67fb07ba9f
A new class LoadOptions is created similar to the existing SavedOptions. The option experimental_io_device is the only option added at this time and usd to set the io_device when loading a SavedModel for distributed training. PiperOrigin-RevId: 316557681 Change-Id: If3f1eae18b09085ff11dc8a6882fabcb18f5f48e
58 lines
2.3 KiB
Python
58 lines
2.3 KiB
Python
# Copyright 2020 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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"""Options for saving SavedModels."""
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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from tensorflow.python.util.tf_export import tf_export
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@tf_export("saved_model.LoadOptions", v1=[])
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class LoadOptions(object):
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"""Options for loading a SavedModel.
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This function may be used in the `options` argument in functions that
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load a SavedModel (`tf.saved_model.load`, `tf.keras.models.load_model`).
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"""
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# Define object attributes in __slots__ for improved memory and performance.
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__slots__ = ("experimental_io_device",)
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def __init__(self,
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experimental_io_device=None):
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"""Creates an object that stores options for SavedModel loading.
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Args:
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experimental_io_device: string. Applies in a distributed setting.
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Tensorflow device to use to access the filesystem. If `None` (default)
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then for each variable the filesystem is accessed from the CPU:0 device
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of the host where that variable is assigned. If specified, the
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filesystem is instead accessed from that device for all variables.
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This is for example useful if you want to load from a local directory,
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such as "/tmp" when running in a distributed setting. In that case
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pass a device for the host where the "/tmp" directory is accessible.
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Example:
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load_options = tf.saved_model.LoadOptions(experimental_io_device=
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'/job:localhost')
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restoredmodel = tf.keras.models.load_model(saved_model_path,
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options=load_options)
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"""
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self.experimental_io_device = experimental_io_device
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