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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.scalar;
import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.api.ops.BaseScalarOp;
import java.util.Arrays;
import java.util.List;
/**
* Scalar subtraction
*
* @author Adam Gibson
*/
public class ScalarSubtraction extends BaseScalarOp {
public ScalarSubtraction() {}
public ScalarSubtraction(INDArray x, INDArray y, INDArray z, long n, Number num) {
super(x, y, z, n, num);
}
public ScalarSubtraction(INDArray x, Number num) {
super(x, num);
}
public ScalarSubtraction(INDArray x) {
this(x, 0);
}
public ScalarSubtraction(SameDiff sameDiff, SDVariable i_v, Number scalar) {
super(sameDiff, i_v, scalar);
}
public ScalarSubtraction(SameDiff sameDiff, SDVariable i_v, Number scalar, boolean inPlace) {
super(sameDiff, i_v, scalar, inPlace);
}
public ScalarSubtraction(SameDiff sameDiff, SDVariable i_v, Number scalar, boolean inPlace, Object[] extraArgs) {
super(sameDiff, i_v, scalar, inPlace, extraArgs);
}
public ScalarSubtraction(SameDiff sameDiff, SDVariable i_v, Number scalar, Object[] extraArgs) {
super(sameDiff, i_v, scalar, extraArgs);
}
@Override
public int opNum() {
return 1;
}
@Override
public String opName() {
return "sub_scalar";
}
@Override
public String onnxName() {
return "Sub";
}
@Override
public String tensorflowName() {
return "RealSub";
}
@Override
public List doDiff(List i_v1) {
SDVariable g = i_v1.get(0);
return Arrays.asList(g);
}
}