tf.keras.layers.PReLU
Parametric Rectified Linear Unit.
Inherits From: Layer
, Module
View aliases
Compat aliases for migration
See
Migration guide for
more details.
`tf.compat.v1.keras.layers.PReLU`
tf.keras.layers.PReLU(
alpha_initializer='zeros',
alpha_regularizer=None,
alpha_constraint=None,
shared_axes=None,
**kwargs
)
It follows:
f(x) = alpha * x for x < 0
f(x) = x for x >= 0
where alpha
is a learned array with the same shape as x.
|
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 the input.
|
Args |
alpha_initializer
|
Initializer function for the weights.
|
alpha_regularizer
|
Regularizer for the weights.
|
alpha_constraint
|
Constraint for the weights.
|
shared_axes
|
The axes along which to share learnable
parameters for the activation function.
For example, if the incoming feature maps
are from a 2D convolution
with output shape (batch, height, width, channels) ,
and you wish to share parameters across space
so that each filter only has one set of parameters,
set shared_axes=[1, 2] .
|
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Last updated 2023-10-06 UTC.
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