Package org.deeplearning4j.nn.conf.layers

Class Upsampling2D

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.Upsampling2D

All Implemented Interfaces:

Serializable, Cloneable, TrainingConfig

public class Upsampling2D
extends BaseUpsamplingLayer

See Also:

Serialized Form

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
static class	Upsampling2D.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	Description
protected CNN2DFormat	format
protected int[]	size

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

constraints, iDropout, layerName

Constructor Summary

Constructors

Modifier	Constructor	Description
protected	Upsampling2D(BaseUpsamplingLayer.UpsamplingBuilder builder)

Method Summary

Modifier and Type	Method	Description
Upsampling2D	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> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, 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

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

getGradientNormalization, getGradientNormalizationThreshold, getRegularizationByParam, initializer, isPretrainParam

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

format

protected CNN2DFormat format

Constructor Detail

Upsampling2D

protected Upsampling2D(BaseUpsamplingLayer.UpsamplingBuilder builder)

Method Detail

clone

public Upsampling2D clone()

Overrides:

clone in class BaseUpsamplingLayer

instantiate

public Layer instantiate(NeuralNetConfiguration conf,
                         Collection<TrainingListener> trainingListeners,
                         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

setNIn

public void setNIn(InputType inputType,
                   boolean override)

Description copied from class: Layer

Set the nIn value (number of inputs, or input channels for CNNs) based on the given input type

Overrides:

setNIn in class NoParamLayer

Parameters:

inputType - Input type for this layer

override - 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.