tensorflow::
  #include <nn_ops.h>
  Computes scaled exponential linear: scale * alpha * (exp(features) - 1)
Summary
if < 0, scale * features otherwise.
To be used together with `initializer = tf.variance_scaling_initializer(factor=1.0, mode='FAN_IN'). For correct dropout, usetf.contrib.nn.alpha_dropout`.
See Self-Normalizing Neural Networks
Arguments:
- scope: A Scope object
Returns:
- Output: The activations tensor.
| Constructors and Destructors | |
|---|---|
| Selu(const ::tensorflow::Scope & scope, ::tensorflow::Input features) | 
| Public attributes | |
|---|---|
| activations | |
| operation | |
| Public functions | |
|---|---|
| node() const  | ::tensorflow::Node * | 
| operator::tensorflow::Input() const  | 
         | 
| operator::tensorflow::Output() const  | 
         | 
Public attributes
activations
::tensorflow::Output activations
operation
Operation operation
Public functions
Selu
Selu( const ::tensorflow::Scope & scope, ::tensorflow::Input features )
node
::tensorflow::Node * node() const
operator::tensorflow::Input
operator::tensorflow::Input() const
operator::tensorflow::Output
operator::tensorflow::Output() const