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Java example source code file (EarlyStoppingConfiguration.java)

This example Java source code file (EarlyStoppingConfiguration.java) is included in the alvinalexander.com "Java Source Code Warehouse" project. The intent of this project is to help you "Learn Java by Example" TM.

Learn more about this Java project at its project page.

Java - Java tags/keywords

arraylist, builder, data, earlystoppingconfiguration, earlystoppingmodelsaver, inmemorymodelsaver, list, scorecalculator, serializable, util

The EarlyStoppingConfiguration.java Java example source code

/*
 *
 *  * Copyright 2015 Skymind,Inc.
 *  *
 *  *    Licensed under the Apache License, Version 2.0 (the "License");
 *  *    you may not use this file except in compliance with the License.
 *  *    You may obtain a copy of the License at
 *  *
 *  *        http://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.
 *
 */

package org.deeplearning4j.earlystopping;

import lombok.Data;
import org.deeplearning4j.earlystopping.saver.InMemoryModelSaver;
import org.deeplearning4j.earlystopping.scorecalc.ScoreCalculator;
import org.deeplearning4j.earlystopping.termination.EpochTerminationCondition;
import org.deeplearning4j.earlystopping.termination.IterationTerminationCondition;
import org.deeplearning4j.nn.api.Model;

import java.io.Serializable;
import java.util.ArrayList;
import java.util.Collections;
import java.util.List;

/** Early stopping configuration: Specifies the various configuration options for running training with early stopping.<br>
 * Users need to specify the following:<br>
 * (a) EarlyStoppingModelSaver: How models will be saved (to disk, to memory, etc) (Default: in memory)<br>
 * (b) Termination conditions: at least one termination condition must be specified<br>
 *     (i) Iteration termination conditions: calculated once for each minibatch. For example, maxTime or invalid (NaN/infinite) scores<br>
 *     (ii) Epoch termination conditions: calculated once per epoch. For example, maxEpochs or no improvement for N epochs<br>
 * (c) Score calculator: what score should be calculated at every epoch? (For example: test set loss or test set accuracy)<br>
 * (d) How frequently (ever N epochs) should scores be calculated? (Default: every epoch)<br>
 * @param <T> Type of model. For example, {@link org.deeplearning4j.nn.multilayer.MultiLayerNetwork} or {@link org.deeplearning4j.nn.graph.ComputationGraph}
 * @author Alex Black
 */
@Data
public class EarlyStoppingConfiguration<T extends Model> implements Serializable {

    private EarlyStoppingModelSaver<T> modelSaver;
    private List<EpochTerminationCondition> epochTerminationConditions;
    private List<IterationTerminationCondition> iterationTerminationConditions;
    private boolean saveLastModel;
    private int evaluateEveryNEpochs;
    private ScoreCalculator<T> scoreCalculator;

    private EarlyStoppingConfiguration( Builder<T> builder ){
        this.modelSaver = builder.modelSaver;
        this.epochTerminationConditions = builder.epochTerminationConditions;
        this.iterationTerminationConditions = builder.iterationTerminationConditions;
        this.saveLastModel = builder.saveLastModel;
        this.evaluateEveryNEpochs = builder.evaluateEveryNEpochs;
        this.scoreCalculator = builder.scoreCalculator;
    }


    public static class Builder<T extends Model> {

        private EarlyStoppingModelSaver<T> modelSaver = new InMemoryModelSaver<>();
        private List<EpochTerminationCondition> epochTerminationConditions = new ArrayList<>();
        private List<IterationTerminationCondition> iterationTerminationConditions = new ArrayList<>();
        private boolean saveLastModel = false;
        private int evaluateEveryNEpochs = 1;
        private ScoreCalculator<T> scoreCalculator;

        /** How should models be saved? (Default: in memory)*/
        public Builder<T> modelSaver( EarlyStoppingModelSaver modelSaver ){
            this.modelSaver = modelSaver;
            return this;
        }

        /** Termination conditions to be evaluated every N epochs, with N set by evaluateEveryNEpochs option */
        public Builder<T> epochTerminationConditions(EpochTerminationCondition... terminationConditions){
            epochTerminationConditions.clear();
            Collections.addAll(epochTerminationConditions, terminationConditions);
            return this;
        }

        /** Termination conditions to be evaluated every N epochs, with N set by evaluateEveryNEpochs option */
        public Builder<T> epochTerminationConditions(List terminationConditions){
            this.epochTerminationConditions = terminationConditions;
            return this;
        }

        /** Termination conditions to be evaluated every iteration (minibatch)*/
        public Builder<T> iterationTerminationConditions(IterationTerminationCondition... terminationConditions){
            iterationTerminationConditions.clear();
            Collections.addAll(iterationTerminationConditions,terminationConditions);
            return this;
        }

        /** Save the last model? If true: save the most recent model at each epoch, in addition to the best
         * model (whenever the best model improves). If false: only save the best model. Default: false
         * Useful for example if you might want to continue training after a max-time terminatino condition
         * occurs.
         */
        public Builder<T> saveLastModel(boolean saveLastModel){
            this.saveLastModel = saveLastModel;
            return this;
        }

        /** How frequently should evaluations be conducted (in terms of epochs)? Defaults to every (1) epochs. */
        public Builder<T> evaluateEveryNEpochs(int everyNEpochs){
            this.evaluateEveryNEpochs = everyNEpochs;
            return this;
        }

        /** Score calculator. Used to calculate a score (such as loss function on a test set), every N epochs,
         * where N is set by {@link #evaluateEveryNEpochs}
         */
        public Builder<T> scoreCalculator(ScoreCalculator scoreCalculator){
            this.scoreCalculator = scoreCalculator;
            return this;
        }

        /** Create the early stopping configuration */
        public EarlyStoppingConfiguration<T> build(){
            return new EarlyStoppingConfiguration<>(this);
        }

    }

}

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