tf.keras.layers.ActivityRegularization | TensorFlow v2.16.1 (original) (raw)
tf.keras.layers.ActivityRegularization
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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. |
Methods
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_call
symbolic_call(
*args, **kwargs
)
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Last updated 2024-06-07 UTC.