|TensorFlow 1 version||View source on GitHub|
Parametric Rectified Linear Unit.
Compat aliases for migration
See Migration guide for more details.
tf.keras.layers.PReLU( alpha_initializer='zeros', alpha_regularizer=None, alpha_constraint=None, shared_axes=None, **kwargs )
f(x) = alpha * x for x < 0,
f(x) = x for x >= 0,
alpha is a learned array with the same shape as x.
Arbitrary. Use the keyword argument
(tuple of integers, does not include the samples axis)
when using this layer as the first layer in a model.
Same shape as the input.
||Initializer function for the weights.|
||Regularizer for the weights.|
||Constraint for the weights.|
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