org.nd4j.linalg.api.ops.impl.transforms.comparison.Min 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.comparison;
import lombok.NonNull;
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.impl.transforms.BaseDynamicTransformOp;
import java.util.Arrays;
import java.util.List;
/**
* Min function
*
* @author Adam Gibson
*/
public class Min extends BaseDynamicTransformOp {
public Min() {}
public Min(SameDiff sameDiff, @NonNull SDVariable first, @NonNull SDVariable second){
this(sameDiff, new SDVariable[]{first, second}, false);
}
public Min( SameDiff sameDiff, SDVariable[] args, boolean inPlace) {
super(sameDiff, args, inPlace);
}
public Min( INDArray[] inputs, INDArray[] outputs) {
super(inputs, outputs);
}
@Override
public String opName() {
return "minimum";
}
@Override
public String onnxName() {
return "Min";
}
@Override
public String tensorflowName() {
return "Minimum";
}
@Override
public List doDiff(List f1) {
SDVariable min = outputVariables()[0];
SDVariable eq1 = sameDiff.eq(larg(), min);
SDVariable eq2 = sameDiff.eq(rarg(), min);
return Arrays.asList(eq1.mul(f1.get(0)), eq2.mul(f1.get(0)));
}
}