Coverage for /pythoncovmergedfiles/medio/medio/usr/local/lib/python3.8/site-packages/tensorflow/lite/python/analyzer.py: 38%
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« prev ^ index » next coverage.py v7.4.0, created at 2024-01-03 07:57 +0000
1# Copyright 2021 The TensorFlow Authors. All Rights Reserved.
2#
3# Licensed under the Apache License, Version 2.0 (the "License");
4# you may not use this file except in compliance with the License.
5# You may obtain a copy of the License at
6#
7# http://www.apache.org/licenses/LICENSE-2.0
8#
9# Unless required by applicable law or agreed to in writing, software
10# distributed under the License is distributed on an "AS IS" BASIS,
11# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12# See the License for the specific language governing permissions and
13# limitations under the License.
14# ==============================================================================
15"""This tool analyzes a TensorFlow Lite graph."""
17import os
19# pylint: disable=g-import-not-at-top
20if not os.path.splitext(__file__)[0].endswith(
21 os.path.join("tflite_runtime", "analyzer")):
22 # This file is part of tensorflow package.
23 from tensorflow.lite.python import wrap_toco
24 from tensorflow.lite.python.analyzer_wrapper import _pywrap_analyzer_wrapper as _analyzer_wrapper
25 from tensorflow.python.util.tf_export import tf_export as _tf_export
26else:
27 # This file is part of tflite_runtime package.
28 from tflite_runtime import _pywrap_analyzer_wrapper as _analyzer_wrapper
30 def _tf_export(*x, **kwargs):
31 del x, kwargs
32 return lambda x: x
35@_tf_export("lite.experimental.Analyzer")
36class ModelAnalyzer():
37 """Provides a collection of TFLite model analyzer tools.
39 Example:
41 ```python
42 model = tf.keras.applications.MobileNetV3Large()
43 fb_model = tf.lite.TFLiteConverterV2.from_keras_model(model).convert()
44 tf.lite.experimental.Analyzer.analyze(model_content=fb_model)
45 # === TFLite ModelAnalyzer ===
46 #
47 # Your TFLite model has ‘1’ subgraph(s). In the subgraph description below,
48 # T# represents the Tensor numbers. For example, in Subgraph#0, the MUL op
49 # takes tensor #0 and tensor #19 as input and produces tensor #136 as output.
50 #
51 # Subgraph#0 main(T#0) -> [T#263]
52 # Op#0 MUL(T#0, T#19) -> [T#136]
53 # Op#1 ADD(T#136, T#18) -> [T#137]
54 # Op#2 CONV_2D(T#137, T#44, T#93) -> [T#138]
55 # Op#3 HARD_SWISH(T#138) -> [T#139]
56 # Op#4 DEPTHWISE_CONV_2D(T#139, T#94, T#24) -> [T#140]
57 # ...
58 ```
60 WARNING: Experimental interface, subject to change.
61 """
63 @staticmethod
64 def analyze(model_path=None,
65 model_content=None,
66 gpu_compatibility=False,
67 **kwargs):
68 """Analyzes the given tflite_model with dumping model structure.
70 This tool provides a way to understand users' TFLite flatbuffer model by
71 dumping internal graph structure. It also provides additional features
72 like checking GPU delegate compatibility.
74 WARNING: Experimental interface, subject to change.
75 The output format is not guaranteed to stay stable, so don't
76 write scripts to this.
78 Args:
79 model_path: TFLite flatbuffer model path.
80 model_content: TFLite flatbuffer model object.
81 gpu_compatibility: Whether to check GPU delegate compatibility.
82 **kwargs: Experimental keyword arguments to analyze API.
84 Returns:
85 Print analyzed report via console output.
86 """
87 if not model_path and not model_content:
88 raise ValueError("neither `model_path` nor `model_content` is provided")
89 if model_path:
90 print(f"=== {model_path} ===\n")
91 tflite_model = model_path
92 input_is_filepath = True
93 else:
94 print("=== TFLite ModelAnalyzer ===\n")
95 tflite_model = model_content
96 input_is_filepath = False
98 if kwargs.get("experimental_use_mlir", False):
99 print(
100 wrap_toco.wrapped_flat_buffer_file_to_mlir(tflite_model,
101 input_is_filepath))
102 else:
103 print(
104 _analyzer_wrapper.ModelAnalyzer(tflite_model, input_is_filepath,
105 gpu_compatibility))