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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.shape;
import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.imports.NoOpNameFoundException;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.api.ops.ShapeOp;
import java.util.*;
/**
* Transpose function
*
* @author Adam Gibson
*/
public class RollAxis extends ShapeOp {
private int axis;
public RollAxis(SameDiff sameDiff, int axis) {
super(sameDiff);
this.axis = axis;
}
public RollAxis(SameDiff sameDiff, SDVariable i_v, int axis) {
super(sameDiff, i_v, false);
this.axis = axis;
}
public RollAxis(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs, int axis) {
super(sameDiff, i_v, shape, inPlace, extraArgs);
this.axis = axis;
}
public RollAxis() {
}
public RollAxis(INDArray x, INDArray z) {
super(x, z);
}
public RollAxis(INDArray x, INDArray z, long n) {
super(x, z, n);
}
public RollAxis(INDArray x, INDArray y, INDArray z, long n) {
super(x, y, z, n);
}
public RollAxis(INDArray x) {
super(x);
}
@Override
public Map propertiesForFunction() {
return Collections.singletonMap("axis", axis);
}
@Override
public void exec(int... dimensions) {
exec();
}
@Override
public boolean isExecSpecial() {
return true;
}
@Override
public void exec() {
int[] permute = new int[x.rank()];
permute[0] = axis;
int outPos = 1;
for( int i=0; i calculateOutputShape() {
List ret = new ArrayList<>();
long[] inputShape = arg().getShape();
long[] outputShape = new long[inputShape.length];
outputShape[0] = inputShape[axis];
for(int i = 1; i <=axis; ++i) {
outputShape[i] = inputShape[i - 1];
}
for(int i = axis + 1; i < inputShape.length; ++i) {
outputShape[i] = inputShape[i];
}
ret.add(outputShape);
return ret;
}
@Override
public int opNum() {
return 0;
}
@Override
public String opName() {
return "rollaxis";
}
@Override
public String onnxName() {
throw new NoOpNameFoundException("No onnx opName found for " + opName());
}
@Override
public String tensorflowName() {
throw new NoOpNameFoundException("No tensorflow opName found for " + opName());
}
@Override
public INDArray z() {
return x().transpose();
}
@Override
public List doDiff(List i_v) {
SDVariable ret = outputVariables()[0];
return Arrays.asList(ret);
}
}