org.deeplearning4j.nn.conf.layers

Class Subsampling1DLayer

java.lang.Object

org.deeplearning4j.nn.conf.layers.Layer

org.deeplearning4j.nn.conf.layers.SubsamplingLayer

org.deeplearning4j.nn.conf.layers.Subsampling1DLayer

All Implemented Interfaces:

java.io.Serializable, java.lang.Cloneable

public class Subsampling1DLayer
extends SubsamplingLayer

1D (temporal) subsampling layer. Currently, we just subclass off the SubsamplingLayer and hard code the "width" dimension to 1. Also, this layer accepts RNN InputTypes instead of CNN InputTypes. This approach treats a multivariate time series with L timesteps and P variables as an L x 1 x P image (L rows high, 1 column wide, P channels deep). The kernel should be H

See Also:

Serialized Form

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	Subsampling1DLayer.Builder

Nested classes/interfaces inherited from class org.deeplearning4j.nn.conf.layers.SubsamplingLayer

SubsamplingLayer.BaseSubsamplingBuilder<T extends SubsamplingLayer.BaseSubsamplingBuilder<T>>, SubsamplingLayer.PoolingType

Field Summary

Fields inherited from class org.deeplearning4j.nn.conf.layers.SubsamplingLayer

convolutionMode, eps, kernelSize, padding, pnorm, poolingType, stride

Fields inherited from class org.deeplearning4j.nn.conf.layers.Layer

activationFn, adamMeanDecay, adamVarDecay, biasInit, biasLearningRate, dist, dropOut, epsilon, gradientNormalization, gradientNormalizationThreshold, l1, l1Bias, l2, l2Bias, layerName, learningRate, learningRateSchedule, momentum, momentumSchedule, rho, rmsDecay, updater, weightInit

Method Summary

Modifier and Type	Method and Description
Subsampling1DLayer	clone()
InputType	getOutputType(int layerIndex, InputType inputType) For a given type of input to this layer, what is the type of the output?
InputPreProcessor	getPreProcessorForInputType(InputType inputType) For the given type of input to this layer, what preprocessor (if any) is required? Returns null if no preprocessor is required, otherwise returns an appropriate InputPreProcessor for this layer, such as a CnnToFeedForwardPreProcessor
Layer	instantiate(NeuralNetConfiguration conf, java.util.Collection<IterationListener> iterationListeners, int layerIndex, org.nd4j.linalg.api.ndarray.INDArray layerParamsView, boolean initializeParams)
void	setNIn(InputType inputType, boolean override) Set the nIn value (number of inputs, or input depth for CNNs) based on the given input type

Methods inherited from class org.deeplearning4j.nn.conf.layers.SubsamplingLayer

getEps, getL1ByParam, getL2ByParam, getLearningRateByParam, getPnorm, initializer

Methods inherited from class org.deeplearning4j.nn.conf.layers.Layer

getUpdaterByParam, resetLayerDefaultConfig

Methods inherited from class java.lang.Object

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

Method Detail

instantiate

public Layer instantiate(NeuralNetConfiguration conf,
                         java.util.Collection<IterationListener> iterationListeners,
                         int layerIndex,
                         org.nd4j.linalg.api.ndarray.INDArray layerParamsView,
                         boolean initializeParams)

Overrides:

instantiate in class SubsamplingLayer

getOutputType

public InputType getOutputType(int layerIndex,
                               InputType inputType)

Description copied from class: Layer

For a given type of input to this layer, what is the type of the output?

Overrides:

getOutputType in class SubsamplingLayer

Parameters:

layerIndex - Index of the layer

inputType - Type of input for the layer

Returns:

Type of output from the layer

setNIn

public void setNIn(InputType inputType,
                   boolean override)

Description copied from class: Layer

Set the nIn value (number of inputs, or input depth for CNNs) based on the given input type

Overrides:

setNIn in class SubsamplingLayer

Parameters:

inputType - Input type for this layer

override - If false: only set the nIn value if it's not already set. If true: set it regardless of whether it's already set or not.

getPreProcessorForInputType

public InputPreProcessor getPreProcessorForInputType(InputType inputType)

Description copied from class: Layer

For the given type of input to this layer, what preprocessor (if any) is required?
Returns null if no preprocessor is required, otherwise returns an appropriate InputPreProcessor for this layer, such as a CnnToFeedForwardPreProcessor

Overrides:

getPreProcessorForInputType in class SubsamplingLayer

Parameters:

inputType - InputType to this layer

Returns:

Null if no preprocessor is required, otherwise the type of preprocessor necessary for this layer/input combination

clone

public Subsampling1DLayer clone()

Overrides:

clone in class SubsamplingLayer