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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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package org.nd4j.linalg.api.ops.impl.reduce3;

import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.linalg.api.ndarray.INDArray;

import java.util.Arrays;
import java.util.List;

public class CosineDistance extends BaseReduce3Op {

    public CosineDistance(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, int... dimensions) {
        super(sameDiff, i_v, i_v2, dimensions);
    }

    public CosineDistance(SameDiff sameDiff, SDVariable i_v, SDVariable dimensions) {
        super(sameDiff, i_v, dimensions);
    }

    public CosineDistance(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, SDVariable dimensions) {
        super(sameDiff, i_v, i_v2, dimensions);
    }

    public CosineDistance() {
    }

    public CosineDistance(INDArray x, INDArray y, INDArray z) {
        this(x, y, z, null);
    }

    public CosineDistance(INDArray x, INDArray y, INDArray z, int... dimension) {
        super(x, y, z, dimension);
        extraArgs = new Object[]{0.0f, 0.0f};
    }

    public CosineDistance(INDArray x, INDArray y, int... dimension) {
        this(x, y, null, dimension);
    }

    public CosineDistance(INDArray x, INDArray y, INDArray z, boolean allDistances, int... dimension) {
        this(x, y, z, dimension);
        this.isComplex = allDistances;
    }

    public CosineDistance(INDArray x, INDArray y, boolean allDistances, int... dimension) {
        this(x, y, null, allDistances, dimension);
    }

    public CosineDistance(INDArray x, INDArray y, INDArray z, boolean keepDims, boolean allDistances, int... dimensions){
        super(x, y, z, keepDims, allDistances, dimensions);
        extraArgs = new Object[]{0.0f, 0.0f};
    }

    public CosineDistance(SameDiff sameDiff, SDVariable i_v, int[] dimensions) {
        super(sameDiff, i_v, dimensions);
    }

    public CosineDistance(SameDiff sd, SDVariable x, SDVariable y, boolean keepDims, boolean isComplex, int[] dimensions) {
        super(sd,x,y,keepDims,isComplex,dimensions);
    }

    public CosineDistance(INDArray x, INDArray y, boolean keepDims, boolean isComplex, int[] dimensions) {
        super(x,y,null,keepDims,isComplex,dimensions);
    }



    @Override
    public int opNum() {
        return 5;
    }

    @Override
    public String opName() {
        return "cosinedistance";
    }



    @Override
    public List doDiff(List i_v1) {
        //Cosine distance = 1 - cosine similarity
        //Therefore: just need to negate gradients from cosine similarity...

        List diff = CosineSimilarity.doDiff(sameDiff, larg(), rarg(), i_v1.get(0), keepDims, dimensions);
        return Arrays.asList(sameDiff.math.neg(diff.get(0)), sameDiff.math.neg(diff.get(1)));
    }
}