Class SameDiffLambdaLayer
- java.lang.Object
-
- org.deeplearning4j.nn.conf.layers.Layer
-
- org.deeplearning4j.nn.conf.layers.samediff.AbstractSameDiffLayer
-
- org.deeplearning4j.nn.conf.layers.samediff.SameDiffLayer
-
- org.deeplearning4j.nn.conf.layers.samediff.SameDiffLambdaLayer
-
- All Implemented Interfaces:
Serializable,Cloneable,TrainingConfig
- Direct Known Subclasses:
CapsuleStrengthLayer,IdentityLayer
public abstract class SameDiffLambdaLayer extends SameDiffLayer
- See Also:
- Serialized Form
-
-
Nested Class Summary
-
Nested classes/interfaces inherited from class org.deeplearning4j.nn.conf.layers.samediff.SameDiffLayer
SameDiffLayer.Builder<T extends SameDiffLayer.Builder<T>>
-
-
Field Summary
-
Fields inherited from class org.deeplearning4j.nn.conf.layers.samediff.SameDiffLayer
paramWeightInit, weightInit
-
Fields inherited from class org.deeplearning4j.nn.conf.layers.samediff.AbstractSameDiffLayer
biasUpdater, gradientNormalization, gradientNormalizationThreshold, regularization, regularizationBias, updater
-
Fields inherited from class org.deeplearning4j.nn.conf.layers.Layer
constraints, iDropout, layerName
-
-
Constructor Summary
Constructors Constructor Description SameDiffLambdaLayer()
-
Method Summary
All Methods Instance Methods Abstract Methods Concrete Methods Modifier and Type Method Description abstract SDVariabledefineLayer(SameDiff sameDiff, SDVariable layerInput)The defineLayer method is used to define the forward pass for the layerSDVariabledefineLayer(SameDiff sameDiff, SDVariable layerInput, Map<String,SDVariable> paramTable, SDVariable mask)Define the layervoiddefineParameters(SDLayerParams params)Define the parameters for the network.InputTypegetOutputType(int layerIndex, InputType inputType)For a given type of input to this layer, what is the type of the output?voidinitializeParameters(Map<String,INDArray> params)Set the initial parameter values for this layer, if required-
Methods inherited from class org.deeplearning4j.nn.conf.layers.samediff.SameDiffLayer
feedForwardMaskArray, instantiate, validateInput
-
Methods inherited from class org.deeplearning4j.nn.conf.layers.samediff.AbstractSameDiffLayer
applyGlobalConfig, applyGlobalConfigToLayer, getLayerParams, getMemoryReport, getPreProcessorForInputType, getRegularizationByParam, getUpdaterByParam, initializer, initWeights, isPretrainParam, onesMaskForInput, paramReshapeOrder, setNIn
-
Methods inherited from class org.deeplearning4j.nn.conf.layers.Layer
clone, 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
getGradientNormalization, getGradientNormalizationThreshold, getLayerName
-
-
-
-
Method Detail
-
defineLayer
public abstract SDVariable defineLayer(SameDiff sameDiff, SDVariable layerInput)
The defineLayer method is used to define the forward pass for the layer- Parameters:
sameDiff- SameDiff instance to use to define the vertexlayerInput- Layer input variable- Returns:
- The output variable (corresponding to the output activations for the layer)
-
defineLayer
public SDVariable defineLayer(SameDiff sameDiff, SDVariable layerInput, Map<String,SDVariable> paramTable, SDVariable mask)
Description copied from class:SameDiffLayerDefine the layer- Specified by:
defineLayerin classSameDiffLayer- Parameters:
sameDiff- SameDiff instancelayerInput- Input to the layerparamTable- Parameter table - keys as defined byAbstractSameDiffLayer.defineParameters(SDLayerParams)mask- Optional, maybe null. Mask to apply if supported- Returns:
- The final layer variable corresponding to the activations/output from the forward pass
-
getOutputType
public InputType getOutputType(int layerIndex, InputType inputType)
Description copied from class:LayerFor a given type of input to this layer, what is the type of the output?- Specified by:
getOutputTypein classLayer- Parameters:
layerIndex- Index of the layerinputType- Type of input for the layer- Returns:
- Type of output from the layer
-
defineParameters
public void defineParameters(SDLayerParams params)
Description copied from class:AbstractSameDiffLayerDefine the parameters for the network. UseSDLayerParams.addWeightParam(String, long...)andSDLayerParams.addBiasParam(String, long...)- Specified by:
defineParametersin classAbstractSameDiffLayer- Parameters:
params- Object used to set parameters for this layer
-
initializeParameters
public void initializeParameters(Map<String,INDArray> params)
Description copied from class:AbstractSameDiffLayerSet the initial parameter values for this layer, if required- Specified by:
initializeParametersin classAbstractSameDiffLayer- Parameters:
params- Parameter arrays that may be initialized
-
-