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Exposes custom classes/functions to Keras deserialization internals.
tf.keras.utils.CustomObjectScope( *args )
Under a scope with custom_object_scope(objects_dict)
, Keras methods such as tf.keras.models.load_model
or tf.keras.models.model_from_config
will be able to deserialize any custom object referenced by a saved config (e.g. a custom layer or metric).
Consider a custom regularizer my_regularizer
:
layer = Dense(3, kernel_regularizer=my_regularizer) config = layer.get_config() # Config contains a reference to `my_regularizer` ... # Later: with custom_object_scope({'my_regularizer': my_regularizer}): layer = Dense.from_config(config)
Arguments | |
---|---|
*args | Dictionary or dictionaries of {name: object} pairs. |
__enter__
__enter__()
__exit__
__exit__( *args, **kwargs )
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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.4/api_docs/python/tf/keras/utils/CustomObjectScope