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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"""Options for saving SavedModels."""
16
17from __future__ import absolute_import
18from __future__ import division
19from __future__ import print_function
20
21from tensorflow.python.util.tf_export import tf_export
22
23
24@tf_export("saved_model.LoadOptions", v1=[])
25class LoadOptions(object):
26  """Options for loading a SavedModel.
27
28  This function may be used in the `options` argument in functions that
29  load a SavedModel (`tf.saved_model.load`, `tf.keras.models.load_model`).
30  """
31
32  # Define object attributes in __slots__ for improved memory and performance.
33  __slots__ = ("allow_partial_checkpoint", "experimental_io_device",
34               "experimental_skip_checkpoint")
35
36  def __init__(self,
37               allow_partial_checkpoint=False,
38               experimental_io_device=None,
39               experimental_skip_checkpoint=False):
40    """Creates an object that stores options for SavedModel loading.
41
42    *When to set `allow_partial_checkpoint=True`?*
43
44    This can be used when loading a Keras model (`tf.keras.models.load_model`)
45    with custom objects. When new variables are added to the custom object
46    class, loading will fail the assertion check that all loaded variables have
47    been restored, because the SavedModel checkpoint only contains the variables
48    that were in original the custom object.
49    See the following example:
50
51    ```
52    class Custom(tf.keras.Model):
53      def __init__(self):
54        super(Custom, self).__init__()
55        self.v = tf.Variable(...)
56
57      def call(self, inputs):
58        return ...
59
60    model = Custom()
61    model.save(...)
62    ```
63
64    After saving, say that `Custom` is updated to include an additional
65    variable.
66
67    ```
68    class Custom(tf.keras.Model):
69      def __init__(self):
70        super(Custom, self).__init__()
71        self.v = tf.Variable(...)
72        self.w = tf.Variable(...)
73
74      def call(self, inputs):
75        return ...
76    ```
77
78    `tf.keras.models.load_model(path, custom_objects={'Custom': Custom})` fails
79    to load since `Custom.w` does not exist in the SavedModel checkpoint. To
80    acknowledge that there are variables that are not restored from the
81    checkpoint and successfully load the model, call:
82
83    ```
84    tf.keras.models.load_model(
85      path, custom_objects={'Custom': Custom},
86      options=tf.saved_model.LoadOptions(allow_partial_checkpoint=True))
87    ```
88
89    Args:
90      allow_partial_checkpoint: bool. Defaults to `False`. When enabled, allows
91        the SavedModel checkpoint to not entirely match the loaded object.
92      experimental_io_device: string. Applies in a distributed setting.
93        Tensorflow device to use to access the filesystem. If `None` (default)
94        then for each variable the filesystem is accessed from the CPU:0 device
95        of the host where that variable is assigned. If specified, the
96        filesystem is instead accessed from that device for all variables.
97        This is for example useful if you want to load from a local directory,
98        such as "/tmp" when running in a distributed setting. In that case
99        pass a device for the host where the "/tmp" directory is accessible.
100      experimental_skip_checkpoint: bool. Defaults to `False`. If set to `True`,
101        checkpoints will not be restored. Note that this in the majority of
102        cases will generate an unusable model.
103
104    Example:
105
106      load_options = tf.saved_model.LoadOptions(experimental_io_device=
107        '/job:localhost')
108      restoredmodel = tf.keras.models.load_model(saved_model_path,
109                                                 options=load_options)
110
111    """
112    self.experimental_io_device = experimental_io_device
113    self.allow_partial_checkpoint = allow_partial_checkpoint
114    self.experimental_skip_checkpoint = experimental_skip_checkpoint
115