org.nd4j.linalg.api.ops.impl.transforms.custom.SpaceToBatch Maven / Gradle / Ivy
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package org.nd4j.linalg.api.ops.impl.transforms.custom;
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.linalg.factory.Nd4j;
import java.util.*;
public class SpaceToBatch extends DynamicCustomOp {
protected int[] blocks;
protected int[][] padding;
public SpaceToBatch() {
}
public SpaceToBatch(SameDiff sameDiff, SDVariable x, int[] blocks, int[] paddingTop, int... paddingBottom) {
this(sameDiff, new SDVariable[]{x}, blocks, new int[][]{paddingBottom, paddingBottom}, false);
}
public SpaceToBatch(SameDiff sameDiff, SDVariable[] args, int[] blocks, int[][] padding, boolean inPlace) {
super(null, sameDiff, new SDVariable[]{args[0], sameDiff.constant(Nd4j.createFromArray(padding))}, inPlace);
this.blocks = blocks;
this.padding = padding;
addIArgument(blocks[0]);
}
public SpaceToBatch(INDArray x, int[] blocks, int[] paddingTop, int... paddingBottom) {
addInputArgument(x);
this.blocks = blocks;
this.padding = padding;
addIArgument(blocks[0]);
}
@Override
public String opName() {
return "space_to_batch";
}
@Override
public String onnxName() {
return "space_to_batch";
}
@Override
public String tensorflowName() {
return "SpaceToBatch";
}
@Override
public Map propertiesForFunction() {
Map ret = new HashMap<>();
if(blocks != null)
ret.put("blocks",blocks);
if(padding != null)
ret.put("padding",padding);
return ret;
}
@Override
public void configureFromArguments() {
super.configureFromArguments();
}
@Override
public void setPropertiesForFunction(Map properties) {
if(properties.containsKey("padding")) {
int[][] padding = (int[][]) properties.get("padding");
this.padding = padding;
}
if(properties.containsKey("blocks")) {
int[] blocks = (int[]) properties.get("blocks");
this.blocks = blocks;
}
}
@Override
public List doDiff(List i_v) {
// Inverse of space to batch is batch to space with same blocks and crops as padding
SDVariable gradient = sameDiff.setupFunction(i_v.get(0));
return Arrays.asList(sameDiff.cnn().batchToSpace(gradient, blocks, padding[0], padding[1]));
}
@Override
public List calculateOutputDataTypes(List dataTypes){
return Collections.singletonList(dataTypes.get(0));
}
}