org.nd4j.linalg.api.ops.random.impl.BinomialDistributionEx Maven / Gradle / Ivy

Show more of this group Show more artifacts with this name
Show all versions of nd4j-api Show documentation
There is a newer version: 1.0.0-M2.1
/*******************************************************************************
 * 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.random.impl;

import lombok.NonNull;
import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.base.Preconditions;
import org.nd4j.imports.NoOpNameFoundException;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.api.ops.random.BaseRandomOp;

import java.util.LinkedHashMap;
import java.util.List;
import java.util.Map;

/**
 * This Op generates binomial distribution
 *
 * @author [email protected]
 */
public class BinomialDistributionEx extends BaseRandomOp {
    private int trials;
    private double probability;

    public BinomialDistributionEx() {
        super();
    }

    /**
     * This op fills Z with binomial distribution over given trials with single given probability for all trials
     * @param z
     * @param trials
     * @param probability
     */
    public BinomialDistributionEx(@NonNull INDArray z, int trials, double probability) {
        super(z, z, z);
        this.trials = trials;
        this.probability = probability;
        this.extraArgs = new Object[] {(double) this.trials, this.probability};
    }

    /**
     * This op fills Z with binomial distribution over given trials with probability for each trial given as probabilities INDArray
     * @param z
     * @param trials
     * @param probabilities array with probability value for each trial
     */
    public BinomialDistributionEx(@NonNull INDArray z, int trials, @NonNull INDArray probabilities) {
        super(z, probabilities, z);
        if (z.length() != probabilities.length())
            throw new IllegalStateException("Length of probabilities array should match length of target array");

        if (probabilities.elementWiseStride() < 1)
            throw new IllegalStateException("Probabilities array shouldn't have negative elementWiseStride");

        Preconditions.checkArgument(probabilities.dataType() == z.dataType(), "Probabilities and Z operand should have same data type");

        this.trials = trials;
        this.probability = 0.0;
        this.extraArgs = new Object[] {(double) this.trials, this.probability};
    }


    /**
     * This op fills Z with binomial distribution over given trials with probability for each trial given as probabilities INDArray
     *
     * @param z
     * @param probabilities
     */
    public BinomialDistributionEx(@NonNull INDArray z, @NonNull INDArray probabilities) {
        // FIXME: int cast
        this(z, (int) probabilities.length(), probabilities);
    }


    @Override
    public int opNum() {
        return 9;
    }

    @Override
    public String opName() {
        return "distribution_binomial_ex";
    }

    @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 null;
    }
}