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 *  * terms of the Apache License, Version 2.0 which is available at
 *  * https://www.apache.org/licenses/LICENSE-2.0.
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 *  *  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.
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package org.deeplearning4j.earlystopping;

import lombok.Data;
import org.deeplearning4j.nn.api.Model;

import java.io.Serializable;
import java.util.Map;

@Data
public class EarlyStoppingResult implements Serializable {
    public enum TerminationReason {
        Error, IterationTerminationCondition, EpochTerminationCondition
    }

    private TerminationReason terminationReason;
    private String terminationDetails;
    private Map scoreVsEpoch;
    private int bestModelEpoch;
    private double bestModelScore;
    private int totalEpochs;
    private T bestModel;

    public EarlyStoppingResult(TerminationReason terminationReason, String terminationDetails,
                    Map scoreVsEpoch, int bestModelEpoch, double bestModelScore, int totalEpochs,
                    T bestModel) {
        this.terminationReason = terminationReason;
        this.terminationDetails = terminationDetails;
        this.scoreVsEpoch = scoreVsEpoch;
        this.bestModelEpoch = bestModelEpoch;
        this.bestModelScore = bestModelScore;
        this.totalEpochs = totalEpochs;
        this.bestModel = bestModel;
    }

    @Override
    public String toString() {
        return "EarlyStoppingResult(terminationReason=" + terminationReason + ",details=" + terminationDetails
                        + ",bestModelEpoch=" + bestModelEpoch + ",bestModelScore=" + bestModelScore + ",totalEpochs="
                        + totalEpochs + ")";

    }

    public T getBestModel() {
        return bestModel;
    }

}




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