DeepLearning4j可以通过使用Apache Spark或者Hadoop来实现分布式训练。下面是使用Apache Spark来实现分布式训练的步骤:
在pom.xml文件中添加以下依赖:<dependency> <groupId>org.deeplearning4j</groupId> <artifactId>deeplearning4j-core</artifactId> <version>1.0.0-beta3</version></dependency><dependency> <groupId>org.deeplearning4j</groupId> <artifactId>deeplearning4j-ui_2.10</artifactId> <version>1.0.0-beta3</version></dependency><dependency> <groupId>org.deeplearning4j</groupId> <artifactId>deeplearning4j-scaleout</artifactId> <version>1.0.0-beta3</version></dependency><dependency> <groupId>org.nd4j</groupId> <artifactId>nd4j-native</artifactId> <version>1.0.0-beta3</version></dependency><dependency> <groupId>org.nd4j</groupId> <artifactId>nd4j-cuda-9.2-platform</artifactId> <version>1.0.0-beta3</version></dependency><dependency> <groupId>org.datavec</groupId> <artifactId>datavec-api</artifactId> <version>1.0.0-beta3</version></dependency><dependency> <groupId>org.datavec</groupId> <artifactId>datavec-local</artifactId> <version>1.0.0-beta3</version></dependency><dependency> <groupId>org.datavec</groupId> <artifactId>datavec-spark_2.10</artifactId> <version>1.0.0-beta3</version></dependency>创建一个SparkConf对象和JavaSparkContext对象:SparkConf conf = new SparkConf();conf.setAppName("DL4J Spark");JavaSparkContext sc = new JavaSparkContext(conf);加载数据集并创建一个DataSet对象:JavaRDD<String> data = sc.textFile("hdfs://path/to/data.txt");JavaRDD<DataSet> dataSet = data.map(new StringToDataSet());创建一个MultiLayerConfiguration对象并设置神经网络的配置:MultiLayerConfiguration conf = new NeuralNetConfiguration.Builder() .seed(12345) .weightInit(WeightInit.XAVIER) .updater(new Adam(0.01)) .list() .layer(0, new DenseLayer.Builder().nIn(784).nOut(250) .activation(Activation.RELU) .build()) .layer(1, new OutputLayer.Builder(LossFunctions.LossFunction.NEGATIVELOGLIKELIHOOD) .activation(Activation.SOFTMAX) .nIn(250).nOut(10).build()) .build();创建一个ComputationGraph对象并使用SparkComputationGraph对象进行训练:ComputationGraph model = new ComputationGraph(conf);model.init();SparkComputationGraph sparkNet = new SparkComputationGraph(sc, model);sparkNet.fit(dataSet);通过以上步骤,就可以使用DeepLearning4j和Apache Spark实现分布式训练。同样的,如果要使用Hadoop来实现分布式训练,可以使用datavec-hadoop依赖来读取HDFS中的数据集,并使用SparkComputationGraph对象进行训练。




