tf.keras.utils.CustomObjectScope | TensorFlow v2.16.1 (original) (raw)
tf.keras.utils.CustomObjectScope
Exposes custom classes/functions to Keras deserialization internals.
View aliases
Main aliases
tf.keras.utils.custom_object_scope
tf.keras.utils.CustomObjectScope(
custom_objects
)
Under a scope with custom_object_scope(objects_dict), Keras methods such as keras.models.load_model() orkeras.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 | |
|---|---|
| custom_objects | Dictionary of {str: object} pairs, where the str key is the object name. |
Methods
__enter__
__enter__()
__exit__
__exit__(
*args, **kwargs
)
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Last updated 2024-06-07 UTC.