org.deeplearning4j.nn.api

Interface Layer

All Superinterfaces:

Cloneable, Serializable

All Known Implementing Classes:

BaseLayer, ConvolutionDownSampleLayer, Layer, OutputLayer, SubsamplingLayer

public interface Layer
extends Serializable, Cloneable

Interface for a layer of a neural network. This has an activation function, an input and output size, weights, and a bias

Author:

Adam Gibson

Method Summary

Modifier and Type	Method and Description
org.nd4j.linalg.api.ndarray.INDArray	activate() Trigger an activation with the last specified input
org.nd4j.linalg.api.ndarray.INDArray	activate(org.nd4j.linalg.api.ndarray.INDArray input) Initialize the layer with the given input and return the activation for this layer given this input
org.nd4j.linalg.api.ndarray.INDArray	activationMean()
Layer	clone()
NeuralNetConfiguration	conf()
org.nd4j.linalg.api.ndarray.INDArray	getB()
org.nd4j.linalg.api.ndarray.INDArray	getInput()
org.nd4j.linalg.api.ndarray.INDArray	getW()
org.nd4j.linalg.api.ndarray.INDArray	preOutput(org.nd4j.linalg.api.ndarray.INDArray x)
void	setB(org.nd4j.linalg.api.ndarray.INDArray b)
void	setConfiguration(NeuralNetConfiguration conf)
void	setInput(org.nd4j.linalg.api.ndarray.INDArray input)
void	setW(org.nd4j.linalg.api.ndarray.INDArray w)
Layer	transpose() Return a transposed copy of the weights/bias (this means reverse the number of inputs and outputs on the weights)

Method Detail

activationMean

org.nd4j.linalg.api.ndarray.INDArray activationMean()

conf

NeuralNetConfiguration conf()

setConfiguration

void setConfiguration(NeuralNetConfiguration conf)

getW

org.nd4j.linalg.api.ndarray.INDArray getW()

setW

void setW(org.nd4j.linalg.api.ndarray.INDArray w)

getB

org.nd4j.linalg.api.ndarray.INDArray getB()

setB

void setB(org.nd4j.linalg.api.ndarray.INDArray b)

getInput

org.nd4j.linalg.api.ndarray.INDArray getInput()

setInput

void setInput(org.nd4j.linalg.api.ndarray.INDArray input)

preOutput

org.nd4j.linalg.api.ndarray.INDArray preOutput(org.nd4j.linalg.api.ndarray.INDArray x)

activate

org.nd4j.linalg.api.ndarray.INDArray activate()

Trigger an activation with the last specified input

Returns:

the activation of the last specified input

activate

org.nd4j.linalg.api.ndarray.INDArray activate(org.nd4j.linalg.api.ndarray.INDArray input)

Initialize the layer with the given input and return the activation for this layer given this input

Parameters:

input - the input to use

Returns:

transpose

Layer transpose()

Return a transposed copy of the weights/bias (this means reverse the number of inputs and outputs on the weights)

Returns:

the transposed layer

clone

Layer clone()