org.nd4j.linalg.api.ops.random.impl.RandomMultinomial 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.
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* * See the NOTICE file distributed with this work for additional
* * information regarding copyright ownership.
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* * SPDX-License-Identifier: Apache-2.0
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package org.nd4j.linalg.api.ops.random.impl;
import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.common.base.Preconditions;
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.api.ops.OpContext;
import org.nd4j.linalg.api.ops.random.BaseRandomOp;
import org.nd4j.linalg.api.shape.LongShapeDescriptor;
import java.util.Arrays;
import java.util.Collections;
import java.util.List;
public class RandomMultinomial extends DynamicCustomOp {
public RandomMultinomial() {
}
@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 String opName() {
return "random_multinomial";
}
@Override
public List doDiff(List f1) {
return Collections.emptyList();
}
@Override
public List calculateOutputDataTypes(List inputDataTypes){
return Collections.singletonList(dArguments.isEmpty() ? inputDataTypes.get(0) : dArguments.get(0));
}
}