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1# Copyright 2015 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"""Types for specifying saving and loading behavior."""
16
17
18class SaveSpec:
19  """Class used to describe tensor slices that need to be saved."""
20
21  def __init__(self, tensor, slice_spec, name, dtype=None, device=None):
22    """Creates a `SaveSpec` object.
23
24    Args:
25      tensor: the tensor to save or callable that produces a tensor to save.
26        If the value is `None`, the `SaveSpec` is ignored.
27      slice_spec: the slice to be saved. See `Variable.SaveSliceInfo`.
28      name: the name to save the tensor under.
29      dtype: The data type of the Tensor. Required if `tensor` is callable.
30        Used for error checking in the restore op.
31      device: The device generating and consuming this tensor. Required if
32        `tensor` is callable. Used to group objects to save by device.
33    """
34    self._tensor = tensor
35    self.slice_spec = slice_spec
36    self.name = name
37    if callable(self._tensor):
38      if dtype is None or device is None:
39        raise AssertionError(
40            "When passing a callable `tensor` to a SaveSpec, an explicit "
41            "dtype and device must be provided.")
42      self.dtype = dtype
43      self.device = device
44    else:
45      self.dtype = tensor.dtype
46      if device is not None:
47        self.device = device
48      else:
49        self.device = tensor.device
50
51  @property
52  def tensor(self):
53    return self._tensor() if callable(self._tensor) else self._tensor
54
55
56class SaveableObject:
57  """Base class for saving and restoring saveable objects."""
58
59  def __init__(self, op, specs, name):
60    """Creates a `SaveableObject` object.
61
62    Args:
63      op: the "producer" object that this class wraps; it produces a list of
64        tensors to save.  E.g., a "Variable" object saving its backing tensor.
65      specs: a list of SaveSpec, each element of which describes one tensor to
66        save under this object. All Tensors must be on the same device.
67      name: the name to save the object under.
68    """
69    self.op = op
70    self.specs = specs
71    self.name = name
72
73  @property
74  def device(self):
75    """The device for SaveSpec Tensors."""
76    return self.specs[0].device
77
78  def restore(self, restored_tensors, restored_shapes):
79    """Restores this object from 'restored_tensors'.
80
81    Args:
82      restored_tensors: the tensors that were loaded from a checkpoint
83      restored_shapes: the shapes this object should conform to after
84        restore, or None.
85
86    Returns:
87      An operation that restores the state of the object.
88
89    Raises:
90      ValueError: If the object cannot be restored using the provided
91        parameters.
92    """
93    # pylint: disable=unused-argument
94    raise ValueError("Calling an abstract method.")
95