Class SeparableConvolution2D
- 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.ConvolutionLayer
-
- org.deeplearning4j.nn.conf.layers.SeparableConvolution2D
-
- All Implemented Interfaces:
Serializable,Cloneable,TrainingConfig
public class SeparableConvolution2D extends ConvolutionLayer
- See Also:
- Serialized Form
-
-
Nested Class Summary
Nested Classes Modifier and Type Class Description static classSeparableConvolution2D.Builder-
Nested classes/interfaces inherited from class org.deeplearning4j.nn.conf.layers.ConvolutionLayer
ConvolutionLayer.AlgoMode, ConvolutionLayer.BaseConvBuilder<T extends ConvolutionLayer.BaseConvBuilder<T>>, ConvolutionLayer.BwdDataAlgo, ConvolutionLayer.BwdFilterAlgo, ConvolutionLayer.FwdAlgo
-
-
Field Summary
-
Fields inherited from class org.deeplearning4j.nn.conf.layers.ConvolutionLayer
cnn2dDataFormat, convolutionMode, cudnnAlgoMode, cudnnAllowFallback, cudnnBwdDataAlgo, cudnnBwdFilterAlgo, cudnnFwdAlgo, dilation, hasBias, kernelSize, padding, stride
-
Fields inherited from class org.deeplearning4j.nn.conf.layers.FeedForwardLayer
nIn, nOut, timeDistributedFormat
-
Fields inherited from class org.deeplearning4j.nn.conf.layers.BaseLayer
activationFn, biasInit, biasUpdater, gainInit, gradientNormalization, gradientNormalizationThreshold, iUpdater, regularization, regularizationBias, weightInitFn, weightNoise
-
Fields inherited from class org.deeplearning4j.nn.conf.layers.Layer
constraints, iDropout, layerName
-
-
Constructor Summary
Constructors Modifier Constructor Description protectedSeparableConvolution2D(SeparableConvolution2D.Builder builder)SeparableConvolution2D layer nIn in the input layer is the number of channels nOut is the number of filters to be used in the net or in other words the channels The builder specifies the filter/kernel size, the stride and padding The pooling layer takes the kernel size
-
Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description SeparableConvolution2Dclone()InputTypegetOutputType(int layerIndex, InputType inputType)For a given type of input to this layer, what is the type of the output?booleanhasBias()protected voidinitializeConstraints(Layer.Builder<?> builder)Initialize the weight constraints.ParamInitializerinitializer()Layerinstantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)-
Methods inherited from class org.deeplearning4j.nn.conf.layers.ConvolutionLayer
getMemoryReport, getPreProcessorForInputType, setNIn
-
Methods inherited from class org.deeplearning4j.nn.conf.layers.FeedForwardLayer
isPretrainParam
-
Methods inherited from class org.deeplearning4j.nn.conf.layers.BaseLayer
getGradientNormalization, getRegularizationByParam, getUpdaterByParam, resetLayerDefaultConfig
-
Methods inherited from class org.deeplearning4j.nn.conf.layers.Layer
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
getGradientNormalizationThreshold, getLayerName
-
-
-
-
Constructor Detail
-
SeparableConvolution2D
protected SeparableConvolution2D(SeparableConvolution2D.Builder builder)
SeparableConvolution2D layer nIn in the input layer is the number of channels nOut is the number of filters to be used in the net or in other words the channels The builder specifies the filter/kernel size, the stride and padding The pooling layer takes the kernel size
-
-
Method Detail
-
initializeConstraints
protected void initializeConstraints(Layer.Builder<?> builder)
Description copied from class:LayerInitialize the weight constraints. Should be called last, in the outer-most constructor- Overrides:
initializeConstraintsin classLayer
-
hasBias
public boolean hasBias()
- Overrides:
hasBiasin classConvolutionLayer
-
clone
public SeparableConvolution2D clone()
- Overrides:
clonein classConvolutionLayer
-
instantiate
public Layer instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
- Overrides:
instantiatein classConvolutionLayer
-
initializer
public ParamInitializer initializer()
- Overrides:
initializerin classConvolutionLayer- Returns:
- The parameter initializer for this model
-
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?- Overrides:
getOutputTypein classConvolutionLayer- Parameters:
layerIndex- Index of the layerinputType- Type of input for the layer- Returns:
- Type of output from the layer
-
-