142 lines
5.0 KiB
Python
142 lines
5.0 KiB
Python
# Copyright 2019 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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"""Helper classes that list&validate all attributes to serialize to
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SavedModel."""
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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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import abc
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from keras.saving.legacy.saved_model import json_utils
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from keras.saving.legacy.saved_model import utils
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class SavedModelSaver(object, metaclass=abc.ABCMeta):
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"""Saver defining the methods and properties used to serialize Keras
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objects."""
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def __init__(self, obj):
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self.obj = obj
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@abc.abstractproperty
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def object_identifier(self):
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"""String stored in object identifier field in the SavedModel proto.
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Returns:
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A string with the object identifier, which is used at load time.
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"""
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raise NotImplementedError
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@property
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def tracking_metadata(self):
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"""String stored in metadata field in the SavedModel proto.
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Returns:
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A serialized JSON storing information necessary for recreating this
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layer.
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"""
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# TODO(kathywu): check that serialized JSON can be loaded (e.g., if an
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# object is in the python property)
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return json_utils.Encoder().encode(self.python_properties)
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def trackable_children(self, serialization_cache):
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"""Lists all Trackable children connected to this object."""
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if not utils.should_save_traces():
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return {}
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children = self.objects_to_serialize(serialization_cache)
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children.update(self.functions_to_serialize(serialization_cache))
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return children
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@abc.abstractproperty
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def python_properties(self):
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"""Returns dictionary of python properties to save in the metadata.
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This dictionary must be serializable and deserializable to/from JSON.
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When loading, the items in this dict are used to initialize the object
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and define attributes in the revived object.
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"""
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raise NotImplementedError
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@abc.abstractmethod
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def objects_to_serialize(self, serialization_cache):
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"""Returns dictionary of extra checkpointable objects to serialize.
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See `functions_to_serialize` for an explanation of this function's
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effects.
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Args:
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serialization_cache: Dictionary passed to all objects in the same
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object graph during serialization.
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Returns:
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A dictionary mapping attribute names to checkpointable objects.
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"""
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raise NotImplementedError
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@abc.abstractmethod
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def functions_to_serialize(self, serialization_cache):
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"""Returns extra functions to include when serializing a Keras object.
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Normally, when calling exporting an object to SavedModel, only the
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functions and objects defined by the user are saved. For example:
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```
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obj = tf.Module()
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obj.v = tf.Variable(1.)
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@tf.function
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def foo(...): ...
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obj.foo = foo
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w = tf.Variable(1.)
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tf.saved_model.save(obj, 'path/to/saved/model')
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loaded = tf.saved_model.load('path/to/saved/model')
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loaded.v # Variable with the same value as obj.v
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loaded.foo # Equivalent to obj.foo
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loaded.w # AttributeError
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```
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Assigning trackable objects to attributes creates a graph, which is used
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for both checkpointing and SavedModel serialization.
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When the graph generated from attribute tracking is insufficient, extra
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objects and functions may be added at serialization time. For example,
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most models do not have their call function wrapped with a @tf.function
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decorator. This results in `model.call` not being saved. Since Keras
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objects should be revivable from the SavedModel format, the call
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function is added as an extra function to serialize.
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This function and `objects_to_serialize` is called multiple times when
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exporting to SavedModel. Please use the cache to avoid generating new
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functions and objects. A fresh cache is created for each SavedModel
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export.
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Args:
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serialization_cache: Dictionary passed to all objects in the same
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object graph during serialization.
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Returns:
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A dictionary mapping attribute names to `Function` or
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`ConcreteFunction`.
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"""
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raise NotImplementedError
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