tf.nn.silu
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Computes the SiLU or Swish activation function: x * sigmoid(x).
View aliases
Main aliases
tf.nn.swish
Compat aliases for migration
See
Migration guide for
more details.
tf.compat.v1.nn.silu, tf.compat.v1.nn.swish
tf.nn.silu(
features
)
The SiLU activation function was introduced in "Gaussian Error Linear Units
(GELUs)" Hendrycks et al. 2016 and
"Sigmoid-Weighted Linear Units for Neural Network Function Approximation in
Reinforcement Learning"
Elfwing et al. 2017 and was independently
discovered (and called swish) in "Searching for Activation Functions"
Ramachandran et al. 2017
Args |
|---|
features
|
A Tensor representing preactivation values.
|
name
|
A name for the operation (optional).
|
Returns |
|---|
|
The activation value.
|
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Last updated 2021-02-18 UTC.
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View source on GitHub