org.nd4j.linalg.api.ops.impl.transforms.custom.Trace Maven / Gradle / Ivy
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* * terms of the Apache License, Version 2.0 which is available at
* * https://www.apache.org/licenses/LICENSE-2.0.
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package org.nd4j.linalg.api.ops.impl.transforms.custom;
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 java.util.Collections;
import java.util.List;
public class Trace extends DynamicCustomOp {
public Trace(SameDiff sd, SDVariable in){
super(null, sd, new SDVariable[]{in});
}
public Trace(@NonNull INDArray in){
super(wrapOrNull(in), null);
}
public Trace(){ }
@Override
public String opName(){
return "trace";
}
@Override
public List doDiff(List gradAtOutput){
SDVariable rows = sameDiff.reshape(sameDiff.sizeAt(arg(), -2), 1);
SDVariable cols = sameDiff.reshape(sameDiff.sizeAt(arg(), -1), 1);
SDVariable eye = sameDiff.math().eye(/*sameDiff.shape(gradAtOutput.get(0)),*/ rows, cols);
//Reshape gradient from [x,y,z] to [x,y,z,1,1]
SDVariable reshapedGrad = sameDiff.expandDims(gradAtOutput.get(0), -1);
reshapedGrad = sameDiff.expandDims(reshapedGrad, -1);
return Collections.singletonList(reshapedGrad.mul(eye));
}
@Override
public List calculateOutputDataTypes(List dataTypes){
Preconditions.checkState(dataTypes != null && dataTypes.size() == 1, "Expected exactly 1 input datatype for %s, got %s", getClass(), dataTypes);
return Collections.singletonList(dataTypes.get(0));
}
}