/*******************************************************************************
 * 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.scalar;

import lombok.val;
import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.imports.NoOpNameFoundException;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.api.ops.BaseScalarOp;
import org.nd4j.linalg.api.ops.BaseTransformOp;
import org.nd4j.linalg.factory.Nd4j;
import org.tensorflow.framework.AttrValue;
import org.tensorflow.framework.GraphDef;
import org.tensorflow.framework.NodeDef;

import java.util.Arrays;
import java.util.List;
import java.util.Map;

/**
 * Pow function
 *
 * @author Adam Gibson
 */
public class Pow extends BaseScalarOp {
    private double pow;

    public Pow() {
    }

    public Pow(SameDiff sameDiff, SDVariable i_v, boolean inPlace, double pow) {
        super(sameDiff, i_v, pow, inPlace);
        this.pow = pow;
        this.extraArgs = new Object[]{pow};
    }


    public Pow(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs, double pow) {
        super(sameDiff, i_v, pow, extraArgs);
        this.pow = pow;
        this.extraArgs = new Object[]{pow};
    }

    public Pow(INDArray x, INDArray z, double pow) {
        super(x, z, pow);
        this.pow = pow;
        this.extraArgs = new Object[]{pow};
    }

    public Pow(INDArray x, double pow) {
        super(x, pow);
        this.pow = pow;
        this.extraArgs = new Object[]{pow};
    }

    @Override
    public int opNum() {
        return 31;
    }

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

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

    @Override
    public String tensorflowName() {
        throw new NoOpNameFoundException("No TensorFlow op found for " + getClass().getSimpleName());
    }

    @Override
    public List<SDVariable> doDiff(List<SDVariable> i_v1) {
        SDVariable g = f().powDerivative(arg(), this.pow).mul(i_v1.get(0));
        return Arrays.asList(g);
    }

}
