Layer that applies an update to the cost function based input activity.
Inherits From: Layer, Operation
tf.keras.layers.ActivityRegularization(
l1=0.0, l2=0.0, **kwargs
)
| Args | |
|---|---|
l1 | L1 regularization factor (positive float). |
l2 | L2 regularization factor (positive float). |
| Input shape | |
|---|---|
Arbitrary. Use the keyword argument input_shape (tuple of integers, does not include the samples axis) when using this layer as the first layer in a model. |
| Output shape | |
|---|---|
| Same shape as input. |
| Attributes | |
|---|---|
input | Retrieves the input tensor(s) of a symbolic operation. Only returns the tensor(s) corresponding to the first time the operation was called. |
output | Retrieves the output tensor(s) of a layer. Only returns the tensor(s) corresponding to the first time the operation was called. |
from_config@classmethod
from_config(
config
)
Creates a layer from its config.
This method is the reverse of get_config, capable of instantiating the same layer from the config dictionary. It does not handle layer connectivity (handled by Network), nor weights (handled by set_weights).
| Args | |
|---|---|
config | A Python dictionary, typically the output of get_config. |
| Returns | |
|---|---|
| A layer instance. |
symbolic_callsymbolic_call(
*args, **kwargs
)
© 2022 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 4.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/keras/layers/ActivityRegularization