org.nd4j.linalg.api.ops.impl.transforms.custom.BatchToSpaceND Maven / Gradle / Ivy
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* Copyright (c) 2015-2018 Skymind, Inc.
*
* 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.
*
* 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
* License for the specific language governing permissions and limitations
* under the License.
*
* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
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.ops.DynamicCustomOp;
import java.util.Arrays;
import java.util.Collections;
import java.util.List;
/**
* N-dimensional batch to space operation. Transforms data from a tensor from batch dimension into M spatial dimensions
* according to the "blocks" specified (a vector of length M). Afterwards the spatial dimensions are optionally cropped,
* as specified in "crops", a tensor of dim (M, 2), denoting the crop range.
*
* Example:
* input: [[[[1]]], [[[2]]], [[[3]]], [[[4]]]]
* input shape: [4, 1, 1, 1]
* blocks: [2, 2]
* crops: [[0, 0], [0, 0]]
*
* output: [[[[1], [2]], [[3], [4]]]]
* output shape: [1, 2, 2, 1]
*
* @author Max Pumperla
*/
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 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));
}
@Override
public List calculateOutputDataTypes(List dataTypes){
return Collections.singletonList(dataTypes.get(0));
}
}