org.nd4j.linalg.activations.impl

Class ActivationELU

java.lang.Object

org.nd4j.linalg.activations.BaseActivationFunction

org.nd4j.linalg.activations.impl.ActivationELU

All Implemented Interfaces:

Serializable, IActivation

public class ActivationELU
extends BaseActivationFunction

f(x) = alpha * (exp(x) - 1.0); x < 0 = x ; x>= 0 alpha defaults to 1, if not specified

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
static double	DEFAULT_ALPHA

Constructor Summary

Constructors

Constructor and Description
ActivationELU()
ActivationELU(double alpha)

Method Summary

Modifier and Type	Method and Description
Pair<INDArray,INDArray>	backprop(INDArray in, INDArray epsilon) Backpropagate the errors through the activation function, given input z and epsilon dL/da. Returns 2 INDArrays: (a) The gradient dL/dz, calculated from dL/da, and (b) The parameter gradients dL/dW, where w is the weights in the activation function.
INDArray	getActivation(INDArray in, boolean training) Carry out activation function on the input array (usually known as 'preOut' or 'z') Implementations must overwrite "in", transform in place and return "in" Can support separate behaviour during test
String	toString()

Methods inherited from class org.nd4j.linalg.activations.BaseActivationFunction

assertShape, numParams

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Field Detail

DEFAULT_ALPHA

public static final double DEFAULT_ALPHA

See Also:

Constant Field Values

Constructor Detail

ActivationELU

public ActivationELU()

ActivationELU

public ActivationELU(double alpha)

Method Detail

getActivation

public INDArray getActivation(INDArray in,
                              boolean training)

Description copied from interface: IActivation

Carry out activation function on the input array (usually known as 'preOut' or 'z') Implementations must overwrite "in", transform in place and return "in" Can support separate behaviour during test

Parameters:

in - input array.

training - true when training.

Returns:

transformed activation

backprop

public Pair<INDArray,INDArray> backprop(INDArray in,
                                        INDArray epsilon)

Description copied from interface: IActivation

Backpropagate the errors through the activation function, given input z and epsilon dL/da.
Returns 2 INDArrays:
(a) The gradient dL/dz, calculated from dL/da, and
(b) The parameter gradients dL/dW, where w is the weights in the activation function. For activation functions with no gradients, this will be null.

Parameters:

in - Input, before applying the activation function (z, or 'preOut')

epsilon - Gradient to be backpropagated: dL/da, where L is the loss function

Returns:

dL/dz and dL/dW, for weights w (null if activation function has no weights)

toString

public String toString()

Overrides:

toString in class Object