100 lines
3.5 KiB
Python
100 lines
3.5 KiB
Python
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# 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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"""Types for specifying saving and loading behavior."""
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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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class SaveSpec(object):
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"""Class used to describe tensor slices that need to be saved."""
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def __init__(self, tensor, slice_spec, name, dtype=None):
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"""Creates a `SaveSpec` object.
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Args:
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tensor: the tensor to save or callable that produces a tensor to save.
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slice_spec: the slice to be saved. See `Variable.SaveSliceInfo`.
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name: the name to save the tensor under.
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dtype: The data type of the Tensor. Required if `tensor` is callable.
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Used for error checking in the restore op.
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"""
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self._tensor = tensor
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self.slice_spec = slice_spec
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self.name = name
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if callable(self._tensor):
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if dtype is None:
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raise AssertionError(
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"When passing a callable `tensor` to a SaveSpec, an explicit "
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"dtype must be provided.")
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self.dtype = dtype
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else:
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self.dtype = tensor.dtype
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@property
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def tensor(self):
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return self._tensor() if callable(self._tensor) else self._tensor
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class SaveableObject(object):
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"""Base class for saving and restoring saveable objects."""
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def __init__(self, op, specs, name):
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"""Creates a `SaveableObject` object.
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Args:
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op: the "producer" object that this class wraps; it produces a list of
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tensors to save. E.g., a "Variable" object saving its backing tensor.
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specs: a list of SaveSpec, each element of which describes one tensor to
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save under this object. All Tensors must be on the same device.
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name: the name to save the object under.
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"""
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self.op = op
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self.specs = specs
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self.name = name
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self._device = None
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@property
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def device(self):
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"""The device for SaveSpec Tensors."""
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# Note that SaveSpec.tensor runs Tensor-gathering ops when executing
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# eagerly, making this call potentially very expensive.
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#
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# TODO(allenl): Consider another way to gather device information. Lower
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# priority since this property isn't part of the normal save()/restore()
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# workflow, but does come up when some alternative builders are passed to
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# the Saver.
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if self._device is None:
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self._device = self.specs[0].tensor.device
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return self._device
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def restore(self, restored_tensors, restored_shapes):
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"""Restores this object from 'restored_tensors'.
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Args:
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restored_tensors: the tensors that were loaded from a checkpoint
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restored_shapes: the shapes this object should conform to after
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restore, or None.
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Returns:
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An operation that restores the state of the object.
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Raises:
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ValueError: If the object cannot be restored using the provided
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parameters.
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"""
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# pylint: disable=unused-argument
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raise ValueError("Calling an abstract method.")
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