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 *  *  information regarding copyright ownership.
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 *  * distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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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));
    }


}




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