3wxLAuBoyOiPTh1yt3EPrV4TrHZBIJ9i+aAA9HawNFRWS6jK0wHQvctZ7aZPPg4SNQWMgRF58Af39/pKSkICgwAJVV1fAdOaLZEx9ijWOOal+b0yePIuVJS3xyqBo/XlJjwcJFWP3RKjzuJcVbI+Xw36RE3wFDTeY1mvDwBJwoPQHPlz2bvW3mF5kYbDsYe3bvqXed2IX7TJFeC+WtXbsWV65cQefOneHl5QUvLy907twZGRkZ+O9//wsAKCkpQWRkZLNjLVq0CBKJpMnLuXPndA2xjgkTJiAtLQ0HDx7E5MmTERoaips3bzZ6+8WLF2tqBRQWFiIrK6tFj0+GIZFI8H9je+CfTwysc1wtAO/EneaMPZEZKa6owsofz+Kprw/Xu04lCMi4XWaAqIhMn1gztmIVpmOBu9YjxkqGu5PWfXNsNCs6lixZolkBsm+ODU6fPGqQ2WhDi4iIwMHDR5DypCXGdJFrVr2sWLFCc+JqTBc5Up60xMHDRxAREWHokLXi4uwCVYFKq9uqC9RwcXZp8LrY2Fjk38mHe6h7gwk9AEikEriHuCP/Tj62bNly3zGbA51n6gFArVZjx44duHChpghRr1698Oijj0Iq1e0cwa1bt3Dnzp0mb9OjRw8oFArNz7rO1N/L29sb4eHhWLx4sVa3Z0s703bw0m08/XX9jgffPzcSo3q6GiAiIhKLWi1g6/FrWJ16HreKlQ3ehjP1RC0jxkyrWDOS5jqzaa7EWulhrsx15Ul0dDRmzZoF71XeTS7BV+Yokb44HdHR0Zg5c2a962fMmIEdp3eg2zvdmn3MjA8zMKnvJGzdurUloRsdXfJQeZPXNkIqlWLy5MkYP348LC0t73u/opubm2YJf2tRq9VQKhv+8kfmp3s7W0glNTP0d7OQcY8tkSk7kZmP95L+wMmsAgA1/9aXTOmDW8VKvBN3GipBgEwiwYdBfZnQE7VA7YxtREQEQkNDNUlF7YxtTEwMoqKimkyea8eYPOlRjF1f9+TAyJEjERQYgISzZc2eHBBrHGodoaGh+DZ6I/5+uBrDO8k0NRhSLsjqJK3NtSA0V7XdHIICA/DEVqUmsQ/sYwEAWndzMDYhISF4/Y3XkRuT2+Sy+dzYXDi7OiM4OLjBcfLy8yBzkmn1mFInKfLy23bXK52X36vVaixfvhydOnWCnZ0drly5AgBYsmSJXs+uZWZmIi0tDZmZmVCpVEhLS0NaWhpKSko0t+ndu7em2EJpaSneeecdHD58GFevXsWxY8cQHh6O69evIyQkRG9xknHxcLTGyqB+kN1z4ilicxpuFLINBpGpuVlUgTdj0hD4xUGczCqAnaUcix/rjdSIcXi4tzueGNYF+xdNwPfPjcT+RRNYP4NIBPb29li7dm29pMLPzw9r167VKnkWqzAdC9yZDrFaEJozMVpGGhux+t2LtYz/bubcGk/n5ffvv/8+NmzYgPfffx/PPfccTp8+jR49emDz5s2IiorCoUOH9BJoWFgYNmzYUO/4nj17MH78eAA1+6jXr1+PsLCanodPP/00jhw5gtu3b8PV1RXDhg1DZGRkk4Xy7sXl9+Yhp7AcGbfLYGclw6v/O4GMO2Xo6WaLmBdGwdWu6eqcRGR4ymoV1u6/gs93X0RpZc0f+eAhnbFgci+0tzevwjhEROZkyZIlWLFiBeJCrTWz0AAQf7YKQTHliIyMxPLlyw0YoeHUbmO5ewl+rXtPephSYg/UVK4PCw9D/p182PnYQeokhbpAjZILJXB2dcaG9Rua7Hcv1jL+xuKROcmgKlBpHY8h6JKH6pzUe3l54auvvsIjjzwCe3t7nDx5Ej169MC5c+fw/+3deViU5d4H8O8zM2wyMAgoAwKCoeICCOJC+paWQeprbomVccw8pYYLek4pXaZHj0l2WtC3srJOmidNLdHMk+SWW0oCYriwuGLKIijbsM887x/E5ASyyMAsfD/X5RXzzDMzP+a6G/3Oc9+/OyQkBHfv3m1V8caGod78/Ha3DOEfn8Stogr0c7PH1peHwt7aoukHElG7E0URBy7mYdXeC7heUNvwboCHA/7xVD8M8HAwbHFERNQocw6trWWua+rvVVFRgW+++QZxcXG4c/cOHDs7YuLEiXj66aeb7FSvz+73dVvjyQfI4RLuovMlQWVOJXK356I0pRRxcXF46qmnWvdL61GbhnobGxukpaWhe/fuOqH+woULGDx4sM50eHPAUG+ertwuRfgnJ5FfWoXg7p3x5czB6GT5QC0miKiNXMorwYo9F3AsMx8A0MXOCkue9MXEwG6Q3KcTLhERGYeOEFpbg40Em7Znzx5MmDCh4TCeXYncHbVhfNeuXfe9ym7KW+O16ZZ2ffv2xbFjx+od/+abbxAYGNjSpyMyiB5d5PjyxSGwt5Yh8fpdzNqchMqa5q3bIaK2kV1Ujp8v5yMjtwQr9pxHWOwxHMvMh6VUgjkjHsLhv4/A5IHuDPRERCbA3LcgLCkpwcyZMxEfH69zPD4+HjNnzmxyiz59bRlpzsaNG4e4uDhIr0uRuSQT11ZfQ9ZHWbi2+hoyozMhvS5tNNADHWdrvBZfqd+9ezemT5+O6OhorFy5EitWrEB6ejq+/PJLfP/993jiiSfaqlaD4JV685acdRfPf5aAsio1wvq54MPngiCTtvi7LiJqpW2nsxC9M7XeThWj+rhg6dg+8HK2NUxhRET0QPS9BWFJSUm9XRiA2hDdnF0Y9EkfWz3q83nMXWum8Zvy1nhtOv0eAI4dO4aVK1fi7NmzKC0tRVBQEJYtW4bQ0NAHLtpYMdSbvxOX8jFj42lU1WgwKbAb3pkSwCuBRO3oVmEZhq05jD//bRQ7dQAmBHYzTFFERNRq5hh+zfnLCnM08rGROKM6A49XPJo8N+ujLATZBuHwocPtUFnT2jzUdyQM9R3DgQu5mPWfJKg1IiKGdsfK8f0gCAz2RG3t7I1CRO9MxYXs4nr3bX1pKEIecjJAVUREpC+tDa36DtGtxbXwpqWjXKnnPGMiAKP6uuC98AAIArD51HW8HZ9u6JKIzNq1fBUityRj/IcnGgz0UkGAl3MnA1RGRET6ZGdnh88//7xeE7ywsDB8/vnnTQbwqKgo/HwqAXufscJwTxm2P22F0Q9JsGrVKm0TvuGeMux9xgo/n0pAVFRUo8/X2rXw4eHhsLSQ4d1TNdq+ANuftsLOcBudhoDvnKyBpYUM4eHhjT4fta0JEyagNKMUlTmVjZ5XmV2J0oxSTJw4sZ0q069mXanv3Llzs69a3rlzp9VFGRNeqe9YtiRk4fW4VADAq2G9ETnSx8AVEZmX2yWVWHcwE1t/yUKNRoQgABMDu6FXVzn+FZ8BtShCKghYPak/pg7yNHS5RERkYPrsoq+vafzcqs90dJTu980K9Zs2bdL+XFBQgFWrViEsLAwhISEAgJMnTyI+Ph5vvPEGFi5c2MryjQtDfcez4egVvPnfiwCAleP74S8hXoYtiMgMlFbWYMPRK9hw7ArKqmp3mhjRuwsWP+mLPq61n63ZReW4ll8GL+dOcFXYGLJcIiIyIvoI0fqexv/GG29g1apV2Blug4l9LLTH4y5WY9L2cixduhT//Oc/9fcm0APTx9Z4htCma+onT56MkSNHYu7cuTrHP/jgAxw4cAC7du1qccHGjKG+Y3pvfwbWHcwEALwzJQBPD3Q3cEVkDrKLynE1XwVvZ9sOE1qrajTY+ksW1h3MRIGqCgAQ4K7A4tG+ePghZwNXR0REpqK1IVqfa+F5pd70fPfdd3jhxRdwt+Au5L3kkDhIoCnUoDSjFJ2dOmPTF5uMKtADbRzq5XI5UlJS4OOjOy350qVLGDBgAEpLS1tesRFjqO+YRFHEP7+/iH+fuAqJAHw0LQhP9nc1dFlkwu7dsk0iADGT/Mx6erlGI2Jvajbe+TEd1wvKAADezrZ4Naw3RvdXshElERE1mz5CtL6m8etzOQC1r9ZsjWcIbRrqu3fvjvnz5+Nvf/ubzvF3330X69atw/Xr11tesRFjqO+4RFHE4m9/xfbE32AhFfDZ9EF4tFcXQ5dFJkAURdwurcTV2ypcK1Ah9WYx/nNK97NRIgDHXhuJbp3NrxnciUv5eOuHNKTeLAIAOMutEDWqJ6YO8oCFlP1ZiYio+fQZovXx5QC731N7aUkOlbX0yVesWIG//vWv+OmnnzBkyBAAQEJCAvbt24cNGzY8WMVERkgQBMRM8oeqUo29qdmYtTkRsVMHwN7GokNNn6aGp82Looi7ZdW4mq/CtXwVruarcLWg9udr+Sqofl83fj8aERi99jjG+rsitK8LQh5ygrWFtD1+Hb2re3+qazT4/MQ1HM24DQCwtZRi1qMPYeZwb9hatfivGyIiImzfvh1V1TX429BOOgH+zyH67yEy7E4rw/bt2+8b6seOHYvXFi/BqlWrsDdDqjONf29GDXanVWHp0qWNTpmPjY1F2oXzGPt1IvY+A+3a/KVLl+LtNW9h6reV2rX5Dw8dgtjYWH2/JUT1PNA+9QkJCVi3bh0uXqxtJtanTx/Mnz9fG/LNCa/UU1WNBrM2J+Jw+m3tsY4wfZpq3TttXgAQ4KGAKAJX81Uorqi57+MkAtCtsw28nGzhYmeFb5NvorEPW1tLKUb07orQfi4Y0bsrFDYWjZxtPO59f+pYSAVMG9Id8x7zgZPc6v4PJiIiaoI+G9zpay28vrroEzWmTaffdzQM9QTU7qk94p2fdI5JBQHHl4zkFXszlpFTgrDYo42GcTeFNbycbeHlbAtvJ1t4//6zh6MNrGR/XHnfdjoLr+88p92ybeX4fvBw7IT9F3Lx44Uc5Bb/sX+qTCJgaA8nhPZzwag+LnBzML4xptaI2HXmJv6246zOcQHAjtkhCPZyNExhRERkdvQRovW9Fr6kpARRUVEIDw/XOS8+Ph7bt29HbGwsAz21it5DvUqlgq2tbbMLaOn5xoyhngDg58v5eG5DQr3jW18aghB28DY7FdVqbPr5GtYeyEBZtabe/QtH9URYfyW6O9rCxrL5U+bvt2WbRiMi9WYRfryQgx/P5yIzT7fhqF83BUL7uiC0nxK9XOTIKa4wWBf9O6oqbE+8ga8SruPGnfIGz9n60lCEPOTUrnUREZF5a22I5lp4MjV6D/Wurq5YsGABpk+fDlfXhjuAi6KIAwcO4L333sMjjzyC6OjoB6veyDDUE1Abxoa9dUhnijEAPNLTGR9MC4K9tWlMlabGqTUivk3+De/vz0B2UUWD57THDI2r+Srs/z3gJ2Xdxb2f0o62lrirqoKI9lsGIooiUm4UYvPJ6/g+NRtVNbVfdNhZy1BaUaMzk4EzWIiIyBjpe596oram91Cfnp6O119/HXv37kVAQACCg4Ph5uYGa2tr3L17FxcuXMDJkychk8kQHR2NWbNmQSo1zYZPf8ZQT3XunT4tCIAEAtSiiO5OnbB+2kD0deP4MFWiKOJQWh7W7EtDRm7tVXI3hTUWhfZGtVqDpXF/TJtfPal/u/ZSuF1SiUNpufjxfC6OZt5Gtbr+R/bM4V54oq8SAzwc9Npsr7xKje/O3sTmU9dx7max9rhfNwUiQrpjnL8bvjt7U2dZQXu/P0RERM3FtfBkStpsTX1WVhZ27NiBY8eO4fr16ygvL4ezszMCAwMRFhaG0aNHm02Yr8NQT/e6d/r07ZJKzPlPMm4WlsNKJsE/J/RHeLCHoUukFkq6fhdrfkjDL9fuAAAUNhaYO9IHESHdtQH5ftPm29uhtFy8uDHxvvdbyiQI9HDA0B5OGNrDCYGeDxbyr9wuxVcJWdiReEPbDNBSJsE4fzdEhHRHgLtCZ595Y3l/iIiImsK18GQq2ChPjxjqqTGFZVVYuC1F2xk/PNgdK8f3N9mtyTqSS3ml+Fd8GuLP5wIArGQSzBjmjTkjHjLazvMNLQMRBOBxXxec/a0Qt0sqdc63lEkwQBvyHRHk2VlnbN67VV8XuRUOpeVh86nrOJaZrz3Hw9EGzw/pjvBgD3S2tWzz35GIiIiIGOr1iqGemqLRiPjop0t4b38GNCLQ19Ue658PQncn82gWaW5yiysQeyAT2xNvQK0RIRGAKQM9EPVET5O4yvznLvp1091FUcSVfBUSrtzBqSsFOHWlAHl/DvlSCQZ4OmCotyPKq9X4/PhV7VZ99jYyFJXXXpUXBGBk766ICOmOR3t2gUQiNFAJEREREbUVhno9Yqin5jpxKR/zt55BgaoKdtYyvDMlAGH9lIYuq0O790q0rZUMnxy5jM+PX0XF7x3tn+jrgtfCeqOni2lNs2vOdHdRFHE1X4WEq3+E/Hu3zWuIwlqGZ4d0x7QhnvBw7NQWpRMRERFRM5hlqH/zzTexd+9epKSkwNLSEoWFhS16/OzZs/HJJ5/g/fffR1RUVLMfx1BPLZFTVIG5W5KReP0uAGDWIz3walhvyKQSA1fW8Ww7nYXonanaK9E2llKUVakBAAO7d8aS0b4Y1IH2UhdFEdcKypBwpQB7zt7CicsF9c7Z9OIgPNqrqwGqIyIiIqJ7tSSHmkzSqKqqwpQpUzBnzpwWPzYuLg6nTp2Cm5tbG1RG9AelwhpbXx6Kvw73BgB8cvQKntuQgLzihrdHo7aRXVSuDfQAIAIoq1Kju6MNPo0YiG9mh3SoQA8AgiDA29kWzwz2xDvhAfjzjHqpIKCXic1YICIiIqIWhPqVK1eirKysLWtp1IoVK7Bw4UL4+fm16HE3b97EvHnz8NVXX8HCwjibX5F5sZBKsPR/+2L9tCDIrWT45dodjFl3HCcbuDJKbSMzt1SnmVydNyf6IbSfUqdze0fkqrBBzCQ/SH9/H+rW5ptCTwEiIiIi0iVr7okrVqzA7Nmz0amT6ayz1Gg0iIiIwKuvvop+/fo16zGVlZWorPxj3WlxcXEjZxPd32g/V/RW2uGVr5KRllOCaZ+dwqthvpj1SA82HmtDtwrL8dYPafWOSwUBD3WVG6Ai4zR1kCce6dWFW9ERERERmbhmX6k3kaX3OtasWQOZTIb58+c3+zExMTFQKBTaPx4e3HecHlyPLnLEvTIMk4PcoRGBNfvS8PLmJGTklODny/nILio3dIlm5WjGbYxddwwXsothLZNop5jzSnTDXBU2CHnIie8LERERkQlr9pV6AHqfsrpkyRKsWbOm0XMuXrwIX1/fFj93UlIS1q5di+Tk5BbVHR0djUWLFmlvFxcXM9hTq9hYSvHOFH8Ee3XG8u/O48DFXBy4WLs3ukQAYib5YeogTwNXado0GhHrDmVi7cFMiCLQv5s91k8bCJlU4JVoIiIiIjJrze5+L5FIoFAomgzId+7cafaL3759GwUFja8z7tGjBywtLbW3N27ciKioqCa738fGxmLRokWQSP6YjKBWqyGRSODh4YFr1641q0Z2vyd9+ik9Dy98cVrnmFQQcHzJSIbOB3RHVYWobSk4mnEbAPDsYE8sH9cX1hZSA1dGRERERPRgWpJDW3SlfsWKFVAoFK0q7l5dunRBly5d9PZ894qIiMCoUaN0joWFhSEiIgIzZsxok9ckaoqlrP6KF7UoIjO3hKH+AZzJuovIr5Jxq6gC1hYSvDnBD5MHuhu6LCIiIiKidtOiUP/MM8+ga1fD7GGclZWFO3fuICsrC2q1GikpKQAAHx8fyOW1za98fX0RExODiRMnwsnJCU5OTjrPYWFhAaVSid69e7d3+UQAAG9nW0gE1OvMvmZfOnq52EOpsDZMYSZGFEVs+vka3vzvRVSrRXg722L980HwVXI2DRERERF1LM1ulGfoLaCWLVuGwMBALF++HKWlpQgMDERgYCASExO156Snp6OoqMiAVRI17s9biUkEwFomwflbxfjf/zuGU1e47V1TVJU1mP91Cv6x5wKq1SLG+Cnx3dxhDPRERERE1CG1aE19Tk6Owa7UGwrX1FNbyC4q1zZwq6rRYNbmJKTllEAqEfD6mD54cZiXwb9IM0aZuSWY/Z8kXL6tgkwiIJrvFRERERGZoZbk0GaH+o6KoZ7aQ3mVGkt2/ordKbcAAOMHuCFmkh86WbZohYxZ251yE0u+TUV5tRou9lb48LkgBHs5GrosIiIiIiK9a0kObfb0eyJqOzaWUsROHYDl4/pCJhGwO+UWJn30M64XqAxdmsFV1qjxxq5zWPB1Csqr1Rjm44S98/+HgZ6IiIiICLxS3yReqaf2lnClAJFbziC/tBL21jKsfSYQI3071rKX7KJyXM1XwVomwYo9F3D2t9peGfMe80HUqF6QSjjdnoiIiIjMF6ff6xFDPRlCTlEF5nyVhDNZhRAEIOrxXpj3mA8kHSDMbjudheidqTo7BChsLBA7dUCH+3KDiIiIiDomTr8nMnFKhTW+fnkonh/qCVEE3j+QgZe+TERRebWhS2tT2UXl9QI9AHzxQjADPRERERFRAxjqiYyUlUyKVRP88PbT/rCUSXAwLQ/jPziO9JwSQ5fWZnaduVkv0ANAZQ0nFBERERERNYShnsjIhQd74NvZD6Obgw2uFZRhwocnsOfsLUOXpVd5xRWYuyUZa/al17tPKgjwcu5kgKqIiIiIiIwfQz2RCfBzV2DPvOEY5uOE8mo15m09gzf3XsCNOyr8fDkf2UXlhi7xgWg0Ijafuo7H3zuC73/NhkQAhvs4o651gFQQsHpSf7gqbAxbKBERERGRkWKjvCawUR4Zkxq1Bu/8mIGPj1zWOS4RgJhJfpg6yNNAlbXcxexivB6XijNZhQAAf3cFVk/0Q/9uCmQXleNafhm8nDsx0BMRERFRh9OSHCprp5qISA9kUgmWjPaFp6MNXo87pz2uEYHonan4n57OcHMw7qnqZVU1WHsgE58dvwq1RoTcSoa/h/ZCRIiXdqs6V4UNwzwRERERUTMw1BOZIC9n23rHNCLw1AcnMCnIHWP9XOHvroAgGNcWeAcv5mLZ7vO4WVi7XGB0fyWWj+sHpcLawJUREREREZkmhnoiE+TtbAuJgHqd4vNLq/Dp0Sv49OgVuHe2wRg/V4zxc0WAgQN+TlEFVuw5jx/O5QAAujnYYOX4fni8j4vBaiIiIiIiMgdcU98ErqknY7XtdBZe33kOalGEVBDwj6f6wVluib2p2TiUloeyKrX23G4ONhjjp8QYP1cM8HBot4Cv1ojYfPIa3vkxA6WVNZBKBPx1uDcWjOqJTpb8TpGIiIiIqCEtyaEM9U1gqCdjdr+GcuVVahzJyMPe1BwcvJhbL+CP7q/EGH9XBP4e8LOLynE1XwVvZ9tWrWW/93kKSqvwelwqfv2tCAAwwMMBqyf6oa8b/z8iIiIiImoMQ70eMdSTqauoVuOn9NvYm5pdL+C7KazRo4scJy7nQxRb10V/2+ksRO9MhUYE6uYBiADsrGVY/KQvnhvsCYnEuNb4ExEREREZI4Z6PWKoJ3NSF/D/+3vAV90T8O/l5mANawspLCQSWMgEyCQSWEgFWEglkEklsJAIkP1+20IqQVWNGntTc+o9z6g+Llg9qT+62rERHhERERFRc3FLOyJqkLWFFE/2V+LJ/kpUVKvx6dEreG9/Rr3zbhVW6OX1Zg73ZqAnIiIiImpDDPVEHZS1hRRTgt0ReyBDp4u+RAA+fn4g7G0sUKMWUa3R1P5XrUG1+p6fNSJqfr9doKrEJ0eu4N5pP1JBgJdzp3b/vYiIiIiIOhKGeqIOzFVhg5hJfjpd9FdP6o/QfsoWP5e3s22952lN0z0iIiIiImoa19Q3gWvqqSO4Xxd9Qz0PEREREVFHxjX1RNQirgobvYRwfT0PERERERE1j8TQBRARERERERHRg2GoJyIiIiIiIjJRDPVEREREREREJopr6ptQ10ewuLjYwJUQERERERFRR1CXP5vT156hvgklJSUAAA8PDwNXQkRERERERB1JSUkJFApFo+dwS7smaDQa3Lp1C3Z2dhAEwdDl3FdxcTE8PDxw48YNbr1HJo/jmcwJxzOZE45nMiccz2TMRFFESUkJ3NzcIJE0vmqeV+qbIJFI4O7ubugyms3e3p4fSmQ2OJ7JnHA8kznheCZzwvFMxqqpK/R12CiPiIiIiIiIyEQx1BMRERERERGZKIZ6M2FlZYXly5fDysrK0KUQtRrHM5kTjmcyJxzPZE44nslcsFEeERERERERkYnilXoiIiIiIiIiE8VQT0RERERERGSiGOqJiIiIiIiITBRDPREREREREZGJYqg3Ex9++CG8vLxgbW2NIUOG4JdffjF0SURNOnr0KMaNGwc3NzcIgoBdu3bp3C+KIpYtWwZXV1fY2Nhg1KhRyMzMNEyxRI2IiYnBoEGDYGdnh65du2LChAlIT0/XOaeiogKRkZFwcnKCXC7H5MmTkZuba6CKie5v/fr18Pf3h729Pezt7RESEoIffvhBez/HMpmyt956C4IgICoqSnuMY5pMHUO9Gdi2bRsWLVqE5cuXIzk5GQEBAQgLC0NeXp6hSyNqlEqlQkBAAD788MMG73/77bexbt06fPzxx0hISICtrS3CwsJQUVHRzpUSNe7IkSOIjIzEqVOnsH//flRXVyM0NBQqlUp7zsKFC7Fnzx7s2LEDR44cwa1btzBp0iQDVk3UMHd3d7z11ltISkpCYmIiHnvsMYwfPx7nz58HwLFMpuv06dP45JNP4O/vr3OcY5pMnkgmb/DgwWJkZKT2tlqtFt3c3MSYmBgDVkXUMgDEuLg47W2NRiMqlUrxX//6l/ZYYWGhaGVlJW7dutUAFRI1X15enghAPHLkiCiKtWPXwsJC3LFjh/acixcvigDEkydPGqpMombr3Lmz+Nlnn3Esk8kqKSkRe/bsKe7fv1989NFHxQULFoiiyM9nMg+8Um/iqqqqkJSUhFGjRmmPSSQSjBo1CidPnjRgZUStc/XqVeTk5OiMbYVCgSFDhnBsk9ErKioCADg6OgIAkpKSUF1drTOefX194enpyfFMRk2tVuPrr7+GSqVCSEgIxzKZrMjISIwdO1Zn7AL8fCbzIDN0AdQ6+fn5UKvVcHFx0Tnu4uKCtLQ0A1VF1Ho5OTkA0ODYrruPyBhpNBpERUVh2LBh6N+/P4Da8WxpaQkHBwedczmeyVilpqYiJCQEFRUVkMvliIuLQ9++fZGSksKxTCbn66+/RnJyMk6fPl3vPn4+kzlgqCciItKjyMhInDt3DsePHzd0KUQPrHfv3khJSUFRURG++eYbTJ8+HUeOHDF0WUQtduPGDSxYsAD79++HtbW1ocshahOcfm/inJ2dIZVK63XozM3NhVKpNFBVRK1XN345tsmUzJ07F99//z0OHz4Md3d37XGlUomqqioUFhbqnM/xTMbK0tISPj4+GDhwIGJiYhAQEIC1a9dyLJPJSUpKQl5eHoKCgiCTySCTyXDkyBGsW7cOMpkMLi4uHNNk8hjqTZylpSUGDhyIgwcPao9pNBocPHgQISEhBqyMqHW8vb2hVCp1xnZxcTESEhI4tsnoiKKIuXPnIi4uDocOHYK3t7fO/QMHDoSFhYXOeE5PT0dWVhbHM5kEjUaDyspKjmUyOY8//jhSU1ORkpKi/RMcHIxp06Zpf+aYJlPH6fdmYNGiRZg+fTqCg4MxePBgxMbGQqVSYcaMGYYujahRpaWluHTpkvb21atXkZKSAkdHR3h6eiIqKgqrVq1Cz5494e3tjTfeeANubm6YMGGC4YomakBkZCS2bNmC3bt3w87OTrsOU6FQwMbGBgqFAjNnzsSiRYvg6OgIe3t7zJs3DyEhIRg6dKiBqyfSFR0djdGjR8PT0xMlJSXYsmULfvrpJ8THx3Msk8mxs7PT9jepY2trCycnJ+1xjmkydQz1ZmDq1Km4ffs2li1bhpycHAwYMAD79u2r12CMyNgkJiZi5MiR2tuLFi0CAEyfPh0bN27Ea6+9BpVKhZdffhmFhYUYPnw49u3bxzVxZHTWr18PABgxYoTO8S+++AIvvPACAOD999+HRCLB5MmTUVlZibCwMHz00UftXClR0/Ly8vCXv/wF2dnZUCgU8Pf3R3x8PJ544gkAHMtkfjimydQJoiiKhi6CiIiIiIiIiFqOa+qJiIiIiIiITBRDPREREREREZGJYqgnIiIiIiIiMlEM9UREREREREQmiqGeiIiIiIiIyEQx1BMRERERERGZKIZ6IiIiIiIiIhPFUE9ERERaL7zwAiZMmNDur7tx40YIggBBEBAVFaU97uXlhdjY2EYfW/c4BweHNq2RiIjIGMkMXQARERG1D0EQGr1/+fLlWLt2LURRbKeKdNnb2yM9PR22trYtelx2dja2bduG5cuXt1FlRERExouhnoiIqIPIzs7W/rxt2zYsW7YM6enp2mNyuRxyudwQpQGo/dJBqVS2+HFKpRIKhaINKiIiIjJ+nH5PRETUQSiVSu0fhUKhDdF1f+Ryeb3p9yNGjMC8efMQFRWFzp07w8XFBRs2bIBKpcKMGTNgZ2cHHx8f/PDDDzqvde7cOYwePRpyuRwuLi6IiIhAfn7+A9VdVlaGF198EXZ2dvD09MSnn37amreBiIjIrDDUExERUaM2bdoEZ2dn/PLLL5g3bx7mzJmDKVOm4OGHH0ZycjJCQ0MRERGBsrIyAEBhYSEee+wxBAYGIjExEfv27UNubi7Cw8Mf6PXfffddBAcH48yZM3jllVcwZ84cnRkGREREHRlDPRERETUqICAAS5cuRc+ePREdHQ1ra2s4OzvjpZdeQs+ePbFs2TIUFBTg119/BQB88MEHCAwMxOrVq+Hr64vAwED8+9//xuHDh5GRkdHi1x8zZgxeeeUV+Pj4YPHixXB2dsbhw4f1/WsSERGZJK6pJyIiokb5+/trf5ZKpXBycoKfn5/2mIuLCwAgLy8PAHD27FkcPny4wfX5ly9fRq9evR749euWDNS9FhERUUfHUE9ERESNsrCw0LktCILOsbqu+hqNBgBQWlqKcePGYc2aNfWey9XVVS+vX/daREREHR1DPREREelVUFAQvv32W3h5eUEm4z81iIiI2hLX1BMREZFeRUZG4s6dO3j22Wdx+vRpXL58GfHx8ZgxYwbUarWhyyMiIjIrDPVERESkV25ubjhx4gTUajVCQ0Ph5+eHqKgoODg4QCLhPz2IiIj0SRBFUTR0EURERNSxbdy4EVFRUSgsLDTI44mIiEwVvy4nIiIio1BUVAS5XI7Fixe36HFyuRyzZ89uo6qIiIiMG6/UExERkcGVlJQgNzcXAODg4ABnZ+dmP/bSpUsAarfb8/b2bpP6iIiIjBVDPREREREREZGJ4vR7IiIiIiIiIhPFUE9ERERERERkohjqiYiIiIiIiEwUQz0RERERERGRiWKoJyIiIiIiIjJRDPVEREREREREJoqhnoiIiIiIiMhEMdQTERERERERmSiGeiIiIiIiIiIT9f+A+9PXNcM1hAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1200x800 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "multi_dense_model = tf.keras.Sequential([\n",
    "    # Take the last time step.\n",
    "    # Shape [batch, time, features] => [batch, 1, features]\n",
    "    tf.keras.layers.Lambda(lambda x: x[:, -1:, :]),\n",
    "    # Shape => [batch, 1, dense_units]\n",
    "    tf.keras.layers.Dense(512, activation='relu'),\n",
    "    # Shape => [batch, out_steps*features]\n",
    "    tf.keras.layers.Dense(OUT_STEPS*num_features,\n",
    "                          kernel_initializer=tf.initializers.zeros()),\n",
    "    # Shape => [batch, out_steps, features]\n",
    "    tf.keras.layers.Reshape([OUT_STEPS, num_features])\n",
    "])\n",
    "\n",
    "history = compile_and_fit(multi_dense_model, multi_window)\n",
    "\n",
    "IPython.display.clear_output()\n",
    "multi_val_performance['Dense'] = multi_dense_model.evaluate(multi_window.val)\n",
    "multi_performance['Dense'] = multi_dense_model.evaluate(multi_window.test, verbose=0)\n",
    "multi_window.plot(multi_dense_model)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "icsBAjCzMaMl"
   },
   "source": [
    "#### CNN"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "34lCZrWYNBwd"
   },
   "source": [
    "컨볼루션 모델은 고정 너비 기록을 기반으로 예측을 수행하므로 시간에 따라 상황이 어떻게 변하는지 볼 수 있어 밀집 모델보다 성능을 높일 수 있습니다.\n",
    "\n",
    "![컨볼루션 모델은 시간이 지남에 따라 상황이 어떻게 변하는지 확인합니다](images/multistep_conv.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:06:21.551317Z",
     "iopub.status.busy": "2022-12-14T23:06:21.550613Z",
     "iopub.status.idle": "2022-12-14T23:07:28.642696Z",
     "shell.execute_reply": "2022-12-14T23:07:28.641925Z"
    },
    "id": "0xJoIP6PMWMI"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/437 [..............................] - ETA: 29s - loss: 0.2029 - mean_absolute_error: 0.2695"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 21/437 [>.............................] - ETA: 1s - loss: 0.2137 - mean_absolute_error: 0.2792 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 42/437 [=>............................] - ETA: 0s - loss: 0.2136 - mean_absolute_error: 0.2806"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 63/437 [===>..........................] - ETA: 0s - loss: 0.2128 - mean_absolute_error: 0.2796"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 84/437 [====>.........................] - ETA: 0s - loss: 0.2132 - mean_absolute_error: 0.2802"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "105/437 [======>.......................] - ETA: 0s - loss: 0.2130 - mean_absolute_error: 0.2796"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "127/437 [=======>......................] - ETA: 0s - loss: 0.2138 - mean_absolute_error: 0.2796"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "150/437 [=========>....................] - ETA: 0s - loss: 0.2153 - mean_absolute_error: 0.2806"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "171/437 [==========>...................] - ETA: 0s - loss: 0.2162 - mean_absolute_error: 0.2813"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "192/437 [============>.................] - ETA: 0s - loss: 0.2155 - mean_absolute_error: 0.2809"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "213/437 [=============>................] - ETA: 0s - loss: 0.2147 - mean_absolute_error: 0.2805"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "234/437 [===============>..............] - ETA: 0s - loss: 0.2146 - mean_absolute_error: 0.2803"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "255/437 [================>.............] - ETA: 0s - loss: 0.2151 - mean_absolute_error: 0.2806"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "276/437 [=================>............] - ETA: 0s - loss: 0.2149 - mean_absolute_error: 0.2804"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "297/437 [===================>..........] - ETA: 0s - loss: 0.2145 - mean_absolute_error: 0.2801"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "318/437 [====================>.........] - ETA: 0s - loss: 0.2139 - mean_absolute_error: 0.2797"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "339/437 [======================>.......] - ETA: 0s - loss: 0.2142 - mean_absolute_error: 0.2799"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "360/437 [=======================>......] - ETA: 0s - loss: 0.2138 - mean_absolute_error: 0.2798"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "382/437 [=========================>....] - ETA: 0s - loss: 0.2137 - mean_absolute_error: 0.2797"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "403/437 [==========================>...] - ETA: 0s - loss: 0.2135 - mean_absolute_error: 0.2795"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "425/437 [============================>.] - ETA: 0s - loss: 0.2132 - mean_absolute_error: 0.2793"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "437/437 [==============================] - 1s 2ms/step - loss: 0.2134 - mean_absolute_error: 0.2795\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x800 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "CONV_WIDTH = 3\n",
    "multi_conv_model = tf.keras.Sequential([\n",
    "    # Shape [batch, time, features] => [batch, CONV_WIDTH, features]\n",
    "    tf.keras.layers.Lambda(lambda x: x[:, -CONV_WIDTH:, :]),\n",
    "    # Shape => [batch, 1, conv_units]\n",
    "    tf.keras.layers.Conv1D(256, activation='relu', kernel_size=(CONV_WIDTH)),\n",
    "    # Shape => [batch, 1,  out_steps*features]\n",
    "    tf.keras.layers.Dense(OUT_STEPS*num_features,\n",
    "                          kernel_initializer=tf.initializers.zeros()),\n",
    "    # Shape => [batch, out_steps, features]\n",
    "    tf.keras.layers.Reshape([OUT_STEPS, num_features])\n",
    "])\n",
    "\n",
    "history = compile_and_fit(multi_conv_model, multi_window)\n",
    "\n",
    "IPython.display.clear_output()\n",
    "\n",
    "multi_val_performance['Conv'] = multi_conv_model.evaluate(multi_window.val)\n",
    "multi_performance['Conv'] = multi_conv_model.evaluate(multi_window.test, verbose=0)\n",
    "multi_window.plot(multi_conv_model)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "weBjeZAFJOP4"
   },
   "source": [
    "#### RNN"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "8022xOKxOO92"
   },
   "source": [
    "반복 모델은 모델이 수행하는 예측과 관련이 있는 경우 긴 입력 기록을 사용하는 방법을 학습할 수 있습니다. 여기서 모델은 다음 24시간에 대한 단일 예측을 수행하기 전에 24시간 동안 내부 상태를 축적합니다.\n",
    "\n",
    "이 싱글샷 형식에서 LSTM은 마지막 타임스텝에서만 출력을 생성하면 되므로 `tf.keras.layers.LSTM`에서 `return_sequences=False`를 설정합니다.\n",
    "\n",
    "![lstm은 입력 창에 대한 상태를 누적하고 다음 24시간 동안 단일 예측을 수행합니다](https://github.com/tensorflow/docs-l10n/blob/master/site/ko/tutorials/structured_data/images/multistep_lstm.png?raw=true)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:07:28.647512Z",
     "iopub.status.busy": "2022-12-14T23:07:28.646793Z",
     "iopub.status.idle": "2022-12-14T23:09:20.421840Z",
     "shell.execute_reply": "2022-12-14T23:09:20.421037Z"
    },
    "id": "Bf1ks6RTzF64"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/437 [..............................] - ETA: 29s - loss: 0.2182 - mean_absolute_error: 0.2789"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 18/437 [>.............................] - ETA: 1s - loss: 0.2232 - mean_absolute_error: 0.2881 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 36/437 [=>............................] - ETA: 1s - loss: 0.2270 - mean_absolute_error: 0.2891"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 55/437 [==>...........................] - ETA: 1s - loss: 0.2201 - mean_absolute_error: 0.2860"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 74/437 [====>.........................] - ETA: 1s - loss: 0.2170 - mean_absolute_error: 0.2846"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 93/437 [=====>........................] - ETA: 0s - loss: 0.2150 - mean_absolute_error: 0.2837"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "112/437 [======>.......................] - ETA: 0s - loss: 0.2134 - mean_absolute_error: 0.2827"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "131/437 [=======>......................] - ETA: 0s - loss: 0.2135 - mean_absolute_error: 0.2829"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "149/437 [=========>....................] - ETA: 0s - loss: 0.2140 - mean_absolute_error: 0.2832"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "167/437 [==========>...................] - ETA: 0s - loss: 0.2136 - mean_absolute_error: 0.2829"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "185/437 [===========>..................] - ETA: 0s - loss: 0.2134 - mean_absolute_error: 0.2827"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "203/437 [============>.................] - ETA: 0s - loss: 0.2135 - mean_absolute_error: 0.2831"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "222/437 [==============>...............] - ETA: 0s - loss: 0.2128 - mean_absolute_error: 0.2827"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "240/437 [===============>..............] - ETA: 0s - loss: 0.2123 - mean_absolute_error: 0.2824"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "258/437 [================>.............] - ETA: 0s - loss: 0.2128 - mean_absolute_error: 0.2827"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "277/437 [==================>...........] - ETA: 0s - loss: 0.2133 - mean_absolute_error: 0.2829"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "295/437 [===================>..........] - ETA: 0s - loss: 0.2132 - mean_absolute_error: 0.2828"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "313/437 [====================>.........] - ETA: 0s - loss: 0.2130 - mean_absolute_error: 0.2827"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "331/437 [=====================>........] - ETA: 0s - loss: 0.2129 - mean_absolute_error: 0.2827"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "349/437 [======================>.......] - ETA: 0s - loss: 0.2128 - mean_absolute_error: 0.2827"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "367/437 [========================>.....] - ETA: 0s - loss: 0.2133 - mean_absolute_error: 0.2829"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "385/437 [=========================>....] - ETA: 0s - loss: 0.2132 - mean_absolute_error: 0.2829"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "403/437 [==========================>...] - ETA: 0s - loss: 0.2136 - mean_absolute_error: 0.2831"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "421/437 [===========================>..] - ETA: 0s - loss: 0.2140 - mean_absolute_error: 0.2834"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "437/437 [==============================] - 1s 3ms/step - loss: 0.2137 - mean_absolute_error: 0.2833\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1200x800 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "multi_lstm_model = tf.keras.Sequential([\n",
    "    # Shape [batch, time, features] => [batch, lstm_units].\n",
    "    # Adding more `lstm_units` just overfits more quickly.\n",
    "    tf.keras.layers.LSTM(32, return_sequences=False),\n",
    "    # Shape => [batch, out_steps*features].\n",
    "    tf.keras.layers.Dense(OUT_STEPS*num_features,\n",
    "                          kernel_initializer=tf.initializers.zeros()),\n",
    "    # Shape => [batch, out_steps, features].\n",
    "    tf.keras.layers.Reshape([OUT_STEPS, num_features])\n",
    "])\n",
    "\n",
    "history = compile_and_fit(multi_lstm_model, multi_window)\n",
    "\n",
    "IPython.display.clear_output()\n",
    "\n",
    "multi_val_performance['LSTM'] = multi_lstm_model.evaluate(multi_window.val)\n",
    "multi_performance['LSTM'] = multi_lstm_model.evaluate(multi_window.test, verbose=0)\n",
    "multi_window.plot(multi_lstm_model)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "d5n-1cDW12Vo"
   },
   "source": [
    "### 고급: 자기 회귀 모델\n",
    "\n",
    "위의 모델은 모두 한 번에 전체 출력 시퀀스를 예측합니다.\n",
    "\n",
    "경우에 따라 모델이 이 예측을 여러 타임스텝으로 분해하는 것이 도움이 될 수 있습니다. 그러면 이전의 <a href=\"https://arxiv.org/abs/1308.0850\" class=\"external\">RNN(Recurrent Neural Networks)을 이용한 시퀀스 생성</a>에서와 같이 각 모델의 출력을 각 스텝에서 자체 피드백할 수 있어 이전 예측을 조건부로 예측을 수행할 수 있습니다.\n",
    "\n",
    "이 형태의 모델이 갖는 한 가지 분명한 장점은 다양한 길이의 출력을 생성하도록 설정할 수 있다는 것입니다.\n",
    "\n",
    "이 튜토리얼의 전반부에서 훈련한 단일 스텝 다중 출력 모델 중 하나를 가져와 자기 회귀 피드백 루프에서 실행할 수 있지만 여기서는 이를 수행하도록 명시적으로 훈련된 모델을 빌드하는 데 중점을 둘 것입니다.\n",
    "\n",
    "![모델의 출력을 입력으로 피드백](images/multistep_autoregressive.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "PKRreBbULRXY"
   },
   "source": [
    "#### RNN\n",
    "\n",
    "이 튜토리얼에서는 자기 회귀 RNN 모델만 빌드하지만 이 패턴은 단일 타임스텝을 출력하도록 설계된 모든 모델에 적용할 수 있습니다.\n",
    "\n",
    "이 모델은 앞의 단일 스텝 LSTM 모델과 기본 형태가 동일하여 `tf.keras.layers.LSTM` 레이어 다음에 `LSTM` 레이어 출력을 모델 예측으로 변환하는 `tf.keras.layers.Dense` 레이어가 이어집니다.\n",
    "\n",
    "`tf.keras.layers.LSTM`은 상태와 시퀀스 결과를 자동으로 관리하는 더 높은 수준의 `tf.keras.layers.RNN`에서 래핑된 `tf.keras.layers.LSTMCell`입니다(자세한 내용은 [Keras를 사용한 순환 신경망(RNN)](https://www.tensorflow.org/guide/keras/rnn) 가이드 참조).\n",
    "\n",
    "이 경우 모델은 각 스텝에 대한 입력을 수동으로 관리해야 하므로 더 낮은 수준의 단일 타임스텝 인터페이스에 대해 `tf.keras.layers.LSTMCell`를 직접 사용합니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:09:20.426549Z",
     "iopub.status.busy": "2022-12-14T23:09:20.426029Z",
     "iopub.status.idle": "2022-12-14T23:09:20.431083Z",
     "shell.execute_reply": "2022-12-14T23:09:20.430408Z"
    },
    "id": "s5tz3Nu0R5JG"
   },
   "outputs": [],
   "source": [
    "class FeedBack(tf.keras.Model):\n",
    "  def __init__(self, units, out_steps):\n",
    "    super().__init__()\n",
    "    self.out_steps = out_steps\n",
    "    self.units = units\n",
    "    self.lstm_cell = tf.keras.layers.LSTMCell(units)\n",
    "    # Also wrap the LSTMCell in an RNN to simplify the `warmup` method.\n",
    "    self.lstm_rnn = tf.keras.layers.RNN(self.lstm_cell, return_state=True)\n",
    "    self.dense = tf.keras.layers.Dense(num_features)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:09:20.434825Z",
     "iopub.status.busy": "2022-12-14T23:09:20.434046Z",
     "iopub.status.idle": "2022-12-14T23:09:20.445675Z",
     "shell.execute_reply": "2022-12-14T23:09:20.444963Z"
    },
    "id": "2OXVM9G1U7xR"
   },
   "outputs": [],
   "source": [
    "feedback_model = FeedBack(units=32, out_steps=OUT_STEPS)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "ph5uFSfTUNho"
   },
   "source": [
    "이 모델에 필요한 첫 번째 메서드는 입력을 기반으로 내부 상태를 초기화하는 `warmup` 메서드입니다. 일단 훈련되면 이 상태는 입력 기록의 관련 부분을 캡처합니다. 이는 앞서 알아본 단일 스탭 `LSTM` 모델과 동일합니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:09:20.449259Z",
     "iopub.status.busy": "2022-12-14T23:09:20.448757Z",
     "iopub.status.idle": "2022-12-14T23:09:20.452524Z",
     "shell.execute_reply": "2022-12-14T23:09:20.451851Z"
    },
    "id": "vM2K_LLdRjDZ"
   },
   "outputs": [],
   "source": [
    "def warmup(self, inputs):\n",
    "  # inputs.shape => (batch, time, features)\n",
    "  # x.shape => (batch, lstm_units)\n",
    "  x, *state = self.lstm_rnn(inputs)\n",
    "\n",
    "  # predictions.shape => (batch, features)\n",
    "  prediction = self.dense(x)\n",
    "  return prediction, state\n",
    "\n",
    "FeedBack.warmup = warmup"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "6JkaSYaZ9eB7"
   },
   "source": [
    "이 메서드는 단일 타임스텝 예측과 `LSTM`의 내부 상태를 반환합니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:09:20.456219Z",
     "iopub.status.busy": "2022-12-14T23:09:20.455724Z",
     "iopub.status.idle": "2022-12-14T23:09:20.546585Z",
     "shell.execute_reply": "2022-12-14T23:09:20.545749Z"
    },
    "id": "w9Fz6NTKXXwU"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "TensorShape([32, 19])"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prediction, state = feedback_model.warmup(multi_window.example[0])\n",
    "prediction.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "S_ZdvPjdX3y3"
   },
   "source": [
    "`RNN`의 상태 및 초기 예측을 사용하여 이제 이전의 각 스텝에서 수행한 예측을 입력으로 제공하여 모델을 계속 반복할 수 있습니다.\n",
    "\n",
    "출력 예측을 수집하는 가장 간단한 방법은 Python 목록을 사용하고 루프 후에 `tf.stack`을 사용하는 것입니다."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "yotTad3nZXQU"
   },
   "source": [
    "참고: 이와 같은 Python 목록 스태킹은 훈련을 위해 `Model.compile(..., run_eagerly=True)`를 사용하거나 고정 길이의 출력을 통해 즉시 실행하는 경우에만 효과가 있습니다. 동적 출력 길이의 경우 Python 목록 대신 `tf.TensorArray`를 사용하고 Python `range` 대신 `tf.range`를 사용해야 합니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:09:20.550427Z",
     "iopub.status.busy": "2022-12-14T23:09:20.549754Z",
     "iopub.status.idle": "2022-12-14T23:09:20.555373Z",
     "shell.execute_reply": "2022-12-14T23:09:20.554698Z"
    },
    "id": "g1GRDu3mZtr9"
   },
   "outputs": [],
   "source": [
    "def call(self, inputs, training=None):\n",
    "  # Use a TensorArray to capture dynamically unrolled outputs.\n",
    "  predictions = []\n",
    "  # Initialize the LSTM state.\n",
    "  prediction, state = self.warmup(inputs)\n",
    "\n",
    "  # Insert the first prediction.\n",
    "  predictions.append(prediction)\n",
    "\n",
    "  # Run the rest of the prediction steps.\n",
    "  for n in range(1, self.out_steps):\n",
    "    # Use the last prediction as input.\n",
    "    x = prediction\n",
    "    # Execute one lstm step.\n",
    "    x, state = self.lstm_cell(x, states=state,\n",
    "                              training=training)\n",
    "    # Convert the lstm output to a prediction.\n",
    "    prediction = self.dense(x)\n",
    "    # Add the prediction to the output.\n",
    "    predictions.append(prediction)\n",
    "\n",
    "  # predictions.shape => (time, batch, features)\n",
    "  predictions = tf.stack(predictions)\n",
    "  # predictions.shape => (batch, time, features)\n",
    "  predictions = tf.transpose(predictions, [1, 0, 2])\n",
    "  return predictions\n",
    "\n",
    "FeedBack.call = call"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Ubop-YWp15XW"
   },
   "source": [
    "예제 입력에서 이 모델을 테스트 실행합니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:09:20.558627Z",
     "iopub.status.busy": "2022-12-14T23:09:20.558041Z",
     "iopub.status.idle": "2022-12-14T23:09:20.665280Z",
     "shell.execute_reply": "2022-12-14T23:09:20.664436Z"
    },
    "id": "Xja83zEYaM2D"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Output shape (batch, time, features):  (32, 24, 19)\n"
     ]
    }
   ],
   "source": [
    "print('Output shape (batch, time, features): ', feedback_model(multi_window.example[0]).shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "qMs0rYB8be9M"
   },
   "source": [
    "이제 모델을 훈련합니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:09:20.669312Z",
     "iopub.status.busy": "2022-12-14T23:09:20.668684Z",
     "iopub.status.idle": "2022-12-14T23:16:58.017982Z",
     "shell.execute_reply": "2022-12-14T23:16:58.017193Z"
    },
    "id": "VBRVG2hnNyrO"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  1/437 [..............................] - ETA: 31s - loss: 0.2013 - mean_absolute_error: 0.2902"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "  7/437 [..............................] - ETA: 3s - loss: 0.2147 - mean_absolute_error: 0.2943 "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 14/437 [..............................] - ETA: 3s - loss: 0.2142 - mean_absolute_error: 0.2929"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 21/437 [>.............................] - ETA: 3s - loss: 0.2205 - mean_absolute_error: 0.2978"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 28/437 [>.............................] - ETA: 3s - loss: 0.2284 - mean_absolute_error: 0.3033"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 35/437 [=>............................] - ETA: 3s - loss: 0.2280 - mean_absolute_error: 0.3036"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 42/437 [=>............................] - ETA: 3s - loss: 0.2252 - mean_absolute_error: 0.3018"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 49/437 [==>...........................] - ETA: 3s - loss: 0.2272 - mean_absolute_error: 0.3028"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 56/437 [==>...........................] - ETA: 2s - loss: 0.2254 - mean_absolute_error: 0.3021"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 63/437 [===>..........................] - ETA: 2s - loss: 0.2227 - mean_absolute_error: 0.3009"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 70/437 [===>..........................] - ETA: 2s - loss: 0.2243 - mean_absolute_error: 0.3020"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 77/437 [====>.........................] - ETA: 2s - loss: 0.2246 - mean_absolute_error: 0.3020"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 84/437 [====>.........................] - ETA: 2s - loss: 0.2250 - mean_absolute_error: 0.3023"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 91/437 [=====>........................] - ETA: 2s - loss: 0.2266 - mean_absolute_error: 0.3033"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      " 98/437 [=====>........................] - ETA: 2s - loss: 0.2277 - mean_absolute_error: 0.3043"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "105/437 [======>.......................] - ETA: 2s - loss: 0.2280 - mean_absolute_error: 0.3045"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "112/437 [======>.......................] - ETA: 2s - loss: 0.2275 - mean_absolute_error: 0.3044"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "119/437 [=======>......................] - ETA: 2s - loss: 0.2275 - mean_absolute_error: 0.3043"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "126/437 [=======>......................] - ETA: 2s - loss: 0.2267 - mean_absolute_error: 0.3038"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "133/437 [========>.....................] - ETA: 2s - loss: 0.2267 - mean_absolute_error: 0.3041"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "140/437 [========>.....................] - ETA: 2s - loss: 0.2267 - mean_absolute_error: 0.3039"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "147/437 [=========>....................] - ETA: 2s - loss: 0.2266 - mean_absolute_error: 0.3042"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "154/437 [=========>....................] - ETA: 2s - loss: 0.2265 - mean_absolute_error: 0.3040"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "161/437 [==========>...................] - ETA: 2s - loss: 0.2255 - mean_absolute_error: 0.3034"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "168/437 [==========>...................] - ETA: 2s - loss: 0.2253 - mean_absolute_error: 0.3033"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "175/437 [===========>..................] - ETA: 1s - loss: 0.2244 - mean_absolute_error: 0.3028"
     ]
    },
    {
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     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "182/437 [===========>..................] - ETA: 1s - loss: 0.2242 - mean_absolute_error: 0.3027"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "189/437 [===========>..................] - ETA: 1s - loss: 0.2242 - mean_absolute_error: 0.3028"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "196/437 [============>.................] - ETA: 1s - loss: 0.2238 - mean_absolute_error: 0.3025"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "203/437 [============>.................] - ETA: 1s - loss: 0.2240 - mean_absolute_error: 0.3025"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "210/437 [=============>................] - ETA: 1s - loss: 0.2241 - mean_absolute_error: 0.3025"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "217/437 [=============>................] - ETA: 1s - loss: 0.2242 - mean_absolute_error: 0.3027"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "224/437 [==============>...............] - ETA: 1s - loss: 0.2240 - mean_absolute_error: 0.3025"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "231/437 [==============>...............] - ETA: 1s - loss: 0.2250 - mean_absolute_error: 0.3031"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "238/437 [===============>..............] - ETA: 1s - loss: 0.2253 - mean_absolute_error: 0.3033"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "245/437 [===============>..............] - ETA: 1s - loss: 0.2253 - mean_absolute_error: 0.3032"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "252/437 [================>.............] - ETA: 1s - loss: 0.2260 - mean_absolute_error: 0.3036"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "259/437 [================>.............] - ETA: 1s - loss: 0.2255 - mean_absolute_error: 0.3033"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "266/437 [=================>............] - ETA: 1s - loss: 0.2256 - mean_absolute_error: 0.3034"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "273/437 [=================>............] - ETA: 1s - loss: 0.2255 - mean_absolute_error: 0.3033"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "280/437 [==================>...........] - ETA: 1s - loss: 0.2258 - mean_absolute_error: 0.3035"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "287/437 [==================>...........] - ETA: 1s - loss: 0.2257 - mean_absolute_error: 0.3035"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "294/437 [===================>..........] - ETA: 1s - loss: 0.2258 - mean_absolute_error: 0.3035"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "301/437 [===================>..........] - ETA: 1s - loss: 0.2256 - mean_absolute_error: 0.3035"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "308/437 [====================>.........] - ETA: 0s - loss: 0.2252 - mean_absolute_error: 0.3032"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "315/437 [====================>.........] - ETA: 0s - loss: 0.2252 - mean_absolute_error: 0.3032"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "322/437 [=====================>........] - ETA: 0s - loss: 0.2253 - mean_absolute_error: 0.3033"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "329/437 [=====================>........] - ETA: 0s - loss: 0.2255 - mean_absolute_error: 0.3034"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
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     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "378/437 [========================>.....] - ETA: 0s - loss: 0.2257 - mean_absolute_error: 0.3033"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "385/437 [=========================>....] - ETA: 0s - loss: 0.2257 - mean_absolute_error: 0.3033"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "392/437 [=========================>....] - ETA: 0s - loss: 0.2257 - mean_absolute_error: 0.3033"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "399/437 [==========================>...] - ETA: 0s - loss: 0.2255 - mean_absolute_error: 0.3030"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "406/437 [==========================>...] - ETA: 0s - loss: 0.2254 - mean_absolute_error: 0.3029"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "413/437 [===========================>..] - ETA: 0s - loss: 0.2253 - mean_absolute_error: 0.3029"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "420/437 [===========================>..] - ETA: 0s - loss: 0.2251 - mean_absolute_error: 0.3027"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "427/437 [============================>.] - ETA: 0s - loss: 0.2250 - mean_absolute_error: 0.3026"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "435/437 [============================>.] - ETA: 0s - loss: 0.2252 - mean_absolute_error: 0.3027"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
      "437/437 [==============================] - 3s 7ms/step - loss: 0.2251 - mean_absolute_error: 0.3027\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x800 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "history = compile_and_fit(feedback_model, multi_window)\n",
    "\n",
    "IPython.display.clear_output()\n",
    "\n",
    "multi_val_performance['AR LSTM'] = feedback_model.evaluate(multi_window.val)\n",
    "multi_performance['AR LSTM'] = feedback_model.evaluate(multi_window.test, verbose=0)\n",
    "multi_window.plot(feedback_model)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "hGjcJsAQJUkI"
   },
   "source": [
    "### 성능"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "sODAwr2ndtDB"
   },
   "source": [
    "이 문제에 대해 모델 복잡성이 증가함에 따라 분명히 이득이 감소합니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:16:58.023135Z",
     "iopub.status.busy": "2022-12-14T23:16:58.022328Z",
     "iopub.status.idle": "2022-12-14T23:16:58.210562Z",
     "shell.execute_reply": "2022-12-14T23:16:58.209788Z"
    },
    "id": "WZwWBA8S6B3L"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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AAABOizALAAAAp0WYBQAAgNMizAIAAMBpEWYBAADgtAizAAAAcFqEWQAAADgtwiwAAACcFmEWAAAAToswCwAAAKdFmAUAAIDTymTrC2JjY7VlyxadOnVKMTExyps3r6pUqaISJUqkRX0AAADAPaU6zG7YsEHffPONFi9erPj4eHl5eSlLliy6dOmSYmNj5evrq+7du+vNN99U9uzZ07JmAAAAQFIqhxkEBwcrJCRExYsX12+//aZr167p77//VkREhGJiYnT06FENGDBAYWFheuqpp7Ry5cq0rhsAAABIXc9s06ZNtWDBAmXOnDnF7b6+vvL19VWnTp104MABnT171q5FAgAAAClJVZh94403Un3AsmXLqmzZsg9dEAAAAJBaNq9mcPr0aUVERFifb926Vf/61780YcIEuxYGAAAAPIjNYbZdu3ZavXq1JCkyMlKNGjXS1q1b1b9/fw0dOtTuBQIAAAD3YnOY3bdvn6pVqyZJmjt3rsqXL6+NGzdq5syZmjZtmr3rAwAAAO7J5jAbHx8vd3d3SdKqVasUHBwsSSpTpgwTvwAAAJCubA6z5cqV07hx47Ru3TqtXLlSQUFBkqQzZ84od+7cdi8QAAAAuBebw+wXX3yh8ePH67nnnlPbtm1VqVIlSdKiRYusww8AAACA9GDz7Wyfe+45Xbx4UVFRUfL29ra2d+/eXVmzZrVrcQAAAMD92Nwz26BBA127di1JkJWkXLlyKSQkxG6FAQAAAA9ic5hds2aN4uLikrXfvHlT69ats0tRAAAAQGqkepjBnj17rF8fOHBAkZGR1ucJCQlavny5ChUqZN/qAAAAgPtIdZitXLmyLBaLLBaLGjRokGx7lixZNGbMGLsWBwAAANxPqsPsiRMnZIyRr6+vtm7dqrx581q3ubm5ycfHR66urmlSJAAAAJCSVIfZYsWKSZISExPTrBgAAADAFjYvzTV9+vT7bu/YseNDFwMAAADYwuYw27t37yTP4+PjFRMTIzc3N3l6ehJmAQAAkG5sXprr8uXLSR7Xr1/X4cOHVbt2bc2aNSstagQAAABSZHOYTYmfn5+GDx+erNcWAAAASEt2CbOSlClTJp05c8ZehwMAAAAeyOYxs4sWLUry3Bijs2fP6rvvvlOtWrXsVhgAAADwIDaH2ZYtWyZ5brFYlDdvXjVo0EAjR460V10AAADAA9kcZllnFgAAAI+LRxoza4yRMcZetQAAAAA2eagwO3nyZJUvX14eHh7y8PBQ+fLlNWnSJHvXBgAAANyXzWF20KBB6t27t5o3b6558+Zp3rx5at68ud59910NGjTooYoYO3asihcvLg8PD1WvXl1bt25N1etmz54ti8WSbBwvAAAAngw2j5n9/vvvNXHiRLVt29baFhwcrIoVK6pnz54aOnSoTcebM2eOQkNDNW7cOFWvXl2jR49WYGCgDh8+LB8fn3u+7uTJk+rTp4/q1Klj67cAAACADMLmntn4+HgFBAQka/f399etW7dsLmDUqFHq1q2bOnfurLJly2rcuHHy9PTUlClT7vmahIQEtW/fXkOGDJGvr6/N5wQAAEDGYHOYffXVV/X9998na58wYYLat29v07Hi4uK0fft2NWzY8H8FubioYcOG2rRp0z1fN3ToUPn4+Khr164PPEdsbKyioqKSPAAAAJAx2DzMQLo9Aey3337Ts88+K0nasmWLwsPD1bFjR4WGhlr3GzVq1H2Pc/HiRSUkJChfvnxJ2vPly6dDhw6l+Jr169dr8uTJ2rVrV6pqHTZsmIYMGZKqfQEAAOBcbA6z+/bt0zPPPCNJOn78uCQpT548ypMnj/bt22fdz2Kx2KnE/7l27ZpeffVVTZw4UXny5EnVa/r165ckYEdFRalIkSJ2rw0AAADpz+Ywu3r1arudPE+ePHJ1ddW5c+eStJ87d0758+dPtv/x48d18uRJNW/e3Np25yYOmTJl0uHDh1WyZMkkr3F3d5e7u7vdagYAAMDjw+Yxs126dNG1a9eStUdHR6tLly42HcvNzU3+/v4KCwuztiUmJiosLEw1atRItn+ZMmW0d+9e7dq1y/oIDg5W/fr1tWvXLnpcAQAAnjA298z+8MMPGj58uLJnz56k/caNG5o+ffp9VyFISWhoqDp16qSAgABVq1ZNo0ePVnR0tDp37ixJ6tixowoVKqRhw4ZZb9Bwt5w5c0pSsnZkbMU/XJou5zk5vGm6nAcAADycVIfZqKgo6+1rr127Jg8PD+u2hIQELVu27L7rwt5LSEiILly4oEGDBikyMlKVK1fW8uXLrZPCwsPD5eLySHfdBQAAQAaV6jCbM2dOWSwWWSwWPfXUU8m2WyyWh141oEePHurRo0eK29asWXPf106bNu2hzgkAAADnl+owu3r1ahlj1KBBAy1YsEC5cuWybnNzc1OxYsVUsGDBNCkSAAAASEmqw2y9evUkSSdOnFDRokXTZOktAAAAwBY2TwA7deqUTp06dc/tdevWfaSCAAAAgNSyOcw+99xzydru7qVNSEh4pIIAAACA1LJ5mYDLly8neZw/f17Lly9X1apV9dtvv6VFjQAAAECKbO6Z9fLyStbWqFEjubm5KTQ0VNu3b7dLYQAAAMCD2G0B13z58unw4cP2OhwAAADwQDb3zO7ZsyfJc2OMzp49q+HDh6ty5cr2qgsAAAB4IJvDbOXKlWWxWGSMSdL+7LPP2nwrWwAAAOBR2BxmT5w4keS5i4uL8ubNm+T2tgAAAEB6sDnMFitWLC3qAAAAAGz2UBPA1q5dq+bNm6tUqVIqVaqUgoODtW7dOnvXBgAAANyXzWF2xowZatiwoTw9PdWrVy/16tVLWbJk0fPPP6+ffvopLWoEAAAAUmTzMIPPPvtMI0aM0Lvvvmtt69Wrl0aNGqVPPvlE7dq1s2uBwGPj4+RrLKfNea6mz3kAAMgAbO6Z/fPPP9W8efNk7cHBwckmhwEAAABpyeYwW6RIEYWFhSVrX7VqlYoUKWKXogAAAIDUsHmYwXvvvadevXpp165dqlmzpiRpw4YNmjZtmr755hu7FwgAAADci81h9q233lL+/Pk1cuRIzZ07V5L09NNPa86cOWrRooXdCwQAAADuxeYwK0mtWrVSq1at7F0LAAAAYJOHWmcWAAAAeBwQZgEAAOC0CLMAAABwWoRZAAAAOC3CLAAAAJxWqlYzCA0NTfUBR40a9dDFAAAAALZIVZjduXNnkuc7duzQrVu3VLp0aUnSkSNH5OrqKn9/f/tXCAAAANxDqsLs6tWrrV+PGjVK2bNn1w8//CBvb29J0uXLl9W5c2fVqVMnbaoEAAAAUmDzmNmRI0dq2LBh1iArSd7e3vr00081cuRIuxYHAAAA3I/NYTYqKkoXLlxI1n7hwgVdu3bNLkUBAAAAqWFzmG3VqpU6d+6shQsXKiIiQhEREVqwYIG6du2q1q1bp0WNAAAAQIpSNWb2buPGjVOfPn3Url07xcfH3z5Ipkzq2rWrvvzyS7sXCAAAANyLzWHW09NT//73v/Xll1/q+PHjkqSSJUsqa9asdi8OAAAAuB+bw+wdWbNmVcWKFe1ZCwAAAGATm8NsdHS0hg8frrCwMJ0/f16JiYlJtv/55592Kw4AAAC4H5vD7Ouvv661a9fq1VdfVYECBWSxWNKiLgAAAOCBbA6zv/76q5YuXapatWqlRT0AAABAqtm8NJe3t7dy5cqVFrUAAAAANrE5zH7yyScaNGiQYmJi0qIeAAAAINVsHmYwcuRIHT9+XPny5VPx4sWVOXPmJNt37Nhht+IAAACA+7E5zLZs2TINygAAAABsZ3OYHTx4cFrUAQAAANjM5jGzAAAAwOPC5p7ZhIQEff3115o7d67Cw8MVFxeXZPulS5fsVhwAAABwPzb3zA4ZMkSjRo1SSEiIrl69qtDQULVu3VouLi76+OOP06BEAAAAIGU2h9mZM2dq4sSJeu+995QpUya1bdtWkyZN0qBBg7R58+a0qBEAAABIkc1hNjIyUhUqVJAkZcuWTVevXpUkNWvWTEuXLrVvdQAAAMB92BxmCxcurLNnz0qSSpYsqd9++02StG3bNrm7u9u3OgAAAOA+bA6zrVq1UlhYmCSpZ8+eGjhwoPz8/NSxY0d16dLF7gUCAAAA92LzagbDhw+3fh0SEqJixYpp48aN8vPzU/Pmze1aHAAAAHA/NofZf3r22Wf17LPP2qMWAAAAwCbcNAEAAABOizALAAAAp0WYBQAAgNMizAIAAMBp2RxmT58+rYiICOvzrVu36l//+pcmTJhg18IAAACAB7E5zLZr106rV6+WdPtuYI0aNdLWrVvVv39/DR061O4FAgAAAPdic5jdt2+fqlWrJkmaO3euypcvr40bN2rmzJmaNm2avesDAAAA7snmMBsfH2+9be2qVasUHBwsSSpTpoz1NrcAAABAerA5zJYrV07jxo3TunXrtHLlSgUFBUmSzpw5o9y5c9u9QAAAAOBebA6zX3zxhcaPH6/nnntObdu2VaVKlSRJixYtsg4/AAAAANKDzbezfe6553Tx4kVFRUXJ29vb2t69e3d5enratTgAAADgfh5qnVljjLZv367x48fr2rVrkiQ3NzfCLAAAANKVzT2zp06dUlBQkMLDwxUbG6tGjRope/bs+uKLLxQbG6tx48alRZ0AAABAMjb3zPbu3VsBAQG6fPmysmTJYm1v1aqVwsLC7FocAAAAcD8298yuW7dOGzdulJubW5L24sWL66+//rJbYQAAAMCD2Nwzm5iYqISEhGTtERERyp49u12KAgAAAFLD5jDbuHFjjR492vrcYrHo+vXrGjx4sJo0aWLP2gAAAID7snmYwciRIxUYGKiyZcvq5s2bateunY4ePao8efJo1qxZaVEjAAAAkCKbw2zhwoW1e/duzZ49W3v27NH169fVtWtXtW/fPsmEMAAAACCt2RxmJSlTpkzq0KGDvWsBAAAAbPJQYfbMmTNav369zp8/r8TExCTbevXqZZfCAAAAgAexOcxOmzZNb7zxhtzc3JQ7d25ZLBbrNovFQpgFAABAurE5zA4cOFCDBg1Sv3795OLyUHfDBQAAAOzC5jQaExOjV155hSALAAAAh7M5kXbt2lXz5s1Li1oAAAAAm9g8zGDYsGFq1qyZli9frgoVKihz5sxJto8aNcrmIsaOHasvv/xSkZGRqlSpksaMGaNq1aqluO/ChQv1+eef69ixY4qPj5efn5/ee+89vfrqqzafF8D/FP9wabqc5+TwpulyHgDAk+GhwuyKFStUunRpSUo2AcxWc+bMUWhoqMaNG6fq1atr9OjRCgwM1OHDh+Xj45Ns/1y5cql///4qU6aM3NzctGTJEnXu3Fk+Pj4KDAy0+fwAAAD2lB6dA3QM/M9D3QFsypQpeu211+xSwKhRo9StWzd17txZkjRu3DgtXbpUU6ZM0Ycffphs/+eeey7J8969e+uHH37Q+vXrCbMAAABPGJvHzLq7u6tWrVp2OXlcXJy2b9+uhg0b/q8gFxc1bNhQmzZteuDrjTEKCwvT4cOHVbdu3RT3iY2NVVRUVJIHAAAAMgabw2zv3r01ZswYu5z84sWLSkhIUL58+ZK058uXT5GRkfd83dWrV5UtWza5ubmpadOmGjNmjBo1apTivsOGDZOXl5f1UaRIEbvUDgAAAMezeZjB1q1b9d///ldLlixRuXLlkk0AW7hwod2Ku5fs2bNr165dun79usLCwhQaGipfX99kQxAkqV+/fgoNDbU+j4qKItACj4uPvdLpPFfT5zwAgHRnc5jNmTOnWrdubZeT58mTR66urjp37lyS9nPnzil//vz3fJ2Li4tKlSolSapcubIOHjyoYcOGpRhm3d3d5e7ubpd6AQAA8HixOcxOnTrVbid3c3OTv7+/wsLC1LJlS0lSYmKiwsLC1KNHj1QfJzExUbGxsXarCwAAAM7B5jBrb6GhoerUqZMCAgJUrVo1jR49WtHR0dbVDTp27KhChQpp2LBhkm6PgQ0ICFDJkiUVGxurZcuW6ccff9T333/vyG8DAAAADpCqMPvMM88oLCxM3t7eqlKlyn3Xk92xY4dNBYSEhOjChQsaNGiQIiMjVblyZS1fvtw6KSw8PDzJrXOjo6P19ttvKyIiQlmyZFGZMmU0Y8YMhYSE2HReAAAAOL9UhdkWLVpYx522aNHioW6OcD89evS457CCNWvWJHn+6aef6tNPP7Xr+QEAAJxaekyofUwn06YqzA4ePNj69ccff5xWtQAAAAA2sXmdWV9fX/3999/J2q9cuSJfX1+7FAUAAACkhs1h9uTJk0pISEjWHhsbq4iICLsUBQAAAKRGqlczWLRokfXrFStWyMvrf2MzEhISFBYWphIlSti3OgAAAOA+Uh1m76wDa7FY1KlTpyTbMmfOrOLFi2vkyJF2LQ4AAAC4n1SH2cTERElSiRIltG3bNuXJkyfNigIAAABSw+abJpw4cSIt6gAAAABs5vA7gAFARlX8w6Xpcp6Tw5umy3mQMaXHzyk/o0hLNq9mAAAAADwuCLMAAABwWgwzAAA4DT4SB/BPqQqzUVFRqT5gjhw5HroYAMAjeoLvzw7gyZSqMJszZ05ZLJb77mOMkcViSfHuYAAAAEBaSFWYXb16dVrXAQAAnhR8ggA7SlWYrVevXlrXAQAAANgsVWF2z549qT5gxYoVH7oYAAAAwBapCrOVK1eWxWKRMea++zFmFgCQ4fCROPBYS1WY5Ra2AAAAeBylKswWK1YsresAAAAAbPbQN004cOCAwsPDFRcXl6Q9ODj4kYsCAAAAUsPmMPvnn3+qVatW2rt3b5JxtHfWoWXMLAAAANKLi60v6N27t0qUKKHz58/L09NT+/fv1++//66AgACtWbMmDUoEAAAAUmZzz+ymTZv03//+V3ny5JGLi4tcXFxUu3ZtDRs2TL169dLOnTvTok4AAAAgGZt7ZhMSEpQ9e3ZJUp48eXTmzBlJtyeJHT582L7VAQAAAPdhc89s+fLltXv3bpUoUULVq1fXiBEj5ObmpgkTJsjX1zctagQAAABSZHOYHTBggKKjoyVJQ4cOVbNmzVSnTh3lzp1bc+bMsXuBAAAAwL3YHGYDAwOtX5cqVUqHDh3SpUuX5O3tbV3RAAAAAEgPD73O7N1y5cplj8MAAAAANrF5AhgAAADwuCDMAgAAwGkRZgEAAOC0bAqz8fHx6tKli06cOJFW9QAAAACpZlOYzZw5sxYsWJBWtQAAAAA2sXmYQcuWLfXLL7+kQSkAAACAbWxemsvPz09Dhw7Vhg0b5O/vr6xZsybZ3qtXL7sVBwAAANyPzWF28uTJypkzp7Zv367t27cn2WaxWAizAAAASDc2h1kmfwEAAOBx8dBLc8XFxenw4cO6deuWPesBAAAAUs3mMBsTE6OuXbvK09NT5cqVU3h4uCSpZ8+eGj58uN0LBAAAAO7F5jDbr18/7d69W2vWrJGHh4e1vWHDhpozZ45diwMAAADux+Yxs7/88ovmzJmjZ599VhaLxdperlw5HT9+3K7FAQAAAPdjc8/shQsX5OPjk6w9Ojo6SbgFAAAA0prNYTYgIEBLly61Pr8TYCdNmqQaNWrYrzIAAADgAWweZvD555/rhRde0IEDB3Tr1i198803OnDggDZu3Ki1a9emRY0AAABAimzuma1du7Z27dqlW7duqUKFCvrtt9/k4+OjTZs2yd/fPy1qBAAAAFJkc8+sJJUsWVITJ060dy0AAACATWzumW3YsKGmTZumqKiotKgHAAAASDWbw2y5cuXUr18/5c+fXy+//LL+85//KD4+Pi1qAwAAAO7L5jD7zTff6K+//tIvv/yirFmzqmPHjsqXL5+6d+/OBDAAAACkK5vDrCS5uLiocePGmjZtms6dO6fx48dr69atatCggb3rAwAAAO7poSaA3REZGanZs2drxowZ2rNnj6pVq2avugAAAIAHsrlnNioqSlOnTlWjRo1UpEgRff/99woODtbRo0e1efPmtKgRAAAASJHNPbP58uWTt7e3QkJCNGzYMAUEBKRFXQAAAMAD2RxmFy1apOeff14uLg813BYAAACwG5vDbKNGjSRJFy5c0OHDhyVJpUuXVt68ee1bGQAAAPAANnevxsTEqEuXLipQoIDq1q2runXrqmDBguratatiYmLSokYAAAAgRTaH2XfffVdr167V4sWLdeXKFV25ckX/+c9/tHbtWr333ntpUSMAAACQIpuHGSxYsEDz58/Xc889Z21r0qSJsmTJojZt2uj777+3Z30AAADAPT3UMIN8+fIla/fx8WGYAQAAANKVzWG2Ro0aGjx4sG7evGltu3HjhoYMGaIaNWrYtTgAAADgfmweZvDNN98oMDBQhQsXVqVKlSRJu3fvloeHh1asWGH3AgEAAIB7sTnMli9fXkePHtXMmTN16NAhSVLbtm3Vvn17ZcmSxe4FAgAAAPdic5iVJE9PT3Xr1s3etQAAAAA24TZeAAAAcFqEWQAAADgtwiwAAACcFmEWAAAATuuhwuyVK1c0adIk9evXT5cuXZIk7dixQ3/99ZddiwMAAADux+bVDPbs2aOGDRvKy8tLJ0+eVLdu3ZQrVy4tXLhQ4eHhmj59elrUCQAAACRjc89saGioXnvtNR09elQeHh7W9iZNmuj333+3a3EAAADA/dgcZrdt26Y33ngjWXuhQoUUGRlpl6IAAACA1LA5zLq7uysqKipZ+5EjR5Q3b167FAUAAACkhs1hNjg4WEOHDlV8fLwkyWKxKDw8XB988IFefPFFuxcIAAAA3IvNYXbkyJG6fv26fHx8dOPGDdWrV0+lSpVS9uzZ9dlnn6VFjQAAAECKbA6zXl5eWrlypRYvXqxvv/1WPXr00LJly7R27VplzZr1oYoYO3asihcvLg8PD1WvXl1bt269574TJ05UnTp15O3tLW9vbzVs2PC++wMAACDjsnlprjtq166t2rVrP3IBc+bMUWhoqMaNG6fq1atr9OjRCgwM1OHDh+Xj45Ns/zVr1qht27aqWbOmPDw89MUXX6hx48bav3+/ChUq9Mj1AAAAwHnYHGa//fbbFNstFos8PDxUqlQp1a1bV66urqk63qhRo9StWzd17txZkjRu3DgtXbpUU6ZM0Ycffphs/5kzZyZ5PmnSJC1YsEBhYWHq2LGjjd8NAAAAnJnNYfbrr7/WhQsXFBMTI29vb0nS5cuX5enpqWzZsun8+fPy9fXV6tWrVaRIkfseKy4uTtu3b1e/fv2sbS4uLmrYsKE2bdqUqnpiYmIUHx+vXLlypbg9NjZWsbGx1ucprcQAAAAA52TzmNnPP/9cVatW1dGjR/X333/r77//1pEjR1S9enV98803Cg8PV/78+fXuu+8+8FgXL15UQkKC8uXLl6Q9X758qV6z9oMPPlDBggXVsGHDFLcPGzZMXl5e1seDAjYAAACch81hdsCAAfr6669VsmRJa1upUqX01VdfqV+/fipcuLBGjBihDRs22LXQlAwfPlyzZ8/Wzz//nORuZHfr16+frl69an2cPn06zesCAABA+rB5mMHZs2d169atZO23bt2y9qYWLFhQ165de+Cx8uTJI1dXV507dy5J+7lz55Q/f/77vvarr77S8OHDtWrVKlWsWPGe+7m7u8vd3f2BtQAAAMD52NwzW79+fb3xxhvauXOntW3nzp1666231KBBA0nS3r17VaJEiQcey83NTf7+/goLC7O2JSYmKiwsTDVq1Ljn60aMGKFPPvlEy5cvV0BAgK3fAgAAADIIm8Ps5MmTlStXLvn7+1t7PQMCApQrVy5NnjxZkpQtWzaNHDkyVccLDQ3VxIkT9cMPP+jgwYN66623FB0dbV3doGPHjkkmiH3xxRcaOHCgpkyZouLFiysyMlKRkZG6fv26rd8KAAAAnJzNwwzy58+vlStX6tChQzpy5IgkqXTp0ipdurR1n/r166f6eCEhIbpw4YIGDRqkyMhIVa5cWcuXL7dOCgsPD5eLy/8y9/fff6+4uDi99NJLSY4zePBgffzxx7Z+OwAAAHBiD33ThDJlyqhMmTJ2KaJHjx7q0aNHitvWrFmT5PnJkyftck4AAAA4v4cKsxEREVq0aJHCw8MVFxeXZNuoUaPsUhgAAADwIDaH2bCwMAUHB8vX11eHDh1S+fLldfLkSRlj9Mwzz6RFjQAAAECKbJ4A1q9fP/Xp00d79+6Vh4eHFixYoNOnT6tevXp6+eWX06JGAAAAIEU2h9mDBw+qY8eOkqRMmTLpxo0bypYtm4YOHaovvvjC7gUCAAAA92JzmM2aNat1nGyBAgV0/Phx67aLFy/arzIAAADgAWweM/vss89q/fr1evrpp9WkSRO999572rt3rxYuXKhnn302LWoEAAAAUmRzmB01apT1BgVDhgzR9evXNWfOHPn5+bGSAQAAANKVTWE2ISFBERERqlixoqTbQw7GjRuXJoUBAAAAD2LTmFlXV1c1btxYly9fTqt6AAAAgFSzeQJY+fLl9eeff6ZFLQAAAIBNbA6zn376qfr06aMlS5bo7NmzioqKSvIAAAAA0ovNE8CaNGkiSQoODpbFYrG2G2NksViUkJBgv+oAAACA+7A5zK5evTot6gAAAABsZnOYrVevXlrUAQAAANjM5jGzkrRu3Tp16NBBNWvW1F9//SVJ+vHHH7V+/Xq7FgcAAADcj81hdsGCBQoMDFSWLFm0Y8cOxcbGSpKuXr2qzz//3O4FAgAAAPfyUKsZjBs3ThMnTlTmzJmt7bVq1dKOHTvsWhwAAABwPzaH2cOHD6tu3brJ2r28vHTlyhV71AQAAACkis1hNn/+/Dp27Fiy9vXr18vX19cuRQEAAACpYXOY7datm3r37q0tW7bIYrHozJkzmjlzpvr06aO33norLWoEAAAAUmTz0lwffvihEhMT9fzzzysmJkZ169aVu7u7+vTpo549e6ZFjQAAAECKbA6zFotF/fv3V9++fXXs2DFdv35dZcuWVbZs2dKiPgAAAOCebB5mMGPGDMXExMjNzU1ly5ZVtWrVCLIAAABwCJvD7LvvvisfHx+1a9dOy5YtU0JCQlrUBQAAADyQzWH27Nmzmj17tiwWi9q0aaMCBQronXfe0caNG9OiPgAAAOCebA6zmTJlUrNmzTRz5kydP39eX3/9tU6ePKn69eurZMmSaVEjAAAAkCKbJ4DdzdPTU4GBgbp8+bJOnTqlgwcP2qsuAAAA4IFs7pmVpJiYGM2cOVNNmjRRoUKFNHr0aLVq1Ur79++3d30AAADAPdncM/vKK69oyZIl8vT0VJs2bTRw4EDVqFEjLWoDAAAA7svmMOvq6qq5c+cqMDBQrq6uaVETAAAAkCo2h9mZM2emRR0AAACAzR5qAlh0dLTWrl2r8PBwxcXFJdnWq1cvuxQGAAAAPIjNYXbnzp1q0qSJYmJiFB0drVy5cunixYvy9PSUj48PYRYAAADp5qHuANa8eXNdvnxZWbJk0ebNm3Xq1Cn5+/vrq6++SosaAQAAgBTZHGZ37dql9957Ty4uLnJ1dVVsbKyKFCmiESNG6KOPPkqLGgEAAIAU2RxmM2fOLBeX2y/z8fFReHi4JMnLy0unT5+2b3UAAADAfdg8ZrZKlSratm2b/Pz8VK9ePQ0aNEgXL17Ujz/+qPLly6dFjQAAAECKbO6Z/fzzz1WgQAFJ0meffSZvb2+99dZbunDhgiZMmGD3AgEAAIB7sblnNiAgwPq1j4+Pli9fbteCAAAAgNSyuWcWAAAAeFykKswGBQVp8+bND9zv2rVr+uKLLzR27NhHLgwAAAB4kFQNM3j55Zf14osvysvLS82bN1dAQIAKFiwoDw8PXb58WQcOHND69eu1bNkyNW3aVF9++WVa1w0AAACkLsx27dpVHTp00Lx58zRnzhxNmDBBV69elSRZLBaVLVtWgYGB2rZtm55++uk0LRgAAAC4I9UTwNzd3dWhQwd16NBBknT16lXduHFDuXPnVubMmdOsQAAAAOBebF7N4A4vLy95eXnZsxYAAADAJqxmAAAAAKdFmAUAAIDTIswCAADAaRFmAQAA4LRSHWa3bt2qhISEe26PjY3V3Llz7VIUAAAAkBqpDrM1atTQ33//bX2eI0cO/fnnn9bnV65cUdu2be1bHQAAAHAfqQ6zxpj7Pr9XGwAAAJBW7Dpm1mKx2PNwAAAAwH0xAQwAAABOy6Y7gB04cECRkZGSbg8pOHTokK5fvy5Junjxov2rAwAAAO7DpjD7/PPPJxkX26xZM0m3hxcYYxhmAAAAgHSV6jB74sSJtKwDAAAAsFmqw2yxYsUeuM++ffseqRgAAADAFo88AezatWuaMGGCqlWrpkqVKtmjJgAAACBVHjrM/v777+rUqZMKFCigr776Sg0aNNDmzZvtWRsAAABwXzZNAIuMjNS0adM0efJkRUVFqU2bNoqNjdUvv/yismXLplWNAAAAQIpS3TPbvHlzlS5dWnv27NHo0aN15swZjRkzJi1rAwAAAO4r1T2zv/76q3r16qW33npLfn5+aVkTAAAAkCqp7pldv369rl27Jn9/f1WvXl3fffcdN0oAAACAQ6U6zD777LOaOHGizp49qzfeeEOzZ89WwYIFlZiYqJUrV+ratWtpWScAAACQjM2rGWTNmlVdunTR+vXrtXfvXr333nsaPny4fHx8FBwcnBY1AgAAACl6pHVmS5curREjRigiIkKzZs2yV00AAABAqjzyTRMkydXVVS1bttSiRYvscTgAAAAgVVK9mkGXLl0euI/FYtHkyZMfqSAAAAAgtVIdZqdNm6ZixYqpSpUqMsakZU0AAABAqqQ6zL711luaNWuWTpw4oc6dO6tDhw7KlStXWtYGAAAA3Feqx8yOHTtWZ8+e1fvvv6/FixerSJEiatOmjVasWEFPLQAAABzCpglg7u7uatu2rVauXKkDBw6oXLlyevvtt1W8eHFdv349rWoEAAAAUvTQqxm4uLjIYrHIGKOEhAR71gQAAACkik1hNjY2VrNmzVKjRo301FNPae/evfruu+8UHh6ubNmyPVQBY8eOVfHixeXh4aHq1atr69at99x3//79evHFF1W8eHFZLBaNHj36oc4JAACAjCHVYfbtt99WgQIFNHz4cDVr1kynT5/WvHnz1KRJE7m4PFwH75w5cxQaGqrBgwdrx44dqlSpkgIDA3X+/PkU94+JiZGvr6+GDx+u/PnzP9Q5AQAAkHGkejWDcePGqWjRovL19dXatWu1du3aFPdbuHBhqk8+atQodevWTZ07d7aeY+nSpZoyZYo+/PDDZPtXrVpVVatWlaQUtwMAAODJkuow27FjR1ksFrudOC4uTtu3b1e/fv2sbS4uLmrYsKE2bdpkt/PExsYqNjbW+jwqKspuxwYAAIBj2XTTBHu6ePGiEhISlC9fviTt+fLl06FDh+x2nmHDhmnIkCF2Ox4AAAAeHw+9moGz6Nevn65evWp9nD592tElAQAAwE5S3TNrb3ny5JGrq6vOnTuXpP3cuXN2ndzl7u4ud3d3ux0PAAAAjw+H9cy6ubnJ399fYWFh1rbExESFhYWpRo0ajioLAAAATsRhPbOSFBoaqk6dOikgIEDVqlXT6NGjFR0dbV3doGPHjipUqJCGDRsm6faksQMHDli//uuvv7Rr1y5ly5ZNpUqVctj3AQAAAMdwaJgNCQnRhQsXNGjQIEVGRqpy5cpavny5dVJYeHh4kjVsz5w5oypVqliff/XVV/rqq69Ur149rVmzJr3LBwAAgIM5NMxKUo8ePdSjR48Ut/0zoBYvXlzGmHSoCgAAAM4gw69mAAAAgIyLMAsAAACnRZgFAACA0yLMAgAAwGkRZgEAAOC0CLMAAABwWoRZAAAAOC3CLAAAAJwWYRYAAABOizALAAAAp0WYBQAAgNMizAIAAMBpEWYBAADgtAizAAAAcFqEWQAAADgtwiwAAACcFmEWAAAAToswCwAAAKdFmAUAAIDTIswCAADAaRFmAQAA4LQIswAAAHBahFkAAAA4LcIsAAAAnBZhFgAAAE6LMAsAAACnRZgFAACA0yLMAgAAwGkRZgEAAOC0CLMAAABwWoRZAAAAOC3CLAAAAJwWYRYAAABOizALAAAAp0WYBQAAgNMizAIAAMBpEWYBAADgtAizAAAAcFqEWQAAADgtwiwAAACcFmEWAAAAToswCwAAAKdFmAUAAIDTIswCAADAaRFmAQAA4LQIswAAAHBahFkAAAA4LcIsAAAAnBZhFgAAAE6LMAsAAACnRZgFAACA0yLMAgAAwGkRZgEAAOC0CLMAAABwWoRZAAAAOC3CLAAAAJwWYRYAAABOizALAAAAp0WYBQAAgNMizAIAAMBpEWYBAADgtAizAAAAcFqEWQAAADgtwiwAAACcFmEWAAAAToswCwAAAKdFmAUAAIDTIswCAADAaRFmAQAA4LQIswAAAHBahFkAAAA4LcIsAAAAnBZhFgAAAE6LMAsAAACnRZgFAACA03oswuzYsWNVvHhxeXh4qHr16tq6det99583b57KlCkjDw8PVahQQcuWLUunSgEAAPA4cXiYnTNnjkJDQzV48GDt2LFDlSpVUmBgoM6fP5/i/hs3blTbtm3VtWtX7dy5Uy1btlTLli21b9++dK4cAAAAjubwMDtq1Ch169ZNnTt3VtmyZTVu3Dh5enpqypQpKe7/zTffKCgoSH379tXTTz+tTz75RM8884y+++67dK4cAAAAjpbJkSePi4vT9u3b1a9fP2ubi4uLGjZsqE2bNqX4mk2bNik0NDRJW2BgoH755ZcU94+NjVVsbKz1+dWrVyVJUVFRj1h96iXGxqTLeZJ8T7EmXc6pdLyOd+Oa2h/X1P4y7DV10PWU0ueaJvv7wDV9ZFxT+8vo1/TO92dMKr4v40B//fWXkWQ2btyYpL1v376mWrVqKb4mc+bM5qeffkrSNnbsWOPj45Pi/oMHDzaSePDgwYMHDx48eDjZ4/Tp0w/Mkw7tmU0P/fr1S9KTm5iYqEuXLil37tyyWCwOrCxtREVFqUiRIjp9+rRy5Mjh6HIyBK6pfXE97Y9ran9cU/vjmtpfRr6mxhhdu3ZNBQsWfOC+Dg2zefLkkaurq86dO5ek/dy5c8qfP3+Kr8mfP79N+7u7u8vd3T1JW86cOR++aCeRI0eODPeD7WhcU/vietof19T+uKb2xzW1v4x6Tb28vFK1n0MngLm5ucnf319hYWHWtsTERIWFhalGjRopvqZGjRpJ9peklStX3nN/AAAAZFwOH2YQGhqqTp06KSAgQNWqVdPo0aMVHR2tzp07S5I6duyoQoUKadiwYZKk3r17q169eho5cqSaNm2q2bNn648//tCECRMc+W0AAADAARweZkNCQnThwgUNGjRIkZGRqly5spYvX658+fJJksLDw+Xi8r8O5Jo1a+qnn37SgAED9NFHH8nPz0+//PKLypcv76hv4bHi7u6uwYMHJxtagYfHNbUvrqf9cU3tj2tqf1xT++Oa3mYxJjVrHgAAAACPH4ffNAEAAAB4WIRZAAAAOC3CLAAAAJwWYRYAAABOizALAADwhDl58qT27dvn6DLsgjD7BGIBi7SVkJCQ5HliYqKDKnFu/JzicXfmzBlHl5Ah8X8/7Z06dUq+vr6qX7++du3a5ehyHhlh9gly6tQpSZLFYnFwJRlXfHy8XF1dJUm//vqrYmJikqyTDNtt2bJFJ06ccHQZQBJ79+5Vx44ddeTIEUeXkiGcOnVKK1askMTfqPTg4uKiwoULKzY2Vi+88IL++OMPR5f0SPgrm4EdOXJEgwcPliTNmzdPL774ov78808HV5VxLVu2zHpb5dDQUPXp00fXrl1zcFXO506vjMVi0YoVK1SjRg0dPXpUt27dcnBlzu3OdY2KitL169cVHR2dbBtSLy4uTlu2bLGGAK7hw/vrr7/k7++v999/XwsWLHB0ORmeMUa5cuVSgwYN9Oabb6pp06Zq1KiRUwdah98BDGln586d+uSTT7Rv3z79/PPPmjp1qnx9fR1dVoZVoEAB/f333/L19dWlS5e0detW653skHp3emUiIyN1/vx5jRgxQo0bN3ZwVc7NGCOLxaLFixdr/PjxOnr0qPz9/VWrVi2988479ISlUmJiolxcXGSMkb+/v/r06aNPPvlEtWvXVtGiRR1dntPav3+/Ll26pFKlSmnGjBm6deuWQkJCHF1WhnTnd0HWrFkVHBys7t27a9myZYqPj1dgYKCWL1+uqlWrOrpMm9Ezm4GFhITojTfe0M8//6wmTZqoU6dOkuhBSCtVqlRR/fr1dfLkSZUoUUJPPfWUJMbMPoxjx46pYMGC6tu3r7Jly+bocpyexWLRkiVL1KZNGz333HP66quvlCtXLvXs2VMbN250dHlOIy4uTtL/3nA1bNhQOXLk0I4dOyQlHy+P1GncuLHatGmj+Ph4ubi4aPLkyZo/f76jy8pQjh8/rp07d+ry5cvWttatW6tp06Zav369vv32W9WtW1cvvPCCtm3b5sBKHw5hNgO6O6wWLVpUHTt21KpVq9SnTx9Jt38R/zNgEXDto02bNpo9e7Zu3LihmjVrKi4uTi4uLsk+Iud631/+/Pk1ZMgQXb161TrWm2v28KKjozVt2jQNGTJEffr0UY0aNfTLL7/onXfeUc2aNR1dnlP4448/9PTTT2v69Ok6duyYJKlWrVry9fXVwIEDJck6Xh6pFxsbK0lq27atKleurC5dusjd3V3ff/89Qw7sJCIiQn5+fqpdu7befvttffvtt9Y3ZtWrV9eMGTPk5eWlOXPmqG7dugoODtamTZscXLWNDDKUxMREY4wxW7ZsMb/++quJiooyxhgzffp04+bmZt57770k++/evTvda8woEhISkjy/c+2NMWbbtm2mVKlSpkaNGubWrVvW9hkzZpiYmJh0q9GZXbp0yQwdOtRYLBYzefJkR5fj1GJiYkzFihXNsmXLzJkzZ0yhQoVMt27drNvnzp1rtm7d6sAKH193/l9v27bN9O7d2xQtWtTUr1/fDBgwwCQkJJhjx46ZmjVrmrFjxzq4Uudx+vRps3Tp0iRt4eHhpmTJkuaHH34w4eHhplmzZub555838+bNc1CVGUNUVJQ5ffq0qVy5ssmcObMZMGCAKVasmAkODjaDBg0y169fN/7+/ubbb781xhhz9epV06hRI+Pr62tu3Ljh4OpTjzCbgdz5pbtgwQLj7e1tPvvsM/Pnn38aY4yJi4szP/74o3F3dzfvvvuuiYqKMoMHDzbVq1c3f//9tyPLdkp3B9lp06aZDz74wLz99ttm165d1vbt27cbPz8/4+/vb9auXWsaNmxo6tatmywEP+nu/NwePHjQbN682axatcq67fr162bQoEHGYrGYqVOnOqhC53P3GytjjLlx44YJCQkxn3zyiSlRooTp1q2bdZ9z586ZLl26mOnTp/OzeZc71+fatWtJ2jdu3GhGjRplfHx8TK1atcybb75pGjVqZN58801HlOl0Tp48aXLnzm0sFot56aWXzMKFC82pU6eMMcbMmjXL1KtXz1y+fNns2LHDNG/e3AQFBZmZM2c6uGrntGPHDtOoUSNz7Ngxc+rUKVOuXDkTFBRk9u7dayZOnGgaN25sSpYsaXx8fEyLFi2s4fXq1avm9OnTDq7eNoTZDGbVqlUmR44cZuLEiebmzZvW9ju/mH/66SeTKVMmU65cOePt7W3++OMPR5WaIbz//vumSJEipnXr1uall14ybm5u5pdffrFuP3DggPH39zdlypQxdevWNXFxccaY5GHjSXXnOvz888+mZMmS5qmnnjL58+c3rVu3NpcvXzbGGBMdHW0GDRpk3NzczPfff+/Aap3DnWv622+/mQEDBlg/Cfjmm2+MxWIxDRo0SPK7oV+/fsbPz8+cOHHCEeU+1pYsWWLq169vmjdvbgYNGmT9/2vM7T/4AwcONK1btzYWi8W4ublZf2aRslu3bpldu3aZ8uXLm+rVq5vKlSubLl26GF9fXzNz5kwzZ84cExwcbFavXm2Mud0hULduXdOyZUvrp4xInZ07d5rMmTOb999/39p26tQpU6JECfP888+biIgIY8ztNxBdu3Y1P/74o6NKtQvCbAbTo0cP065dO2PM7RCwdetW06NHD/Pee++Zbdu2GWOMOXr0qJk9e7b13TAezsSJE03hwoWtbwiWLl1qLBaL8fT0TPaLYd++fdZer/j4+HSv9XG2YsUKkyNHDjNhwgQTFRVlfv31V2OxWExwcLA5d+6cMeb2z/J7771ncuXKZa5cueLgih9/8+fPN7ly5TLvvPOO2bNnj7X9o48+MpkyZTI9e/Y0//rXv0znzp1Njhw5zM6dOx1X7GNq06ZNJnPmzKZPnz7mxRdfNAEBAaZp06ZJAu2tW7fMjRs3zJQpU8z+/fsdWO3jb9u2bcbPz8/Ex8eb+fPnm1atWpnWrVubxYsXm+nTp5u6deuaFi1aGIvFYurXr2/9fbl7924THh7u4Oqdy6FDh0zWrFnNiBEjrG133uSeOnXK+Pn5mWrVqpnIyEhjjEnyM+2sCLMZxJ0f1B49epgXXnjBLF682Lz66qsmKCjIVKpUyQQFBZlnn33WGg7waK5fv24+/fRT61jORYsWmezZs5vx48eb3r17m6xZs5r58+cn+9iWj3GTunz5sunevbv57LPPjDG3x82VKFHChISEmEKFCpnAwEBz9uxZY8ztcZ/nz593ZLlOYevWrSZnzpzJxhnf+YM1efJk8+KLL5o6deqYnj17EsJSsG/fPvPDDz+Yr776yhhjzM2bN82cOXNMlSpVzAsvvGC9lrwxTZ1du3aZ7Nmzm7ffftvaNnfuXNO4cWPTtGlTc+rUKXPlyhWzevVq06BBAzN9+nQHVuvcdu/ebby9vY3FYjF79+41xtz+Ob3708BTp06Zp556ylSvXt389ddfjirVrgizGczixYvNM888Y/LmzWvatWtnFi1aZIwxZurUqaZOnTpMPnpId34R3P0LYefOnebkyZPm6NGjpkyZMuabb74xxhizZs0aY7FYjMViMcuXL3dIvc7i1q1bZsaMGebQoUPm4sWLpkqVKtaJST/++KOxWCzmueeeI8TaYOrUqSYoKMgYc3sS3bx580xwcLDx9/c3//73v40xt4NtYmJiksmJuO3UqVPG39/feHt7W/9PG3M70M6bN89UqVLFNGvWzMTGxjqwSudx4MABky1bNvPRRx8ZY5K+AViwYIFp0KCBadq0qdm+fbsxhjf8j2LXrl0mS5YspkuXLqZTp04mb968ZtOmTcaY5Nf11KlTpmzZsubpp582Z86ccUS5dsXSXE7K/P8yRfv379evv/6qpUuX6ubNm2rWrJkWLlyo33//XTNnzlSzZs0kSQcPHlSmTJkUHx/vyLKdUmJionVdyZiYGN28eVOSVLlyZRUrVkzHjx9X1qxZ1aJFC0mSp6enevfurfHjx+v55593WN2PI/OP5bVcXV0VEhKi0qVL67fffpOHh4cGDBggSfLw8NDzzz+vS5cuJblbFZK7+7pmzpxZK1as0OTJk9WqVStNmzZNefLkUaVKlTRw4EAdP35cmTNnlsViYSmpFOTMmVOvvPKKcuXKpV9//dXa7u7uruDgYA0YMED79+9X+/btHVilc9izZ4/q1Kkjd3d3tWzZUpKUKVMm61KFrVu31jvvvKPY2FgNHjxYf/zxB7f/fkiHDx9WlSpV1LdvX02ePFnvv/++GjRooODgYG3ZskUuLi5JluQsWrSolixZoqxZs1qXR3NqDg7TeAh3egcXLlxoSpQoYfz8/EzlypVN5cqVzcWLF5Psu23bNtO3b1+TI0eOJDPtkTp3v5sdOXKkCQoKMnXr1jVt2rSxTkiYN2+esVgsZt26debEiROmefPmpn379tbX8VHkbXcvGzd69GgzfPjwJCsXDBkyxPj6+lr369evnxkwYECGGM+VVu5cq+vXryd5Hhoaavz8/Ez37t3N5s2bjTG3xx1XqFDBOnYet6U0GTMqKsqMHTvWPPXUU6Zr165JtsXGxpr//Oc/1pVikLKdO3caT09P0717d1O1alXTuHFj89///te6/e7fiwsXLjRBQUGmTp06jN9+CImJiSYqKsp89913Sdr3799vQkJCTN68ea2/B/7ZQ5tR/j4RZp3UqlWrjJeXl5kwYYJJSEgwv/32m7FYLObpp5+2Lqlx6NAh06JFC/Pss8+ynuwj6tevn/Hx8TFjx441ixcvNtmzZzf16tWzBtp27doZi8VifH19TcWKFQlg9zB//nzj4+NjAgMDTZs2bYzFYrFOUjh8+LDJmTOneeaZZ0yjRo1Mjhw5kkxeQsrunnH/8ccfW/843ZnccceHH35onn76acbN3+VOkF2/fr354osvzAcffGBWrlxpjLk9rOC7774zFSpUSBZocX/Hjx83mTNnNn379jXGGHPs2DFTsWJF07hxY+tKBcYkDVKzZs0yrVq1YrKXjY4fP24GDRqU5I3C3YE1pUCbEYcXEWadUFRUlHnnnXesk2b++usvU7RoUdOuXTtTtWpV4+fnZx3UfeDAAesEGjycw4cPm4oVK1p7EZcuXWpy5MiRbJmoZcuWmd9++836iyKjvOO1l/3795uCBQtax22Gh4cbV1dX07dv3yQL03fo0MH06tXL7Nu3z5HlOoV/zrj39/dPMuM+MTHRLFmyxHTv3t3kzp3b7Nixw8EVP37mz59vsmXLZurVq2eqV69uLBaLeffdd01kZKS5ceOGGTNmjPH39zdt2rRxdKlOISEhwYSFhZlp06YZY/4XnFITaP+5pi/ub8+ePaZEiRKmQ4cOZu7cuUm23f2Jw51AW7BgQbN+/fr0LjNdEGad1OLFi80ff/xhLl26ZJ555hnzxhtvGGOMmTNnjrFYLCZfvnzWdeTwaDZu3GiKFi1qjLl93bNly2bGjRtnjLm91uSkSZOSvSYjvvN9VGvWrDENGjQwxhjz559/msKFCydZaP7o0aPGGMPEpFS634z7Jk2amLi4OHPr1i0zevRo06RJE94cpODo0aOmaNGiZuLEidY//rNmzTK5c+c2ffr0McYYc+XKFfPFF1+YOnXqZIiJMmnp+PHjZvjw4ebQoUNJ2u/8fz5+/HiKgZb/77Y7dOiQyZUrl/nwww/NhQsXUtzn7ut64MAB88ILLxg/Pz9z48aNDLfWOWH2MffP28n98wdwyZIlpmbNmtYFz8PCwkyzZs1MixYtzJEjR9KrzAzj7ut75+uLFy+a+vXrm/79+5ts2bKZ8ePHW/fZsWOHCQwMNFu2bEn3Wp3Nr7/+asqXL2+2bNliihUrZrp37279Zfv777+bV155hY8YUyk1M+6Dg4OtPbRXr151VKmPlfPnz5tt27ZZZ87v3bvX+Pr6ml27diX5vz9z5kzj4uJi1q1bZ4y53WN46dIlh9TsLPbs2WNKlixpXnjhBTNr1qxk2/8ZaJs0aWJWrFiR3mVmCLGxseb1119Pdte5qKgoc+zYMRMWFpbiG4RDhw5l2E4upg0+xv766y917NhRq1evtrbdmVV/x6lTp7Rr1y4VLlxYkhQWFqa8efNqzpw58vPzS9d6nd3dqxbcLVOmTMqVK5dGjBih7t27q3v37pKkmzdvasCAAfLw8FBAQEB6l/tYM/9YtUCSSpUqpTx58qhx48aqU6eOxo8fb51Nv2jRIl29elVZs2ZN71Kd0p0Z997e3veccb97927rjPscOXI4qtTHxoEDB9SqVSsNHDhQn332mRISEnTz5k2dPn1aN2/elMVisc7qbteuncqWLastW7ZIkrJlyyZvb29Hlv9YO3z4sBo0aKCXXnpJs2bN0iuvvJJsH1dXV926dUu+vr76+eeftXfvXo0fP14xMTEOqNi5ubm56cSJE/L09LS2LVmyRH369FHlypXVunVr1axZU3/99ZckWVePKF26tAoVKuSQmtNaJkcXgHuLjY1VRESERo4cKTc3N9WqVSvZPi1bttTYsWNVqFAhVaxYURs2bNCWLVvk7u7ugIqdlzHGuiTMqFGjtGvXLkVGRqpr165q3ry5Ro0apaNHj+qPP/5Q3759VbhwYf3yyy+6ePGiduzYYV32hGVlbl9Li8WiLVu26OjRozLG6NVXX1WpUqUUHBys/fv3q1ChQjpw4IAsFoumTp2qyZMn6/fff1euXLkcXf5j6c41lW7/YcqRI4fefvttZcuWTaNGjdLrr7+uSZMmSbr9h65Zs2bKlCmTKlSo4MiyHxv79+9X7dq19fbbb+uNN95Q4cKF5eLiooCAALVs2VJdunTR4sWL5evrK0mKi4uTu7s7bwJS4datW/r888/VvHlzDR8+3Np+48YNXbhwQTdu3FDOnDmVL18+67Jcvr6++v3335WYmJgkkOHBjDG6ceOG8uTJozNnzmjx4sXauXOnfvjhB9WuXVujR4/WM888ozZt2qhv37766aeflCnTExD1HNktjAc7cuSICQoKMoGBgUkGbt+ZrZiQkGCOHj1q2rVrZz777DNz4MABR5XqtO6e+dm/f3+TK1cu061bN9O6dWuTM2dO07VrV3P27Flz7NgxExoaaipWrGiaNm1q3nzzTevkBSZ7JfXzzz8bDw8PU6lSJZMpUybTuHFj60TEQYMGmapVq5pMmTIZf39/U6FCBZbjuY87H3+vXLnS/Otf/zINGzY048aNM8ePHze3bt0y3333nalUqRIz7u/h77//NrVr1za9evVK0n7n//369etNUFCQKV26tAkLCzNr1641/fv3N3ny5DHHjx93RMlOJTY21tStW9eMGTPG2rZ06VLTrVs3ky1bNuPt7W0aN25stm7dat3OjREe3erVq02lSpVMqVKljI+Pj5k2bZo5efKkdftbb71lGjdu7MAK0xdh1gncL9DGx8ebvn37mvbt2zMu7hGdPXvW9OzZ0/z+++/WtlmzZpmKFSuad955xxhze9zXnbsn3UGQve3ONYmKijJNmjQxP/zwg7l06ZLZv3+/KV68uKlRo4Z1lY0zZ86Y1atXm0OHDnF3r1RYuHChyZ49u3nzzTfNwIEDTaFChUxQUJA5d+6ciYqKMt9++y0z7u9h//79pmTJkmbt2rX3DFFbt2417du3N+7u7qZUqVKmXLlyrPxgg8DAQBMQEGCOHDliBgwYYHx9fU3btm3NrFmzzJw5c8yzzz5rPvzwQ3Pr1q0MN/HIkSIiIqy3Av6ntm3bmp49ez4xbxwIs04ipUAbGxtrevToYSwWCz1bj2j27NnGYrGYokWLWm//d8ePP/5oPDw8UrzpxJP+i3nPnj1J1tRdtWqVCQ4ONq1bt06yqHxERIQpXrx4ksmKSJ3w8HBTsWJF61JwiYmJJnv27Ob999+3/vxFR0ebESNGmNq1azPj/h9mzpxpMmXKZL1Wd/9xvzNJJjo62hw8eNBcuHDBnDp16p6zw5HUnWu6ceNGU6FCBVOwYEGTN29eM2XKlCT//1u0aGECAwMdVaZTu3jxok2rPcTExJj+/fubfPnymcOHD6dhZY8XwqwTuTvQrl692rz//vsmS5Ys9CDYwZ9//mm98cF//vMfY4xJEtJKlChhXR8Vt/+ITZ8+3RQsWDDJJwKbNm0yXl5ext3d3XqjjjvhISIiwvj5+ZkKFSoQaG0QHh5uqlSpYq5fv26OHDliChUqZLp162bdvmnTJpOQkMCM+3vYsGGD8fDwMPPnz7/nPt9++61p1KiRuXnzZjpW5pzuXmHn7jfz165dMzt37kxyF8rExEQTHx9vOnToYN5//32W4LJRVFSU8fHxMaGhoam6djNmzDDdunUzBQsWfOJyAWHWyRw5csQ0a9bMeHt7Gzc3N+sSM0i9e33scvbsWdO0aVOTO3fuJD3dFy5cMMWLFzc//vhjOlXoPO6M0YqMjLQGgT/++MPkzZvXtGrVyvrx150/euHh4aZSpUpJxnbhf6Kjo82FCxfMf//7XxMREWGuXLliIiIiTKFChcx///tfU7JkSdOtWzfrz/Du3btNSEiI+eOPPxxc+eMrIiLC+Pj4mODg4CQ/d3cHsffee898+OGHT/wnLQ8SERFhXn755Xvebeqf4uPjzYABA0zBggWTrT2L1JkwYYLx8PAwAwcOvG+gPXTokGnZsqXp1KmTOXjwYDpW+HggzDqhQ4cOmeDgYBZBfwh3/+KdOXOm+fjjj83AgQOt6x1evHjRNGnSxHh7e5vBgwebf//736Zp06amQoUKjI29y51fqgkJCWbXrl0mW7ZsZs6cOdZAu3nzZuPt7W1efvlla8/tnWtP70zKDh8+bDp27GjKlCljPDw8jJeXl2nXrp3Zu3evef/9943FYjEvvfRSktf069fPVK1alaEFD7BgwQLj7u5uXn31VbN//35re3R0tOnXr58pVqzYE/WR7MM6fvy4qVGjhmnatOkD7yQ1adIk88Ybb5i8efM+cb2E9jZ9+nTj6up6z0B78+ZNs3v3bnP58uUn9i5qhFkndfdH4LBd3759Tf78+U23bt1M06ZNja+vrxk6dKgx5nbv4UsvvWQsFot59dVXzaRJk6wfrRFoU9ayZUuTJ08es3DhQmug3bRpk/H29jZt27ZNcYIC/mf37t2mQIEC5s033zTTpk0zBw8eNB988IEpWbKkKVOmjPnyyy9Nx44dTalSpczKlSvN/PnzzbvvvmuyZ8+e4lhuJJWQkGDGjRtnMmXKZMqUKWM6d+5s3nrrLRMcHGx8fHwIWza414Tku3u1Dx48aIKDg0337t2fyF7CtHB3oL3771BsbKzp1q2bsVgsT/RYb8IsnjiLFi0yRYsWNZs3bzbG3B5n5OHhYWbMmGHd587HaT4+PtZfxk/yeLo7var/vCPd3b0E7dq1Mzly5EgSaLds2WIsFot57bXX+Aj3Hnbv3m08PT1Nv379kr1ZmjVrlqlWrZqpXr26mThxouncubPx8vIyFSpUMA0bNrSOS0bqbNmyxbz00kumcuXKpk6dOuaDDz7gTokP4V6B1pjbvyt69uxp6tevb12OD/bxzx7auLg406NHD5M9e3azbds2R5fnUIRZPHFGjx5tgoKCjDHGzJs3z2TPnt06U/zatWvWXwoRERGmSZMmpmDBgmbv3r0Oq/dxkdJ4OWMeHGi3bdvGeLl7CA8PN3ny5DEvv/yyte3OpJk7xo0bZ3Lnzm0mTJhgjDHm6NGj5vr16yYqKird680IGOZiH/daYeedd94xrq6urLDzkB70pv9OoB0wYIDp0aOHyZIlC3NnjDEWY1K47ySQQaxevVrr1q1TYmKiatasqcaNG2vcuHHasWOHXnzxRb300kv68ssv9eabb0qS5s+fr927d6tPnz7y8vLSX3/9pVdeeUXnzp3T/v37lTlzZgd/R47z559/qkOHDsqVK5f69euX5I50CQkJ1lvTtm/fXr/99pu+++47BQcHK0uWLI4q+bF38uRJtWnTRgUKFFDfvn1Vu3Zt6zZz112/6tSpo7x582rhwoVJrjVsd/d1vftr2O7o0aPq1auXjDH68MMP9euvv2rMmDHasGGDqlSp4ujynEZcXJzi4+NTfTvvn376SR06dJAkbd++nWstiTCLDGvSpEn66KOPVKlSJR05ckTGGE2aNEkFChRQpUqVJElTp05Vp06dJEkxMTFq1aqVfH19NXbsWOutac+cOaOEhAQVKVLEYd/L4+LuP14DBw60BlpjjBITE60h685tVDdt2qRs2bI5rF5ncPc1HTBggDXQ3h206tevr0KFCmnGjBmOLBVI5ujRowoNDdWGDRsUHR2tTZs26ZlnnnF0WU7j0KFDGjhwoE6fPq3ChQtrwIABqlSp0gPfZC1ZskSlSpVSmTJl0qnSxxs3kkeGNGnSJL3zzjv697//rZUrV2ratGmKiorSzJkzVaFCBX3//fdydXVVZGSktmzZos2bN6tVq1Y6d+6cxowZIxcXFyUmJkqSChYsSJD9f35+fvr2229lsVj0ySefaMOGDZIki8UiV1dXxcTEqH///qpVq5YWLFhAkE2Fu6/pp59+muSaJiYmKiIiQlmyZFGjRo0k3Q65wOPCz89PX331lerUqaMdO3YQZG2we/du1apVSx4eHmrUqJE2b96snj176sqVKw98bbNmzQiyd3PE2AYgLa1evdpYLBYzZMiQJO0FCxY0tWrVMlevXjUXL140c+bMMXny5DGFCxc2FStWNEFBQdZVIhhXd38PuiMdM+xtd/c1XbdunbX9gw8+MJUqVTKnT592YHXA/bHCjm327NljsmfPbj766CNr25gxY4zFYjFz585Nsi+TZx+MYQbIcI4ePaquXbvK29tbAwcOVEBAgFq3bq0lS5aoUaNGunr1qry8vPTyyy/L29tbBQsWVKFChZQ/f365uLjo1q1bypQpk6O/jcce4+Xs7+5rOmzYMK1cuVKffPKJ1q9fbx0aA8C5xcXFqWbNmjp+/LjOnTsnNzc3SVLv3r01ZswYTZ06VaVKlVKtWrUUHx//RM/VSC3CLDKkO6HA1dVVV69eVUxMjKZOnaoyZcpo/fr1Onz4sL744gtFR0frlVde0ZgxYyRJiYmJ1rGyeDDGy9nfnWu6detWXb58WZs2bZK/v7+jywJgR5s2bVLLli1Vr149zZ07V1988YWGDh2qJk2aKG/evFqyZImKFCmiQoUKKSQkRAEBASpWrJijy35sEWaRYR09elRvv/22tm3bpgkTJqhNmzZJtl+9elW7du1S7dq1mR3+CA4fPqz3339fn3/+ucqVK+focjIErimQ8W3ZskVBQUHKnTu3dU7HnbHxMTExmj59upYtW6Zdu3Zp8+bNKliwoIMrfnwRZpGhHT9+XO+8845cXFz00UcfWWeK/3MoAcsdPRo+CrM/rimQ8dz5W2P+f7WSbdu2KSQkRD4+Plq7dq3c3d2TfUJ4+fJleXt7O7Dqxx+fpyJDK1mypMaMGSNjjD777DPrTPF/joklyD4aQpf9cU2BjOHQoUPq37+/Tp06ZQ2pFotFxhhVrVpVs2fP1pEjR/Tqq68qKirKus+dFXVy5szpqNKdBj2zeCIcPXpU7777rs6dO6fJkyerYsWKji4JAJDBxcfHq1atWvrjjz9UqlQptWjRQtWqVdPLL7+cZL8tW7bohRdeUFBQkL7//nt5eXk5qGLnRJjFE+PgwYOaNGmSvvzySyZ5AQDSxZdffqlMmTKpfPny2rBhg7799ls1bdpUNWrU0FtvvWW9QcLmzZtVs2ZNdezYUVOnTuXudDYgzOKJxKoFAID0sGbNGrVo0UJhYWEKCAjQ2bNnNWHCBI0YMUIVKlRQ165dVbduXZUuXVrbt29XtmzZVLp0aUeX7VT4a44nEkEWAJAennvuOXXv3l2jR4/WzZs3VaBAAR08eFBFixZVmTJlNGPGDFWoUEEjR46Uv78/QfYhsDI8AABAGqpevbpGjRolNzc3vf7661qzZo3CwsJUrlw5HT58WCtWrNDzzz/v6DKdFsMMAAAA0li9evW0fv165c+fX8uWLeOufnbEZ60AAABp5E6f4QcffKBSpUpp7NixqlSpkuhLtB/CLAAAQBq5syqBv7+/EhMTtX379iTteHSEWQAAgDSWL18+DR48WF9//bW2bt3q6HIyFMIsAABAOqhfv76qVq2qggULOrqUDIUJYAAAAOnk5s2b8vDwcHQZGQphFgAAAE6LYQYAAABwWoRZAAAAOC3CLAAAAJwWYRYAAABOizALAAAAp0WYBQAAgNMizAIAAMBpEWYBAADgtAizAAAAcFqEWQAAADit/wPzvfvyNKtonQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.arange(len(multi_performance))\n",
    "width = 0.3\n",
    "\n",
    "metric_name = 'mean_absolute_error'\n",
    "metric_index = lstm_model.metrics_names.index('mean_absolute_error')\n",
    "val_mae = [v[metric_index] for v in multi_val_performance.values()]\n",
    "test_mae = [v[metric_index] for v in multi_performance.values()]\n",
    "\n",
    "plt.bar(x - 0.17, val_mae, width, label='Validation')\n",
    "plt.bar(x + 0.17, test_mae, width, label='Test')\n",
    "plt.xticks(ticks=x, labels=multi_performance.keys(),\n",
    "           rotation=45)\n",
    "plt.ylabel(f'MAE (average over all times and outputs)')\n",
    "_ = plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Zq3hUsedCEmJ"
   },
   "source": [
    "이 튜토리얼의 전반부에서 소개한 다중 출력 모델에 대한 메트릭은 모든 출력 특성에 평균화된 성능을 보여줍니다. 이러한 성능은 유사하지만 출력 타임스텝에 걸쳐서도 평균화됩니다. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-14T23:16:58.214652Z",
     "iopub.status.busy": "2022-12-14T23:16:58.214037Z",
     "iopub.status.idle": "2022-12-14T23:16:58.218380Z",
     "shell.execute_reply": "2022-12-14T23:16:58.217666Z"
    },
    "id": "jKq3eAIvH4Db"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Last    : 0.5157\n",
      "Repeat  : 0.3774\n",
      "Linear  : 0.2981\n",
      "Dense   : 0.2784\n",
      "Conv    : 0.2726\n",
      "LSTM    : 0.2759\n",
      "AR LSTM : 0.2920\n"
     ]
    }
   ],
   "source": [
    "for name, value in multi_performance.items():\n",
    "  print(f'{name:8s}: {value[1]:0.4f}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "MpBFwfnaHP23"
   },
   "source": [
    "밀집 모델에서 컨볼루션 및 반복 모델로 이동하여 얻은 이득은 몇 퍼센트(있다고 하더라도)에 불과하며 자기 회귀 모델의 성능은 분명히 더 나빴습니다. 따라서 이러한 더 복잡한 접근 방법은 **이** 문제에서는 가치가 없을 수도 있지만 시도해 보기 전에는 알 수 있는 방법이 없었으며 이러한 모델은 **다른 특정** 문제에 도움이 될 수 있습니다."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "pOzaIRYBhqwg"
   },
   "source": [
    "## 다음 단계\n",
    "\n",
    "이 튜토리얼에서는 TensorFlow를 사용한 시계열 예측에 대해 간단히 소개했습니다.\n",
    "\n",
    "자세한 내용은 다음을 참조하세요.\n",
    "\n",
    "- <a href=\"https://www.oreilly.com/library/view/hands-on-machine-learning/9781492032632/\" class=\"external\">Scikit-Learn, Keras 및 TensorFlow를 이용한 머신러닝 실무</a>(2차 개정 버전), 챕터 15\n",
    "- [Python을 이용한 딥러닝](https://www.manning.com/books/deep-learning-with-python) 챕터 6\n",
    "- <a href=\"https://www.udacity.com/course/intro-to-tensorflow-for-deep-learning--ud187\" class=\"external\">Udacity의 딥러닝을 위한 TensorFlow 소개</a>(<a href=\"https://github.com/tensorflow/examples/tree/master/courses/udacity_intro_to_tensorflow_for_deep_learning\" class=\"external\">연습 노트북</a> 포함)의 레슨 8.\n",
    "\n",
    "또한 TensorFlow에서 어떤 <a href=\"https://otexts.com/fpp2/index.html\" class=\"external\">클래식 시계열 모델</a>이든 구현할 수 있다는 점을 기억하세요. 이 튜토리얼에서는 TensdorFlow의 내장 기능에 초점을 맞추었습니다.\n"
   ]
  }
 ],
 "metadata": {
  "accelerator": "GPU",
  "colab": {
   "collapsed_sections": [],
   "name": "time_series.ipynb",
   "toc_visible": true
  },
  "kernelspec": {
   "display_name": "Python 3",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.16"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}