Class BaseRecurrentLayer
- java.lang.Object
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- org.deeplearning4j.nn.conf.layers.Layer
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- org.deeplearning4j.nn.conf.layers.BaseLayer
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- org.deeplearning4j.nn.conf.layers.FeedForwardLayer
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- org.deeplearning4j.nn.conf.layers.BaseRecurrentLayer
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- All Implemented Interfaces:
Serializable
,Cloneable
,TrainingConfig
- Direct Known Subclasses:
AbstractLSTM
,GravesBidirectionalLSTM
,SimpleRnn
public abstract class BaseRecurrentLayer extends FeedForwardLayer
- See Also:
- Serialized Form
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Nested Class Summary
Nested Classes Modifier and Type Class Description static class
BaseRecurrentLayer.Builder<T extends BaseRecurrentLayer.Builder<T>>
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Field Summary
Fields Modifier and Type Field Description protected RNNFormat
rnnDataFormat
protected IWeightInit
weightInitFnRecurrent
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Fields inherited from class org.deeplearning4j.nn.conf.layers.FeedForwardLayer
nIn, nOut, timeDistributedFormat
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Fields inherited from class org.deeplearning4j.nn.conf.layers.BaseLayer
activationFn, biasInit, biasUpdater, gainInit, gradientNormalization, gradientNormalizationThreshold, iUpdater, regularization, regularizationBias, weightInitFn, weightNoise
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Fields inherited from class org.deeplearning4j.nn.conf.layers.Layer
constraints, iDropout, layerName
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Constructor Summary
Constructors Modifier Constructor Description protected
BaseRecurrentLayer(BaseRecurrentLayer.Builder builder)
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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
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.FeedForwardLayer
isPretrainParam
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Methods inherited from class org.deeplearning4j.nn.conf.layers.BaseLayer
clone, getGradientNormalization, getRegularizationByParam, getUpdaterByParam, resetLayerDefaultConfig
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Methods inherited from class org.deeplearning4j.nn.conf.layers.Layer
getMemoryReport, initializeConstraints, initializer, instantiate, 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
getGradientNormalizationThreshold, getLayerName
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Field Detail
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weightInitFnRecurrent
protected IWeightInit weightInitFnRecurrent
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rnnDataFormat
protected RNNFormat rnnDataFormat
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Constructor Detail
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BaseRecurrentLayer
protected BaseRecurrentLayer(BaseRecurrentLayer.Builder builder)
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Method Detail
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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 classFeedForwardLayer
- 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 classFeedForwardLayer
- 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 classFeedForwardLayer
- 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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