Package org.deeplearning4j.nn.conf.layers.convolutional

Class Cropping3D

java.lang.Object

org.deeplearning4j.nn.conf.layers.Layer

org.deeplearning4j.nn.conf.layers.NoParamLayer

org.deeplearning4j.nn.conf.layers.convolutional.Cropping3D

All Implemented Interfaces:

Serializable, Cloneable, TrainingConfig

public class Cropping3D
extends NoParamLayer

See Also:

Serialized Form

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
static class	Cropping3D.Builder

Field Summary

Fields inherited from class org.deeplearning4j.nn.conf.layers.Layer

constraints, iDropout, layerName

Constructor Summary

Constructors

Modifier	Constructor	Description
	Cropping3D(int[] cropping)
	Cropping3D(int cropDepth, int cropHeight, int cropWidth)
	Cropping3D(int cropLeftD, int cropRightD, int cropLeftH, int cropRightH, int cropLeftW, int cropRightW)
protected	Cropping3D(Cropping3D.Builder builder)

Method Summary

Modifier and Type	Method	Description
LayerMemoryReport	getMemoryReport(InputType inputType)	This is a report of the estimated memory consumption for the given layer
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
Layer	instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> iterationListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)

Methods inherited from class org.deeplearning4j.nn.conf.layers.NoParamLayer

getGradientNormalization, getGradientNormalizationThreshold, getRegularizationByParam, initializer, isPretrainParam, setNIn

Methods inherited from class org.deeplearning4j.nn.conf.layers.Layer

clone, getUpdaterByParam, 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

getLayerName

Constructor Detail

Cropping3D

public Cropping3D(int cropDepth,
                  int cropHeight,
                  int cropWidth)

Parameters:

cropDepth - Amount of cropping to apply to both depth boundaries of the input activations

cropHeight - Amount of cropping to apply to both height boundaries of the input activations

cropWidth - Amount of cropping to apply to both width boundaries of the input activations

Cropping3D

public Cropping3D(int cropLeftD,
                  int cropRightD,
                  int cropLeftH,
                  int cropRightH,
                  int cropLeftW,
                  int cropRightW)

Parameters:

cropLeftD - Amount of cropping to apply to the left of the depth dimension

cropRightD - Amount of cropping to apply to the right of the depth dimension

cropLeftH - Amount of cropping to apply to the left of the height dimension

cropRightH - Amount of cropping to apply to the right of the height dimension

cropLeftW - Amount of cropping to apply to the left of the width dimension

cropRightW - Amount of cropping to apply to the right of the width dimension

Cropping3D

public Cropping3D(int[] cropping)

Parameters:

cropping - Cropping as either a length 3 array, with values [cropDepth, cropHeight, cropWidth], or as a length 4 array, with values [cropLeftDepth, cropRightDepth, cropLeftHeight, cropRightHeight, cropLeftWidth, cropRightWidth]

Cropping3D

protected Cropping3D(Cropping3D.Builder builder)

Method Detail

instantiate

public Layer instantiate(NeuralNetConfiguration conf,
                         Collection<TrainingListener> iterationListeners,
                         int layerIndex,
                         INDArray layerParamsView,
                         boolean initializeParams,
                         DataType networkDataType)

Specified by:

instantiate in class Layer

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?

Specified by:

getOutputType in class Layer

Parameters:

layerIndex - Index of the layer

inputType - Type of input for the layer

Returns:

Type of output from the layer

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 appropriate InputPreProcessor for this layer, such as a CnnToFeedForwardPreProcessor

Specified by:

getPreProcessorForInputType in class Layer

Parameters:

inputType - InputType to this layer

Returns:

Null if no preprocessor is required, otherwise the type of preprocessor necessary for this layer/input combination

getMemoryReport

public LayerMemoryReport getMemoryReport(InputType inputType)

Description copied from class: Layer

This is a report of the estimated memory consumption for the given layer

Specified by:

getMemoryReport in class Layer

Parameters:

inputType - Input type to the layer. Memory consumption is often a function of the input type

Returns:

Memory report for the layer