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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.
* *
* * 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
* * License for the specific language governing permissions and limitations
* * under the License.
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* * SPDX-License-Identifier: Apache-2.0
* *****************************************************************************
*/
package org.nd4j.linalg.api.ops.custom;
import lombok.NonNull;
import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.common.base.Preconditions;
import org.nd4j.linalg.api.buffer.DataType;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.api.ops.DynamicCustomOp;
import java.util.Collections;
import java.util.List;
public class Roll extends DynamicCustomOp {
public Roll() {}
public Roll(@NonNull INDArray input, @NonNull INDArray shifts, @NonNull INDArray axes) {
Preconditions.checkArgument(axes.rank() == shifts.rank(), "Roll: shifts and axes should be the same rank");
Preconditions.checkArgument(axes.length() == shifts.length(), "Roll: shifts and axes should be the same length");
addInputArgument(input, shifts, axes);
}
public Roll(@NonNull INDArray input, int shift) {
addInputArgument(input);
addIArgument(shift);
}
public Roll(@NonNull SameDiff sameDiff, @NonNull SDVariable input, @NonNull SDVariable shift) {
super("", sameDiff, new SDVariable[]{input,shift});
}
public Roll(@NonNull SameDiff sameDiff, @NonNull SDVariable input, @NonNull SDVariable shift, @NonNull SDVariable axes) {
super("", sameDiff, new SDVariable[]{input,shift,axes});
}
public Roll(@NonNull SameDiff sameDiff, @NonNull SDVariable input, int shift) {
super("", sameDiff, new SDVariable[]{input});
addIArgument(shift);
}
@Override
public String opName() {
return "roll";
}
@Override
public String tensorflowName() {
return "Roll";
}
@Override
public List calculateOutputDataTypes(List inputDataTypes){
int n = args().length;
Preconditions.checkState(inputDataTypes != null && inputDataTypes.size() == n, "Expected %s input data types for %s, got %s", n, getClass(), inputDataTypes);
return Collections.singletonList(inputDataTypes.get(0));
}
}