org.deeplearning4j.nn.conf.layers

Class LSTM

java.lang.Object

org.deeplearning4j.nn.conf.layers.Layer

org.deeplearning4j.nn.conf.layers.BaseLayer

org.deeplearning4j.nn.conf.layers.FeedForwardLayer

org.deeplearning4j.nn.conf.layers.BaseRecurrentLayer

org.deeplearning4j.nn.conf.layers.AbstractLSTM

org.deeplearning4j.nn.conf.layers.LSTM

All Implemented Interfaces:

Serializable, Cloneable, TrainingConfig

public class LSTM
extends AbstractLSTM

LSTM recurrent neural network layer without peephole connections. Supports CuDNN acceleration - see Author:

Alex Black

See Also:

GravesLSTM class for an alternative LSTM (with peephole connections), Serialized Form

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	LSTM.Builder

Field Summary

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

distRecurrent, weightInitRecurrent

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

nIn, nOut

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

activationFn, biasInit, biasUpdater, dist, gradientNormalization, gradientNormalizationThreshold, iUpdater, l1, l1Bias, l2, l2Bias, weightInit, weightNoise

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

constraints, iDropout, layerName

Method Summary

Modifier and Type	Method and Description
LayerMemoryReport	getMemoryReport(InputType inputType) This is a report of the estimated memory consumption for the given layer
protected void	initializeConstraints(Layer.Builder<?> builder) Initialize the weight constraints.
ParamInitializer	initializer()
Layer	instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams)

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

getL1ByParam, getL2ByParam

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

getOutputType, getPreProcessorForInputType, isPretrain, setNIn

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

isPretrainParam

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

clone, getGradientNormalization, getUpdaterByParam, resetLayerDefaultConfig

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

setPretrain

Methods inherited from class java.lang.Object

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

Methods inherited from interface org.deeplearning4j.nn.api.TrainingConfig

getGradientNormalizationThreshold, getLayerName

Method Detail

initializeConstraints

protected void initializeConstraints(Layer.Builder<?> builder)

Description copied from class: Layer

Initialize the weight constraints. Should be called last, in the outer-most constructor

Overrides:

initializeConstraints in class Layer

instantiate

public Layer instantiate(NeuralNetConfiguration conf,
                         Collection<TrainingListener> trainingListeners,
                         int layerIndex,
                         INDArray layerParamsView,
                         boolean initializeParams)

Specified by:

instantiate in class Layer

initializer

public ParamInitializer initializer()

Specified by:

initializer in class Layer

Returns:

The parameter initializer for this model

getMemoryReport

public LayerMemoryReport getMemoryReport(InputType inputType)

Description copied from class: Layer

This is a report of the estimated memory consumption for the given layer

Specified by:

getMemoryReport in class Layer

Parameters:

inputType - Input type to the layer. Memory consumption is often a function of the input type

Returns:

Memory report for the layer