org.deeplearning4j.nn.conf.layers

Class Upsampling3D

java.lang.Object

org.deeplearning4j.nn.conf.layers.Layer

org.deeplearning4j.nn.conf.layers.NoParamLayer

org.deeplearning4j.nn.conf.layers.BaseUpsamplingLayer

org.deeplearning4j.nn.conf.layers.Upsampling3D

All Implemented Interfaces:

Serializable, Cloneable, TrainingConfig

public class Upsampling3D
extends BaseUpsamplingLayer

Upsampling 3D layer
Repeats each value (all channel values for each x/y/z location) by size[0], size[1] and size[2]
If input has shape [minibatch, channels, depth, height, width] then output has shape [minibatch, channels, size[0] * depth, size[1] * height, size[2] * width]

Author:

Max Pumperla

See Also:

Serialized Form

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	Upsampling3D.Builder

Nested classes/interfaces inherited from class org.deeplearning4j.nn.conf.layers.BaseUpsamplingLayer

BaseUpsamplingLayer.UpsamplingBuilder<T extends BaseUpsamplingLayer.UpsamplingBuilder<T>>

Field Summary

Fields

Modifier and Type	Field and Description
protected Convolution3D.DataFormat	dataFormat
protected int[]	size

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

constraints, iDropout, layerName

Constructor Summary

Constructors

Modifier	Constructor and Description
protected	Upsampling3D(Upsampling3D.Builder builder)

Method Summary

Modifier and Type	Method and Description
Upsampling3D	clone()
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

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

Field Detail

size

protected int[] size

dataFormat

protected Convolution3D.DataFormat dataFormat

Constructor Detail

Upsampling3D

protected Upsampling3D(Upsampling3D.Builder builder)

Method Detail

clone

public Upsampling3D clone()

Overrides:

clone in class BaseUpsamplingLayer

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

Overrides:

getPreProcessorForInputType in class BaseUpsamplingLayer

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