/*******************************************************************************
 * 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.deeplearning4j.earlystopping.scorecalc;

import lombok.NoArgsConstructor;
import lombok.val;
import org.deeplearning4j.nn.graph.ComputationGraph;
import org.nd4j.linalg.dataset.DataSet;
import org.nd4j.linalg.dataset.api.MultiDataSet;
import org.nd4j.linalg.dataset.api.iterator.DataSetIterator;
import org.nd4j.linalg.dataset.api.iterator.MultiDataSetIterator;
import org.nd4j.shade.jackson.annotation.JsonIgnore;
import org.nd4j.shade.jackson.annotation.JsonProperty;

/**
 *  Given a DataSetIterator: calculate
 *  the total loss for the model on that data set.
 * Typically used to calculate the loss on a test set.
 *
 * @deprecated Use {@link DataSetLossCalculator} instead for both MultiLayerNetwork and ComputationGraph
 */
@NoArgsConstructor
@Deprecated
public class DataSetLossCalculatorCG implements ScoreCalculator<ComputationGraph> {
    @JsonIgnore
    private DataSetIterator dataSetIterator;
    @JsonIgnore
    private MultiDataSetIterator multiDataSetIterator;
    @JsonProperty
    private boolean average;

    /**Calculate the score (loss function value) on a given data set (usually a test set)
     *
     * @param dataSetIterator Data set to calculate the score for
     * @param average Whether to return the average (sum of loss / N) or just (sum of loss)
     */
    public DataSetLossCalculatorCG(DataSetIterator dataSetIterator, boolean average) {
        this.dataSetIterator = dataSetIterator;
        this.average = average;
    }

    /**Calculate the score (loss function value) on a given data set (usually a test set)
     *
     * @param dataSetIterator Data set to calculate the score for
     * @param average Whether to return the average (sum of loss / N) or just (sum of loss)
     */
    public DataSetLossCalculatorCG(MultiDataSetIterator dataSetIterator, boolean average) {
        this.multiDataSetIterator = dataSetIterator;
        this.average = average;
    }

    @Override
    public double calculateScore(ComputationGraph network) {
        double lossSum = 0.0;
        int exCount = 0;

        if (dataSetIterator != null) {
            dataSetIterator.reset();

            while (dataSetIterator.hasNext()) {
                DataSet dataSet = dataSetIterator.next();
                val nEx = dataSet.getFeatures().size(0);
                lossSum += network.score(dataSet) * nEx;
                exCount += nEx;
            }
        } else {
            multiDataSetIterator.reset();

            while (multiDataSetIterator.hasNext()) {
                MultiDataSet dataSet = multiDataSetIterator.next();
                val nEx = dataSet.getFeatures(0).size(0);
                lossSum += network.score(dataSet) * nEx;
                exCount += nEx;
            }
        }

        if (average)
            return lossSum / exCount;
        else
            return lossSum;
    }

    @Override
    public boolean minimizeScore() {
        return true;
    }

    @Override
    public String toString() {
        return "DataSetLossCalculatorCG(" + dataSetIterator + ",average=" + average + ")";
    }
}
