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 tensorflow.python.saved_model import save_options 18from tensorflow.python.util.tf_export import tf_export 19 20 21@tf_export("saved_model.LoadOptions", v1=[]) 22class LoadOptions(object): 23 """Options for loading a SavedModel. 24 25 This function may be used in the `options` argument in functions that 26 load a SavedModel (`tf.saved_model.load`, `tf.keras.models.load_model`). 27 """ 28 29 # Define object attributes in __slots__ for improved memory and performance. 30 __slots__ = ("allow_partial_checkpoint", "experimental_io_device", 31 "experimental_skip_checkpoint", "experimental_variable_policy") 32 33 def __init__(self, 34 allow_partial_checkpoint=False, 35 experimental_io_device=None, 36 experimental_skip_checkpoint=False, 37 experimental_variable_policy=None): 38 """Creates an object that stores options for SavedModel loading. 39 40 *When to set `allow_partial_checkpoint=True`?* 41 42 This can be used when loading a Keras model (`tf.keras.models.load_model`) 43 with custom objects. When new variables are added to the custom object 44 class, loading will fail the assertion check that all loaded variables have 45 been restored, because the SavedModel checkpoint only contains the variables 46 that were in original the custom object. 47 See the following example: 48 49 ``` 50 class Custom(tf.keras.Model): 51 def __init__(self): 52 super(Custom, self).__init__() 53 self.v = tf.Variable(...) 54 55 def call(self, inputs): 56 return ... 57 58 model = Custom() 59 model.save(...) 60 ``` 61 62 After saving, say that `Custom` is updated to include an additional 63 variable. 64 65 ``` 66 class Custom(tf.keras.Model): 67 def __init__(self): 68 super(Custom, self).__init__() 69 self.v = tf.Variable(...) 70 self.w = tf.Variable(...) 71 72 def call(self, inputs): 73 return ... 74 ``` 75 76 `tf.keras.models.load_model(path, custom_objects={'Custom': Custom})` fails 77 to load since `Custom.w` does not exist in the SavedModel checkpoint. To 78 acknowledge that there are variables that are not restored from the 79 checkpoint and successfully load the model, call: 80 81 ``` 82 tf.keras.models.load_model( 83 path, custom_objects={'Custom': Custom}, 84 options=tf.saved_model.LoadOptions(allow_partial_checkpoint=True)) 85 ``` 86 87 Args: 88 allow_partial_checkpoint: bool. Defaults to `False`. When enabled, allows 89 the SavedModel checkpoint to not entirely match the loaded object. 90 experimental_io_device: string. Applies in a distributed setting. 91 Tensorflow device to use to access the filesystem. If `None` (default) 92 then for each variable the filesystem is accessed from the CPU:0 device 93 of the host where that variable is assigned. If specified, the 94 filesystem is instead accessed from that device for all variables. 95 This is for example useful if you want to load from a local directory, 96 such as "/tmp" when running in a distributed setting. In that case 97 pass a device for the host where the "/tmp" directory is accessible. 98 experimental_skip_checkpoint: bool. Defaults to `False`. If set to `True`, 99 checkpoints will not be restored. Note that this in the majority of 100 cases will generate an unusable model. 101 experimental_variable_policy: string. The policy to apply to variables 102 when loading. This is either a `saved_model.experimental.VariablePolicy` 103 enum instance or one of its value strings (case is not important). See 104 that enum documentation for details. A value of `None` corresponds to 105 the default policy. 106 107 Example: 108 109 load_options = tf.saved_model.LoadOptions(experimental_io_device= 110 '/job:localhost') 111 restoredmodel = tf.keras.models.load_model(saved_model_path, 112 options=load_options) 113 114 """ 115 self.experimental_io_device = experimental_io_device 116 self.allow_partial_checkpoint = allow_partial_checkpoint 117 self.experimental_skip_checkpoint = experimental_skip_checkpoint 118 self.experimental_variable_policy = ( 119 save_options.VariablePolicy.from_obj(experimental_variable_policy)) 120