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本篇內(nèi)容介紹了“StatsListener怎么使用”的有關(guān)知識(shí),在實(shí)際案例的操作過(guò)程中,不少人都會(huì)遇到這樣的困境,接下來(lái)就讓小編帶領(lǐng)大家學(xué)習(xí)一下如何處理這些情況吧!希望大家仔細(xì)閱讀,能夠?qū)W有所成!
import org.deeplearning4j.api.storage.StatsStorage; import org.deeplearning4j.examples.userInterface.util.UIExampleUtils; import org.deeplearning4j.nn.multilayer.MultiLayerNetwork; import org.deeplearning4j.optimize.listeners.ScoreIterationListener; import org.deeplearning4j.ui.api.UIServer; import org.deeplearning4j.ui.stats.StatsListener; import org.deeplearning4j.ui.storage.FileStatsStorage; import org.nd4j.linalg.dataset.api.iterator.DataSetIterator; import java.io.File; /** * A version of UIStorageExample showing how to saved network training data to a file, and then * reload it later, to display in in the UI * * @author Alex Black */ public class UIStorageExample { public static void main(String[] args){ //Run this example twice - once with collectStats = true, and then again with collectStats = false boolean collectStats = true; if(collectStats){ //First run: Collect training stats from the network //Note that we don't have to actually plot it when we collect it - though we can do that too, if required MultiLayerNetwork net = UIExampleUtils.getMnistNetwork(); DataSetIterator trainData = UIExampleUtils.getMnistData(); StatsStorage statsStorage = new FileStatsStorage(new File(System.getProperty("java.io.tmpdir"), "ui-stats.dl4j")); net.setListeners(new StatsListener(statsStorage), new ScoreIterationListener(10)); net.fit(trainData); System.out.println("Done"); } else { //Second run: Load the saved stats and visualize. Go to http://localhost:9000/train StatsStorage statsStorage = new FileStatsStorage(new File(System.getProperty("java.io.tmpdir"), "ui-stats.dl4j")); UIServer uiServer = UIServer.getInstance(); uiServer.attach(statsStorage); } } }
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