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/*******************************************************************************
 * 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.impl.transforms.pairwise.arithmetic;

import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.api.ops.impl.transforms.BaseDynamicTransformOp;

import java.util.List;

/**
 * Division operation
 *
 * @author Adam Gibson
 */
public class DivOp extends BaseDynamicTransformOp {
    public static final String OP_NAME = "divide";

    public DivOp() {}

    public DivOp( SameDiff sameDiff, SDVariable[] args, boolean inPlace) {
        super(sameDiff, args, inPlace);
    }

    public DivOp(INDArray first, INDArray second, INDArray result){
        this(new INDArray[]{first, second}, result == null ? null : new INDArray[]{result});
    }

    public DivOp( INDArray[] inputs, INDArray[] outputs) {
        super(inputs, outputs);
    }


    @Override
    public String opName() {
        return OP_NAME;
    }

    @Override
    public String onnxName() {
        return "Div";
    }

    @Override
    public String tensorflowName() {
        return "Div";
    }



    @Override
    public List doDiff(List i_v) {
        return f().divBp(larg(), rarg(), i_v.get(0));
    }


}