org.nd4j.linalg.api.ops.impl.transforms.custom.CyclicShiftBits Maven / Gradle / Ivy
/*******************************************************************************
* 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 org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.base.Preconditions;
import org.nd4j.imports.NoOpNameFoundException;
import org.nd4j.linalg.api.buffer.DataType;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.api.ops.impl.transforms.BaseDynamicTransformOp;
import java.util.Collections;
import java.util.List;
/**
* Element-wise roll operation, rolls bits to the left, <<
*
* @author [email protected]
*/
public class CyclicShiftBits extends BaseDynamicTransformOp {
public CyclicShiftBits(SameDiff sameDiff, SDVariable x, SDVariable shift) {
super(sameDiff, new SDVariable[] {x, shift} ,false);
}
public CyclicShiftBits(INDArray input, INDArray shift, INDArray output) {
super(new INDArray[]{input, shift}, new INDArray[]{output});
}
public CyclicShiftBits(INDArray input, INDArray shift) {
this(input, shift,input.ulike());
}
public CyclicShiftBits() {}
@Override
public String opName() {
return "cyclic_shift_bits";
}
@Override
public String onnxName() {
throw new NoOpNameFoundException("No onnx op opName found for " + opName());
}
@Override
public String tensorflowName() {
throw new NoOpNameFoundException("No TensorFlow op opName found for " + opName());
}
@Override
public List doDiff(List i_v) {
throw new UnsupportedOperationException("Not yet implemented: " + opName());
}
@Override
public List calculateOutputDataTypes(List dataTypes){
Preconditions.checkState(dataTypes.get(0).isIntType(), "Input 0 datatype must be a integer type, got %s", dataTypes.get(0));
return Collections.singletonList(dataTypes.get(0));
}
}