/*
 *  ******************************************************************************
 *  *
 *  *
 *  * 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.custom;

import lombok.NoArgsConstructor;
import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.common.base.Preconditions;
import org.nd4j.linalg.api.buffer.DataType;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.api.ops.DynamicCustomOp;
import org.tensorflow.framework.AttrValue;
import org.tensorflow.framework.GraphDef;
import org.tensorflow.framework.NodeDef;

import java.util.Collections;
import java.util.List;
import java.util.Map;

@NoArgsConstructor
public class TriangularSolve extends DynamicCustomOp {

    public TriangularSolve(INDArray matrix, INDArray rhs, boolean lower, boolean adjoint) {
        addInputArgument(matrix, rhs);
        addBArgument(lower, adjoint);
    }

    public TriangularSolve(SameDiff sameDiff, SDVariable matrix, SDVariable rhs,
                           SDVariable lower, SDVariable adjoint) {
        super(sameDiff, new SDVariable[] {matrix, rhs, lower, adjoint});
    }

    public TriangularSolve(SameDiff sameDiff, SDVariable matrix, SDVariable rhs,
                           boolean lower, boolean adjoint) {
        super(sameDiff, new SDVariable[] {matrix, rhs});
        addBArgument(lower, adjoint);
    }

    @Override
    public void initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String, AttrValue> attributesForNode, GraphDef graph) {
        if(attributesForNode.containsKey("lower")){
            addBArgument(attributesForNode.get("lower").getB());
        }

        if(attributesForNode.containsKey("adjoint")){
            addBArgument(attributesForNode.get("adjoint").getB());
        }
    }

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

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

    @Override
    public List<DataType> calculateOutputDataTypes(List<DataType> dataTypes) {
        int n = args().length;
        Preconditions.checkState(dataTypes != null && dataTypes.size() == n, "Expected %s input data types for %s, got %s", n, getClass(), dataTypes);
        return Collections.singletonList(dataTypes.get(0));
    }
}
