/*
 *  ******************************************************************************
 *  *
 *  *
 *  * 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.
 *  *
 *  * SPDX-License-Identifier: Apache-2.0
 *  *****************************************************************************
 */

package org.nd4j.linalg.api.ops.impl.nlp;

import lombok.Builder;
import lombok.NonNull;
import lombok.val;
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;

public class CbowRound extends DynamicCustomOp {

    public CbowRound(){ }


    /**
     * full constructor
     *
     * @param target
     * @param context
     * @param ngStarter
     * @param syn0
     * @param syn1
     * @param syn1Neg
     * @param expTable
     * @param negTable
     * @param alpha
     * @param nextRandom
     * @param inferenceVector
     */
    @Builder
    public CbowRound(@NonNull INDArray target, @NonNull INDArray context, @NonNull INDArray lockedWords, @NonNull INDArray ngStarter, @NonNull INDArray syn0, @NonNull INDArray syn1, @NonNull INDArray syn1Neg, @NonNull INDArray expTable, @NonNull INDArray negTable, @NonNull INDArray indices, @NonNull INDArray codes, int nsRounds, @NonNull INDArray alpha, @NonNull INDArray nextRandom, @NonNull INDArray inferenceVector, @NonNull INDArray numLabels, boolean trainWords, int numWorkers,int iterations,double minLearningRate) {

        inputArguments.add(target);
        inputArguments.add(ngStarter);
        inputArguments.add(context);
        inputArguments.add(indices);
        inputArguments.add(codes);
        inputArguments.add(syn0);
        inputArguments.add(syn1);
        inputArguments.add(syn1Neg);
        inputArguments.add(expTable);
        inputArguments.add(negTable);
        inputArguments.add(alpha);
        inputArguments.add(nextRandom);
        inputArguments.add(numLabels);
        inputArguments.add(lockedWords);
        inputArguments.add(inferenceVector);

        // couple of options
        iArguments.add((long) numWorkers);
        iArguments.add((long) nsRounds);
        iArguments.add((long) iterations);


        tArguments.add(minLearningRate);

        bArguments.add(trainWords);
        bArguments.add(!inferenceVector.isEmpty());

        // this op is always inplace
        setInPlace(true);
        setInplaceCall(true);

        for (val in:inputArguments)
            outputArguments.add(in);
    }

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