deepnetts.net.layers.activation

Interface ActivationFunction

All Known Implementing Classes:

LeakyRelu, Linear, Relu, Sigmoid, Tanh

public interface ActivationFunction

Common base interface for all activation functions used in layers. Classes implementing this interface should provide methods for calculating value and first derivative of the activation function. Activation function performs non-linear transformation of its input before its sent to layer output. First derivative of a function shows how fast and in what direction function is changing if its input changes, and it is used by training algorithm. For more see https://en.wikipedia.org/wiki/Activation_function

Author:

Zoran Sevarac

See Also:

ActivationType

Method Summary

Modifier and Type	Method and Description
void	apply(Tensor tensor, int channel)
void	apply(Tensor tensor, int from, int to)
static ActivationFunction	create(ActivationType type) Creates and returns specified type of activation function.
float	getPrime(float y) Returns the first derivative of activation function for specified output y
float	getValue(float x) Returns the value of activation function for specified input x

Method Detail

getValue

float getValue(float x)

Returns the value of activation function for specified input x

Parameters:

x - input for activation

Returns:

value of activation function

apply

void apply(Tensor tensor,
           int channel)

apply

void apply(Tensor tensor,
           int from,
           int to)

getPrime

float getPrime(float y)

Returns the first derivative of activation function for specified output y

Parameters:

y - output of activation function

Returns:

first derivative of activation function

create

static ActivationFunction create(ActivationType type)

Creates and returns specified type of activation function. A factory method for creating activation functions;

Parameters:

type - type of the activation function

Returns:

returns instance of specified activation function type