org.deeplearning4j.nn.conf.layers.recurrent

Class TimeDistributed

java.lang.Object

org.deeplearning4j.nn.conf.layers.Layer

org.deeplearning4j.nn.conf.layers.wrapper.BaseWrapperLayer

org.deeplearning4j.nn.conf.layers.recurrent.TimeDistributed

All Implemented Interfaces:

Serializable, Cloneable, TrainingConfig

public class TimeDistributed
extends BaseWrapperLayer

TimeDistributed wrapper layer.
Note: only the "Feed forward layer time distributed in an RNN" is currently supported. For example, a time distributed dense layer.
Usage: .layer(new TimeDistributed(new DenseLayer.Builder()....build(), timeAxis))
Note that for DL4J RNNs, time axis is always 2 - i.e., RNN activations have shape [minibatch, size, sequenceLength]

Author:

Alex Black

See Also:

Serialized Form

Nested Class Summary

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

Layer.Builder<T extends Layer.Builder<T>>

Field Summary

Fields inherited from class org.deeplearning4j.nn.conf.layers.wrapper.BaseWrapperLayer

underlying

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

constraints, iDropout, layerName

Constructor Summary

Constructors

Constructor and Description
TimeDistributed(Layer underlying)
TimeDistributed(@NonNull Layer underlying, RNNFormat rnnDataFormat)

Method Summary

Modifier and Type	Method and Description
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, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
void	setNIn(InputType inputType, boolean override) Set the nIn value (number of inputs, or input channels for CNNs) based on the given input type

Methods inherited from class org.deeplearning4j.nn.conf.layers.wrapper.BaseWrapperLayer

getGradientNormalization, getGradientNormalizationThreshold, getMemoryReport, getRegularizationByParam, initializer, isPretrainParam, setLayerName

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

clone, getUpdaterByParam, initializeConstraints, resetLayerDefaultConfig, setDataType

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

getLayerName

Constructor Detail

TimeDistributed

public TimeDistributed(@NonNull
                       @NonNull Layer underlying,
                       RNNFormat rnnDataFormat)

Parameters:

underlying - Underlying (internal) layer - should be a feed forward type such as DenseLayer

TimeDistributed

public TimeDistributed(Layer underlying)

Method Detail

instantiate

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

Specified by:

instantiate in class Layer

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 BaseWrapperLayer

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 channels for CNNs) based on the given input type

Overrides:

setNIn in class BaseWrapperLayer

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 BaseWrapperLayer

Parameters:

inputType - InputType to this layer

Returns:

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