tf.keras.layers.deserialize
Instantiates a layer from a config dictionary.
tf.keras.layers.deserialize(
config, custom_objects=None
)
| Args |
|---|
config | dict of the form {'class_name': str, 'config': dict} |
custom_objects | dict mapping class names (or function names) of custom (non-Keras) objects to class/functions |
| Returns |
|---|
| Layer instance (may be Model, Sequential, Network, Layer...) |
Example:
# Configuration of Dense(32, activation='relu')
config = {
'class_name': 'Dense',
'config': {
'activation': 'relu',
'activity_regularizer': None,
'bias_constraint': None,
'bias_initializer': {'class_name': 'Zeros', 'config': {} },
'bias_regularizer': None,
'dtype': 'float32',
'kernel_constraint': None,
'kernel_initializer': {'class_name': 'GlorotUniform',
'config': {'seed': None} },
'kernel_regularizer': None,
'name': 'dense',
'trainable': True,
'units': 32,
'use_bias': True
}
}
dense_layer = tf.keras.layers.deserialize(config)