Package ai.djl.nn.core
Class Prelu
- java.lang.Object
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- ai.djl.nn.AbstractBlock
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- ai.djl.nn.core.Prelu
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- All Implemented Interfaces:
Block
public class Prelu extends AbstractBlock
Applies Leaky Parametric ReLU activation element-wise to the input.Leaky ReLUs attempt to fix the 'dying ReLU' problem by allowing a small slope when the input is negative and has a slope of one when input is positive. This is defined by \(y= x \gt 0 ? x : slope * x\).
Parametric ReLU is a Leaky ReLU in which the slope is learnt during training.
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Field Summary
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Fields inherited from class ai.djl.nn.AbstractBlock
children, inputNames, inputShapes, parameters, version
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Constructor Summary
Constructors Constructor Description Prelu()
Creates a Parametric ReLU Block.
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Method Summary
All Methods Static Methods Instance Methods Concrete Methods Modifier and Type Method Description protected NDList
forwardInternal(ParameterStore parameterStore, NDList inputs, boolean training, ai.djl.util.PairList<java.lang.String,java.lang.Object> params)
A helper forBlock.forward(ParameterStore, NDList, boolean, PairList)
after initialization.Shape[]
getOutputShapes(Shape[] inputs)
Returns the expected output shapes of the block for the specified input shapes.void
loadMetadata(byte loadVersion, java.io.DataInputStream is)
Overwrite this to load additional metadata with the parameter values.static NDList
prelu(NDArray input, NDArray alpha)
Applies a Prelu activation on the inputNDArray
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Methods inherited from class ai.djl.nn.AbstractBlock
addChildBlock, addParameter, beforeInitialize, cast, clear, describeInput, forward, forward, forwardInternal, getChildren, getDirectParameters, getParameters, initialize, initializeChildBlocks, isInitialized, loadParameters, prepare, readInputShapes, saveInputShapes, saveMetadata, saveParameters, setInitializer, setInitializer, setInitializer, toString
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Method Detail
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forwardInternal
protected NDList forwardInternal(ParameterStore parameterStore, NDList inputs, boolean training, ai.djl.util.PairList<java.lang.String,java.lang.Object> params)
A helper forBlock.forward(ParameterStore, NDList, boolean, PairList)
after initialization.- Specified by:
forwardInternal
in classAbstractBlock
- Parameters:
parameterStore
- the parameter storeinputs
- the input NDListtraining
- true for a training forward passparams
- optional parameters- Returns:
- the output of the forward pass
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getOutputShapes
public Shape[] getOutputShapes(Shape[] inputs)
Returns the expected output shapes of the block for the specified input shapes.- Parameters:
inputs
- the shapes of the inputs- Returns:
- the expected output shapes of the block
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loadMetadata
public void loadMetadata(byte loadVersion, java.io.DataInputStream is) throws java.io.IOException, MalformedModelException
Overwrite this to load additional metadata with the parameter values.If you overwrite
AbstractBlock.saveMetadata(DataOutputStream)
or need to provide backward compatibility to older binary formats, you prabably need to overwrite this. This default implementation checks if the version number fits, if not it throws anMalformedModelException
. After that it restores the input shapes.- Overrides:
loadMetadata
in classAbstractBlock
- Parameters:
loadVersion
- the version used for loading this metadata.is
- the input stream we are loading from- Throws:
java.io.IOException
- loading failedMalformedModelException
- data can be loaded but has wrong format
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