tf.keras.saving.custom_object_scope
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Exposes custom classes/functions to Keras deserialization internals.
tf.keras.saving.custom_object_scope(
*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).
Example:
Consider a custom regularizer my_regularizer
:
layer = Dense(3, kernel_regularizer=my_regularizer)
# Config contains a reference to `my_regularizer`
config = layer.get_config()
...
# Later:
with custom_object_scope({'my_regularizer': my_regularizer}):
layer = Dense.from_config(config)
Args |
*args
|
Dictionary or dictionaries of {name: object} pairs.
|
Methods
__enter__
View source
__enter__()
__exit__
View source
__exit__(
*args, **kwargs
)
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Last updated 2023-10-06 UTC.
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