public class Convolution3D extends ConvolutionLayer
Modifier and Type | Class and Description |
---|---|
static class |
Convolution3D.Builder |
static class |
Convolution3D.DataFormat
An optional dataFormat: "NDHWC" or "NCDHW".
|
ConvolutionLayer.AlgoMode, ConvolutionLayer.BaseConvBuilder<T extends ConvolutionLayer.BaseConvBuilder<T>>, ConvolutionLayer.BwdDataAlgo, ConvolutionLayer.BwdFilterAlgo, ConvolutionLayer.FwdAlgo
convolutionMode, cudnnAlgoMode, cudnnAllowFallback, cudnnBwdDataAlgo, cudnnBwdFilterAlgo, cudnnFwdAlgo, dilation, hasBias, kernelSize, padding, stride
nIn, nOut
activationFn, biasInit, biasUpdater, gainInit, gradientNormalization, gradientNormalizationThreshold, iUpdater, regularization, regularizationBias, weightInitFn, weightNoise
constraints, iDropout, layerName
Constructor and Description |
---|
Convolution3D(Convolution3D.Builder builder)
3-dimensional convolutional layer configuration 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 depth The builder specifies the filter/kernel size,
the stride and padding The pooling layer takes the kernel size
|
Modifier and Type | Method and Description |
---|---|
Convolution3D |
clone() |
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 |
boolean |
hasBias() |
ParamInitializer |
initializer() |
Layer |
instantiate(NeuralNetConfiguration conf,
Collection<TrainingListener> iterationListeners,
int layerIndex,
INDArray layerParamsView,
boolean initializeParams,
org.nd4j.linalg.api.buffer.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
|
getMemoryReport
isPretrainParam
getGradientNormalization, getRegularizationByParam, getUpdaterByParam, resetLayerDefaultConfig
initializeConstraints
equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
getGradientNormalizationThreshold, getLayerName
public Convolution3D(Convolution3D.Builder builder)
public boolean hasBias()
hasBias
in class ConvolutionLayer
public Convolution3D clone()
clone
in class ConvolutionLayer
public Layer instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> iterationListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, org.nd4j.linalg.api.buffer.DataType networkDataType)
instantiate
in class ConvolutionLayer
public ParamInitializer initializer()
initializer
in class ConvolutionLayer
public InputType getOutputType(int layerIndex, InputType inputType)
Layer
getOutputType
in class ConvolutionLayer
layerIndex
- Index of the layerinputType
- Type of input for the layerpublic InputPreProcessor getPreProcessorForInputType(InputType inputType)
Layer
InputPreProcessor
for this layer, such as a CnnToFeedForwardPreProcessor
getPreProcessorForInputType
in class ConvolutionLayer
inputType
- InputType to this layerpublic void setNIn(InputType inputType, boolean override)
Layer
setNIn
in class ConvolutionLayer
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.Copyright © 2019. All rights reserved.