org.nd4j.linalg.api.ops.impl.indexaccum.FirstIndex 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.indexaccum;
import lombok.NonNull;
import org.nd4j.autodiff.functions.DifferentialFunction;
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.BaseIndexAccumulation;
import org.nd4j.linalg.factory.Nd4j;
import org.nd4j.linalg.indexing.conditions.Condition;
import java.util.Collections;
import java.util.List;
/**
* Calculate the index
* of max value over a vector
*
* @author [email protected]
*/
public class FirstIndex extends BaseIndexAccumulation {
protected Condition condition;
protected double compare;
protected double eps;
protected int mode;
public FirstIndex(SameDiff sameDiff, SDVariable i_v, Condition condition, boolean keepDims, int... dimensions) {
super(sameDiff, i_v, keepDims, dimensions);
this.condition = condition;
this.compare = condition.getValue();
this.mode = condition.condtionNum();
this.eps = eps;
this.extraArgs = new Object[] {compare, eps, (double) mode};
}
public FirstIndex() {}
public FirstIndex(INDArray x, @NonNull Condition condition, int... dimension) {
this(x, condition, Nd4j.EPS_THRESHOLD, dimension);
}
public FirstIndex(INDArray x, @NonNull Condition condition, double eps, int... dimension) {
super(x, dimension);
this.condition = condition;
this.compare = condition.getValue();
this.mode = condition.condtionNum();
this.eps = eps;
this.extraArgs = new Object[] {compare, eps, (double) mode};
}
@Override
public int opNum() {
return 4;
}
@Override
public String opName() {
return "first_index";
}
@Override
public List doDiff(List f1) {
return Collections.singletonList(sameDiff.zerosLike(arg()));
}
@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());
}
}