# Copyright 2015 The TensorFlow Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ==============================================================================
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"""Bring in all of the public TensorFlow interface into this module."""
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from __future__ import absolute_import as _absolute_import
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from __future__ import division as _division
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from __future__ import print_function as _print_function
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import os as _os
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import sys as _sys
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# pylint: disable=g-bad-import-order
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# API IMPORTS PLACEHOLDER
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from tensorflow.python.tools import component_api_helper as _component_api_helper
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_component_api_helper.package_hook(
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parent_package_str=__name__,
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child_package_str=('tensorboard.summary._tf.summary'),
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error_msg=(
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"Limited tf.compat.v2.summary API due to missing TensorBoard "
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"installation"))
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_component_api_helper.package_hook(
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parent_package_str=__name__,
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child_package_str=(
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'tensorflow_estimator.python.estimator.api._v2.estimator'))
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_component_api_helper.package_hook(
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parent_package_str=__name__,
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child_package_str=('tensorflow.python.keras.api._v2.keras'))
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# We would like the following to work for fully enabling 2.0 in a 1.0 install:
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#
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# import tensorflow.compat.v2 as tf
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# tf.enable_v2_behavior()
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#
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# This make this one symbol available directly.
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from tensorflow.python.compat.v2_compat import enable_v2_behavior # pylint: disable=g-import-not-at-top
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# Add module aliases
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_current_module = _sys.modules[__name__]
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if hasattr(_current_module, 'keras'):
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losses = keras.losses
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metrics = keras.metrics
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optimizers = keras.optimizers
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initializers = keras.initializers
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