Class Cropping1D
- 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.convolutional.Cropping1D
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- All Implemented Interfaces:
Serializable,Cloneable,TrainingConfig
public class Cropping1D extends NoParamLayer
- See Also:
- Serialized Form
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Nested Class Summary
Nested Classes Modifier and Type Class Description static classCropping1D.Builder
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Field Summary
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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 Cropping1D(int cropTopBottom)Cropping1D(int[] cropping)Cropping1D(int cropTop, int cropBottom)protectedCropping1D(Cropping1D.Builder builder)
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description LayerMemoryReportgetMemoryReport(InputType inputType)This is a report of the estimated memory consumption for the given layerInputTypegetOutputType(int layerIndex, InputType inputType)For a given type of input to this layer, what is the type of the output?InputPreProcessorgetPreProcessorForInputType(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 appropriateInputPreProcessorfor this layer, such as aCnnToFeedForwardPreProcessorLayerinstantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)-
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
clone, 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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Cropping1D
public Cropping1D(int cropTopBottom)
- Parameters:
cropTopBottom- Amount of cropping to apply to both the top and the bottom of the input activations
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Cropping1D
public Cropping1D(int cropTop, int cropBottom)- Parameters:
cropTop- Amount of cropping to apply to the top of the input activationscropBottom- Amount of cropping to apply to the bottom of the input activations
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Cropping1D
public Cropping1D(int[] cropping)
- Parameters:
cropping- Cropping as a length 2 array, with values[cropTop, cropBottom]
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Cropping1D
protected Cropping1D(Cropping1D.Builder 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:
instantiatein classLayer
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getOutputType
public InputType getOutputType(int layerIndex, InputType inputType)
Description copied from class:LayerFor a given type of input to this layer, what is the type of the output?- Specified by:
getOutputTypein 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:LayerFor the given type of input to this layer, what preprocessor (if any) is required?
Returns null if no preprocessor is required, otherwise returns an appropriateInputPreProcessorfor this layer, such as aCnnToFeedForwardPreProcessor- Specified by:
getPreProcessorForInputTypein classLayer- 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:LayerThis is a report of the estimated memory consumption for the given layer- Specified by:
getMemoryReportin 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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