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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.accum;

import lombok.NoArgsConstructor;
import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.imports.NoOpNameFoundException;
import org.nd4j.imports.graphmapper.tf.TFGraphMapper;
import org.nd4j.linalg.api.ops.DynamicCustomOp;
import org.nd4j.linalg.api.ops.Op;
import org.tensorflow.framework.AttrValue;
import org.tensorflow.framework.GraphDef;
import org.tensorflow.framework.NodeDef;

import java.util.Map;


/**
 * Softmax cross entropy loss
 *
 * @author Max Pumperla
 */
@NoArgsConstructor
public class SoftmaxCrossEntropyLoss extends DynamicCustomOp {

    private int reductionMode = 0;
    private double labelSmoothing = 0.0;

    public SoftmaxCrossEntropyLoss(SameDiff sameDiff, SDVariable logits, SDVariable weights, SDVariable labels,
                                   int reductionMode, double labelSmoothing) {
        super(null, sameDiff, new SDVariable[]{logits, weights, labels}, false);
        this.reductionMode = reductionMode;
        this.labelSmoothing = labelSmoothing;
        this.sameDiff = sameDiff;

        addArgs();
    }

    public SoftmaxCrossEntropyLoss(SameDiff sameDiff, SDVariable logits, SDVariable weights, SDVariable labels,
                                   int reductionMode) {
        this(sameDiff, logits, weights, labels, reductionMode, 0.0);
    }


    public void addArgs() {
        addIArgument(reductionMode);
        addTArgument(labelSmoothing);
    }

    @Override
    public void initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map attributesForNode, GraphDef graph) {
        TFGraphMapper.getInstance().initFunctionFromProperties(nodeDef.getOp(), this, attributesForNode, nodeDef, graph);
        addArgs();
    }

    /*
    @Override
    public Map> mappingsForFunction() {
        Map> ret = new HashMap<>();
        Map attrs = new LinkedHashMap<>();

        val labelSmooting = PropertyMapping.builder()
                .propertyNames(new String[]{"label_smoothing"})
                .tfInputPosition(4)
                .build();
        attrs.put("labelSmoothing", labelSmooting);

        val reduction = PropertyMapping.builder()
                .propertyNames(new String[]{"reduction"})
                .tfInputPosition(7)
                .build();
        attrs.put("reductionMode", reduction);

        ret.put(tensorflowName(),attrs);
        return ret;
    }
    */

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

    @Override
    public String onnxName() {
        throw new NoOpNameFoundException("No onnx op opName found for " + opName());
    }

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

    @Override
    public Op.Type opType() {
        return Op.Type.CUSTOM;
    }
}