tf.keras.layers.LeakyReLU

Leaky version of a Rectified Linear Unit activation layer.

Inherits From: Layer, Operation

tf.keras.layers.LeakyReLU( negative_slope=0.3, **kwargs )

Used in the notebooks

Used in the guide Used in the tutorials

This layer allows a small gradient when the unit is not active.

Formula:

f(x) = alpha * x if x < 0 f(x) = x if x >= 0

Example:

leaky_relu_layer = LeakyReLU(negative_slope=0.5) input = np.array([-10, -5, 0.0, 5, 10]) result = leaky_relu_layer(input) # result = [-5. , -2.5, 0. , 5. , 10.]

negative_slope Float >= 0.0. Negative slope coefficient. Defaults to 0.3.
**kwargs Base layer keyword arguments, such as name and dtype.

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 )