org.nd4j.linalg.api.ops.BaseBroadcastOp Maven / Gradle / Ivy

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package org.nd4j.linalg.api.ops;

import lombok.NoArgsConstructor;
import lombok.extern.slf4j.Slf4j;
import onnx.OnnxProto3;
import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.api.shape.Shape;
import org.tensorflow.framework.AttrValue;
import org.tensorflow.framework.GraphDef;
import org.tensorflow.framework.NodeDef;

import java.util.ArrayList;
import java.util.List;
import java.util.Map;

@NoArgsConstructor
@Slf4j
public abstract class BaseBroadcastOp extends BaseOp implements BroadcastOp {

    protected int[] dimension;


    public BaseBroadcastOp(SameDiff sameDiff,
                           SDVariable i_v1,
                           SDVariable i_v2,
                           int[] dimension) {
        this(sameDiff, i_v1, i_v2, false, dimension);
    }

    public BaseBroadcastOp(SameDiff sameDiff,
                           SDVariable i_v1,
                           SDVariable i_v2,
                           boolean inPlace,
                           int[] dimension) {
        super(sameDiff, inPlace, new Object[]{i_v2});
        if (i_v1 != null && i_v2 != null) {
            f().validateDifferentialFunctionsameDiff(i_v1);
            f().validateDifferentialFunctionsameDiff(i_v2);
            this.sameDiff = sameDiff;
            this.inPlace = inPlace;
            this.dimension = dimension;
            if(Shape.isPlaceholderShape(i_v1.getShape())) {
                sameDiff.addPropertyToResolve(this,i_v1.getVarName());
            }

            if(Shape.isPlaceholderShape(i_v2.getShape())) {
                sameDiff.addPropertyToResolve(this,i_v2.getVarName());
            }
            sameDiff.addArgsFor(new SDVariable[]{i_v1,i_v2},this);

        } else {
            throw new IllegalArgumentException("Input not null variables.");
        }

    }

    public BaseBroadcastOp(SameDiff sameDiff) {
        this.sameDiff = sameDiff;
    }

    public BaseBroadcastOp(SameDiff sameDiff,
                           SDVariable i_v1,
                           SDVariable i_v2,
                           int[] dimension,
                           Object[] extraArgs) {
        super(sameDiff, extraArgs);
        this.dimension = dimension;
        if (i_v1 != null && i_v2 != null) {
            f().validateDifferentialFunctionsameDiff(i_v1);
            f().validateDifferentialFunctionsameDiff(i_v2);

            this.sameDiff = sameDiff;
            sameDiff.addArgsFor(new SDVariable[]{i_v1,i_v2},this);

        } else {
            throw new IllegalArgumentException("Input not null variables.");
        }


    }


    public BaseBroadcastOp(SameDiff sameDiff, SDVariable i_v, int[] dimension, boolean inPlace) {
        this(sameDiff, i_v, i_v.getShape(), inPlace, dimension, null);
    }

    public BaseBroadcastOp(SameDiff sameDiff,
                           SDVariable i_v,
                           int[] shape,
                           boolean inPlace,
                           int[] dimension,
                           Object[] extraArgs) {
        super(sameDiff, inPlace, extraArgs);
        this.dimension = dimension;
        if (i_v != null) {
            f().validateDifferentialFunctionsameDiff(i_v);
            sameDiff.addArgsFor(new SDVariable[]{i_v},this);


        } else {
            throw new IllegalArgumentException("Input not null variable.");
        }


    }


    public BaseBroadcastOp(SameDiff sameDiff,
                           SDVariable i_v,
                           int[] dimension,
                           Object[] extraArgs) {
        this(sameDiff, i_v, i_v.getShape(), false, dimension, extraArgs);
    }

    public BaseBroadcastOp(INDArray x, INDArray y, INDArray z, int... dimension) {
        super(x, y, z, x.lengthLong());
        this.dimension = dimension;
        for (int i = 0; i < dimension.length; i++)
            if (dimension[i] < 0)
                dimension[i] += x.rank();

    }

    @Override
    public Type opType() {
        return Type.BROADCAST;
    }

    /**
     * Calculate the output shape for this op
     *
     * @return
     */
    public List calculateOutputShape() {
        List ret = new ArrayList<>();
        if (larg().getShape() != null && rarg().getShape() != null)
            ret.add(Shape.broadcastOutputShape(larg().getShape(), rarg().getShape()));
        else if(larg().getShape() != null)
            ret.add(larg().getShape());

        return ret;
    }


    @Override
    public int[] getDimension() {
        if (dimension == null) {
            dimension = Shape.getBroadcastDimensions(larg().getShape(), rarg().getShape());
        }
        return dimension;
    }


    @Override
    public void setDimension(int... dimension) {
        this.dimension = dimension;
    }


    @Override
    public void initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map attributesForNode, GraphDef graph) {
    }



    @Override
    public void initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map attributesForNode, OnnxProto3.GraphProto graph) {

    }
}