Class Upsampling1D
- java.lang.Object
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- org.deeplearning4j.nn.conf.layers.Layer
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- org.deeplearning4j.nn.conf.layers.NoParamLayer
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- org.deeplearning4j.nn.conf.layers.BaseUpsamplingLayer
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- org.deeplearning4j.nn.conf.layers.Upsampling1D
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- All Implemented Interfaces:
Serializable
,Cloneable
,TrainingConfig
public class Upsampling1D extends BaseUpsamplingLayer
- See Also:
- Serialized Form
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Nested Class Summary
Nested Classes Modifier and Type Class Description static class
Upsampling1D.Builder
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Nested classes/interfaces inherited from class org.deeplearning4j.nn.conf.layers.BaseUpsamplingLayer
BaseUpsamplingLayer.UpsamplingBuilder<T extends BaseUpsamplingLayer.UpsamplingBuilder<T>>
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Field Summary
Fields Modifier and Type Field Description protected int[]
size
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Fields inherited from class org.deeplearning4j.nn.conf.layers.Layer
constraints, iDropout, layerName
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Constructor Summary
Constructors Modifier Constructor Description protected
Upsampling1D(BaseUpsamplingLayer.UpsamplingBuilder builder)
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description Upsampling1D
clone()
LayerMemoryReport
getMemoryReport(InputType inputType)
This is a report of the estimated memory consumption for the given layerInputType
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 appropriateInputPreProcessor
for this layer, such as aCnnToFeedForwardPreProcessor
Layer
instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
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Methods inherited from class org.deeplearning4j.nn.conf.layers.NoParamLayer
getGradientNormalization, getGradientNormalizationThreshold, getRegularizationByParam, initializer, isPretrainParam, setNIn
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Methods inherited from class org.deeplearning4j.nn.conf.layers.Layer
getUpdaterByParam, initializeConstraints, resetLayerDefaultConfig, setDataType
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Methods inherited from class java.lang.Object
equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
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Methods inherited from interface org.deeplearning4j.nn.api.TrainingConfig
getLayerName
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Constructor Detail
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Upsampling1D
protected Upsampling1D(BaseUpsamplingLayer.UpsamplingBuilder builder)
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Method Detail
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instantiate
public Layer instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)
- Specified by:
instantiate
in classLayer
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clone
public Upsampling1D clone()
- Overrides:
clone
in classBaseUpsamplingLayer
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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 classLayer
- Parameters:
layerIndex
- Index of the layerinputType
- Type of input for the layer- Returns:
- Type of output from the layer
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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 appropriateInputPreProcessor
for this layer, such as aCnnToFeedForwardPreProcessor
- Overrides:
getPreProcessorForInputType
in classBaseUpsamplingLayer
- Parameters:
inputType
- InputType to this layer- Returns:
- Null if no preprocessor is required, otherwise the type of preprocessor necessary for this layer/input combination
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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 classLayer
- Parameters:
inputType
- Input type to the layer. Memory consumption is often a function of the input type- Returns:
- Memory report for the layer
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