Class TimeDistributed
- java.lang.Object
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- org.deeplearning4j.nn.conf.layers.Layer
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- org.deeplearning4j.nn.conf.layers.wrapper.BaseWrapperLayer
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- org.deeplearning4j.nn.conf.layers.recurrent.TimeDistributed
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- All Implemented Interfaces:
Serializable
,Cloneable
,TrainingConfig
public class TimeDistributed extends BaseWrapperLayer
- See Also:
- Serialized Form
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Nested Class Summary
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Nested classes/interfaces inherited from class org.deeplearning4j.nn.conf.layers.Layer
Layer.Builder<T extends Layer.Builder<T>>
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Field Summary
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Fields inherited from class org.deeplearning4j.nn.conf.layers.wrapper.BaseWrapperLayer
underlying
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Fields inherited from class org.deeplearning4j.nn.conf.layers.Layer
constraints, iDropout, layerName
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Constructor Summary
Constructors Constructor Description TimeDistributed(@NonNull Layer underlying, RNNFormat rnnDataFormat)
TimeDistributed(Layer underlying)
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method 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 appropriateInputPreProcessor
for this layer, such as aCnnToFeedForwardPreProcessor
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
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Methods inherited from class org.deeplearning4j.nn.conf.layers.Layer
clone, getUpdaterByParam, initializeConstraints, resetLayerDefaultConfig, setDataType
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Methods inherited from class java.lang.Object
equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
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Methods inherited from interface org.deeplearning4j.nn.api.TrainingConfig
getLayerName
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Method Detail
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instantiate
public Layer instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
- Specified by:
instantiate
in classLayer
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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 classBaseWrapperLayer
- Parameters:
layerIndex
- Index of the layerinputType
- Type of input for the layer- Returns:
- Type of output from the layer
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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 classBaseWrapperLayer
- Parameters:
inputType
- Input type for this layeroverride
- 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.
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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 appropriateInputPreProcessor
for this layer, such as aCnnToFeedForwardPreProcessor
- Overrides:
getPreProcessorForInputType
in classBaseWrapperLayer
- Parameters:
inputType
- InputType to this layer- Returns:
- Null if no preprocessor is required, otherwise the type of preprocessor necessary for this layer/input combination
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