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* ******************************************************************************
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* *
* * 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.
* *
* * See the NOTICE file distributed with this work for additional
* * information regarding copyright ownership.
* * 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.
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* * SPDX-License-Identifier: Apache-2.0
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*/
package org.nd4j.linalg.api.ops.impl.transforms.any;
import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
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.DynamicCustomOp;
import org.nd4j.linalg.factory.Nd4j;
import java.util.Collections;
import java.util.List;
/**
* [1, 2, 3, 1] -> [0, 0, 1, 0]
* @author Adam Gibson
*/
public class IsMax extends DynamicCustomOp {
public IsMax(SameDiff sameDiff, SDVariable i_v) {
super(sameDiff, i_v);
}
public IsMax(INDArray x, INDArray z) {
super(new INDArray[]{x}, new INDArray[]{z});
}
public IsMax() {}
public IsMax(INDArray x) {
this(x, Nd4j.createUninitialized(DataType.BOOL, x.shape(), x.ordering()));
}
public IsMax(INDArray x, INDArray z, int... dimensions) {
this(x, z);
this.addIArgument(dimensions);
}
public IsMax(INDArray x, int... dimensions) {
this(x, Nd4j.createUninitialized(DataType.BOOL, x.shape(), x.ordering()), dimensions);
}
@Override
public String opName() {
return "ismax";
}
@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 f1) {
return Collections.singletonList(sameDiff.zerosLike(arg()));
}
@Override
public List calculateOutputDataTypes(List inputDataTypes){
//Also supports other types if say float array is provided as output array
return Collections.singletonList(DataType.BOOL);
}
}