tf.keras.layers.Activation  |  TensorFlow v2.16.1 (original) (raw)

tf.keras.layers.Activation

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Applies an activation function to an output.

Inherits From: Layer, Operation

tf.keras.layers.Activation(
    activation, **kwargs
)

Used in the notebooks

Used in the guide Used in the tutorials
Mixed precision Ragged tensors Basic text classification Load text Classifying CIFAR-10 with XLA TFF simulations with accelerators Parametrized Quantum Circuits for Reinforcement Learning
Args
activation Activation function. It could be a callable, or the name of an activation from the keras.activations namespace.
**kwargs Base layer keyword arguments, such as name and dtype.

Example:

layer = keras.layers.Activation('relu') layer([-3.0, -1.0, 0.0, 2.0]) [0.0, 0.0, 0.0, 2.0] layer = keras.layers.Activation(keras.activations.relu) layer([-3.0, -1.0, 0.0, 2.0]) [0.0, 0.0, 0.0, 2.0]

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

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@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

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symbolic_call(
    *args, **kwargs
)