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 *  *  information regarding copyright ownership.
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package org.nd4j.linalg.api.ops.impl.transforms.custom;


import lombok.val;
import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.linalg.api.buffer.DataType;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.api.ops.DynamicCustomOp;
import org.nd4j.shade.guava.primitives.Ints;

import java.util.Arrays;
import java.util.Collections;
import java.util.List;
import java.util.Map;

public class BatchToSpaceND extends DynamicCustomOp {

    private int[] blocks;
    private int[][] crops;

    public BatchToSpaceND() {
    }

    public BatchToSpaceND(SameDiff sameDiff, SDVariable[] args, int[] blocks, int[][] crops, boolean inPlace) {
        super(null, sameDiff, args, inPlace);

        this.blocks = blocks;
        this.crops = crops;

        for (val b : blocks)
            addIArgument(b);

        for (int e = 0; e < crops.length; e++)
            addIArgument(crops[e][0], crops[e][1]);
    }

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

    @Override
    public String onnxName() {
        return "batch_to_space_nd";
    }

    @Override
    public String tensorflowName() {
        return "BatchToSpaceND";
    }


    @Override
    public void configureFromArguments() {
        SDVariable[] args = args();
        if(args != null && args.length > 1) {
            INDArray blocks = args[1].getArr();
            if(blocks != null) {
                this.blocks = blocks.toIntVector();
            }
            if(args.length > 2) {
                INDArray crops = args[2].getArr();
                if(crops != null)
                   this.crops = crops.toIntMatrix();
            }

        }
    }

    @Override
    public void setPropertiesForFunction(Map properties) {
        super.setPropertiesForFunction(properties);
    }

    @Override
    public List doDiff(List i_v) {
        // Inverse of batch to space is space to batch with same blocks and padding as crops
        SDVariable gradient = sameDiff.setupFunction(i_v.get(0));
        return Arrays.asList(sameDiff.cnn().spaceToBatch(gradient, blocks, crops[0], crops[1]));
    }

    @Override
    public List calculateOutputDataTypes(List dataTypes){
        return Collections.singletonList(dataTypes.get(0));
    }
}




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