org.nd4j.linalg.api.ops.impl.transforms.custom.ThresholdRelu Maven / Gradle / Ivy
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* * terms of the Apache License, Version 2.0 which is available at
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package org.nd4j.linalg.api.ops.impl.transforms.custom;
import java.util.Collections;
import java.util.List;
import lombok.Getter;
import lombok.NonNull;
import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.common.base.Preconditions;
import org.nd4j.linalg.api.buffer.DataType;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.api.ops.DynamicCustomOp;
import org.nd4j.linalg.api.ops.impl.scalar.RectifiedLinear;
import org.nd4j.linalg.api.ops.impl.transforms.gradient.ThresholdReluBp;
public class ThresholdRelu extends DynamicCustomOp {
@Getter
private double cutoff = 0.0;
public ThresholdRelu(){ }
public ThresholdRelu(SameDiff sd, SDVariable input, boolean inPlace, double cutoff){
super(sd, new SDVariable[]{input}, inPlace);
this.cutoff = cutoff;
addTArgument(cutoff);
}
public ThresholdRelu(SameDiff sd, SDVariable input, double cutoff){
super(sd, new SDVariable[]{input});
this.cutoff = cutoff;
addTArgument(cutoff);
}
public ThresholdRelu(@NonNull INDArray input, INDArray output, double cutoff){
super(new INDArray[]{input}, wrapOrNull(output));
this.cutoff = cutoff;
addTArgument(cutoff);
}
@Override
public String opName(){
return "thresholdedrelu";
}
@Override
public List calculateOutputDataTypes(List dataTypes) {
Preconditions
.checkArgument(dataTypes != null && dataTypes.size() == 1, "Expected exactly 1 input datatypes, got %s", dataTypes);
Preconditions.checkArgument(dataTypes.get(0).isFPType(), "Input datatype must be floating point, got %s", dataTypes);
return Collections.singletonList(dataTypes.get(0));
}
@Override
public List doDiff(List f1) {
return new ThresholdReluBp(sameDiff, arg(), f1.get(0), cutoff).outputs();
}
}