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1# Copyright 2020 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"""Config functions for TF NumPy."""
17from tensorflow.python.framework import ops
18from tensorflow.python.ops.numpy_ops import np_dtypes
19from tensorflow.python.ops.numpy_ops import np_export
20from tensorflow.python.ops.numpy_ops import np_math_ops
23@np_export.np_export("experimental_enable_numpy_behavior")
24def enable_numpy_behavior(prefer_float32=False):
25 """Enable NumPy behavior on Tensors.
27 Enabling NumPy behavior has three effects:
28 * It adds to `tf.Tensor` some common NumPy methods such as `T`,
29 `reshape` and `ravel`.
30 * It changes dtype promotion in `tf.Tensor` operators to be
31 compatible with NumPy. For example,
32 `tf.ones([], tf.int32) + tf.ones([], tf.float32)` used to throw a
33 "dtype incompatible" error, but after this it will return a
34 float64 tensor (obeying NumPy's promotion rules).
35 * It enhances `tf.Tensor`'s indexing capability to be on par with
36 [NumPy's](https://numpy.org/doc/stable/reference/arrays.indexing.html).
38 Args:
39 prefer_float32: Controls whether dtype inference will use float32
40 for Python floats, or float64 (the default and the
41 NumPy-compatible behavior).
42 """
43 ops.enable_numpy_style_type_promotion()
44 ops.enable_numpy_style_slicing()
45 np_math_ops.enable_numpy_methods_on_tensor()
46 np_dtypes.set_prefer_float32(prefer_float32)