activation_relu: Activation functions

In dfalbel/keras: R Interface to 'Keras'

Description

Activations functions can either be used through layer_activation(), or through the activation argument supported by all forward layers.

Usage

activation_relu(x, alpha = 0, max_value = NULL, threshold = 0)

activation_elu(x, alpha = 1)

activation_selu(x)

activation_hard_sigmoid(x)

activation_linear(x)

activation_sigmoid(x)

activation_softmax(x, axis = -1)

activation_softplus(x)

activation_softsign(x)

activation_tanh(x)

activation_exponential(x)

Arguments

x	Tensor
alpha	Alpha value
max_value	Max value
threshold	Threshold value for thresholded activation.
axis	Integer, axis along which the softmax normalization is applied

Details

• activation_selu() to be used together with the initialization "lecun_normal".

• activation_selu() to be used together with the dropout variant "AlphaDropout".

Value

Tensor with the same shape and dtype as x.

References

• activation_selu(): Self-Normalizing Neural Networks

dfalbel/keras documentation built on Nov. 27, 2019, 8:16 p.m.