/*
 *  ******************************************************************************
 *  *
 *  *
 *  * 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.shape;

import lombok.NonNull;
import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.linalg.api.buffer.DataType;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.api.ops.DynamicCustomOp;

import java.util.ArrayList;
import java.util.List;

public class MeshGrid extends DynamicCustomOp {

    /**
     *
     * @param sd
     * @param cartesian If true: broadcast dimensions for first two dimensions are swapped
     * @param inputs
     */
    public MeshGrid(SameDiff sd, boolean cartesian, SDVariable... inputs){
        super(null, sd, inputs, false);
        addIArgument(cartesian ? 1 : 0);
    }

    public MeshGrid(SameDiff sd, SDVariable[] inputs, boolean cartesian) {
        this(sd, cartesian, inputs);
    }

    public MeshGrid(@NonNull INDArray[] inputs, boolean cartesian){
        super(inputs, null);
        addIArgument(cartesian ? 1 : 0);
    }

    public MeshGrid(){ }

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

    public List<SDVariable> doDiff(List<SDVariable> gradients){
        SDVariable[] args = args();
        List<SDVariable> out = new ArrayList<>(args.length);
        for( int i = 0; i < args.length; i++) {
            long[] dims = new long[args.length-1];
            int x=0;
            for( int j = 0; j < args.length; j++) {
                if(i == j)
                    continue;
                dims[x++] = j;
            }
            out.add(gradients.get(i).sum(dims));
        }
        return out;
    }

    @Override
    public int getNumOutputs(){
        return args().length;
    }

    @Override
    public List<DataType> calculateOutputDataTypes(List<DataType> dataTypes){
        //Same output types as input types
        return dataTypes;
    }

}
