org.nd4j.linalg.api.ops.impl.reduce.floating.SquaredNorm 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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* * information regarding copyright ownership.
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* * SPDX-License-Identifier: Apache-2.0
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package org.nd4j.linalg.api.ops.impl.reduce.floating;
import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.imports.NoOpNameFoundException;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.api.ops.BaseReduceFloatOp;
import org.nd4j.linalg.api.ops.impl.reduce.bp.SquaredNormBp;
import java.util.List;
public class SquaredNorm extends BaseReduceFloatOp {
public SquaredNorm(SameDiff sameDiff, SDVariable input, boolean keepDims, int... dimensions) {
super(sameDiff, input, keepDims, dimensions);
}
public SquaredNorm(INDArray input, INDArray output, boolean keepDims, int... dimensions){
super(input, output, keepDims, dimensions);
}
public SquaredNorm(INDArray input, boolean keepDims, int... dimensions){
this(input, null, keepDims, dimensions);
}
public SquaredNorm(){}
public SquaredNorm(INDArray x, int... dimensions){
super(x, dimensions);
}
@Override
public int opNum() {
return 7;
}
@Override
public String opName() {
return "reduce_sqnorm";
}
@Override
public String onnxName() {
throw new NoOpNameFoundException("No Onnx op found for" + getClass().getName());
}
@Override
public String tensorflowName() {
throw new NoOpNameFoundException("No Tensorflow op found for" + getClass().getName());
}
@Override
public List doDiff(List grad){
return new SquaredNormBp(sameDiff, arg(), grad.get(0), keepDims, dimensions).outputs();
}
}