org.nd4j.linalg.api.ops.impl.transforms.pairwise.arithmetic.SquaredDifferenceOp 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.pairwise.arithmetic;
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.impl.transforms.BaseDynamicTransformOp;
import org.nd4j.linalg.api.ops.impl.transforms.pairwise.arithmetic.bp.SquaredDifferenceBpOp;
import java.util.Arrays;
import java.util.List;
/**
* Squared difference operation, i.e. returns (x - y) * (x - y)
*
* @author Max Pumperla
*/
public class SquaredDifferenceOp extends BaseDynamicTransformOp {
public static final String OP_NAME = "squaredsubtract";
public SquaredDifferenceOp() {}
public SquaredDifferenceOp(SameDiff sameDiff, SDVariable[] args, boolean inPlace) {
super(sameDiff, args, inPlace);
}
public SquaredDifferenceOp(INDArray[] inputs, INDArray[] outputs) {
super(inputs, outputs);
}
@Override
public String opName() {
return OP_NAME;
}
@Override
public String onnxName() {
throw new NoOpNameFoundException("No onnx op opName found for " + opName());
}
@Override
public String tensorflowName() {
return "SquaredDifference";
}
@Override
public List doDiff(List i_v1) {
SDVariable[] outputs = new SquaredDifferenceBpOp(f().sameDiff(), new SDVariable[]{larg(), rarg(), i_v1.get(0)}).outputVariables();
return Arrays.asList(outputs);
}
}