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* * This program and the accompanying materials are made available under the
* * terms of the Apache License, Version 2.0 which is available at
* * https://www.apache.org/licenses/LICENSE-2.0.
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* * See the NOTICE file distributed with this work for additional
* * information regarding copyright ownership.
* * Unless required by applicable law or agreed to in writing, software
* * distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
* * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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* * SPDX-License-Identifier: Apache-2.0
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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.linalg.factory.Nd4j;
import java.util.Arrays;
import java.util.Collections;
import java.util.List;
public class BatchToSpace extends DynamicCustomOp {
private int[] blocks;
private int[][] crops;
public BatchToSpace() {
}
public BatchToSpace(SameDiff sameDiff, SDVariable x, int[] blocks, int[] croppingTop, int... croppingBottom) {
this(sameDiff, x, blocks, new int[][]{croppingTop, croppingBottom}, false);
}
public BatchToSpace(SameDiff sameDiff, SDVariable x, int[] blocks, int[][] crops, boolean inPlace) {
this(sameDiff, new SDVariable[]{x}, blocks, crops, inPlace);
}
public BatchToSpace(SameDiff sameDiff, SDVariable[] args, int[] blocks, int[][] crops, boolean inPlace) {
super(null, sameDiff, new SDVariable[]{args[0], sameDiff.constant(Nd4j.createFromArray(crops))}, inPlace);
this.blocks = blocks;
this.crops = crops;
for (val b : blocks)
addIArgument(b);
}
public BatchToSpace(INDArray x, int[] blocks, int[] croppingTop, int... croppingBottom) {
addInputArgument(x);
int[][] crops = new int[][]{croppingTop, croppingBottom};
this.blocks = blocks;
this.crops = crops;
for (val b : blocks)
addIArgument(b);
}
@Override
public String opName() {
return "batch_to_space";
}
@Override
public String onnxName() {
return "batch_to_space";
}
@Override
public String tensorflowName() {
return "BatchToSpace";
}
@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));
}
}