org.nd4j.linalg.api.ops.impl.transforms.custom.LogicalOr Maven / Gradle / Ivy
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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.
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* * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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* * SPDX-License-Identifier: Apache-2.0
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package org.nd4j.linalg.api.ops.impl.transforms.custom;
import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.common.base.Preconditions;
import org.nd4j.linalg.api.buffer.DataType;
import org.nd4j.linalg.api.ops.DynamicCustomOp;
import java.util.Arrays;
import java.util.Collections;
import java.util.List;
public class LogicalOr extends DynamicCustomOp {
public LogicalOr(){ }
public LogicalOr(SameDiff sd, SDVariable in1, SDVariable in2){
super(null, sd, new SDVariable[]{in1, in2});
}
@Override
public String opName(){
return "boolean_or";
}
@Override
public String tensorflowName() {
return "LogicalOr";
}
@Override
public List doDiff(List f1) {
return Arrays.asList( sameDiff.zerosLike(larg()), sameDiff.zerosLike(rarg()));
}
@Override
public List calculateOutputDataTypes(List dataTypes){
Preconditions.checkState(dataTypes != null && dataTypes.size() == 2, "Expected exactly 2 input datatypes for %s, got %s", getClass(), dataTypes);
Preconditions.checkState(dataTypes.get(0) == DataType.BOOL, "Datatype for input 0 must be BOOL: got %s", dataTypes.get(0));
Preconditions.checkState(dataTypes.get(1) == DataType.BOOL, "Datatype for input 1 must be BOOL: got %s", dataTypes.get(1));
return Collections.singletonList(DataType.BOOL);
}
}