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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.deeplearning4jgroupId>
<artifactId>deeplearning4j-coreartifactId>
<version>1.0.0-beta3version>
dependency>
<dependency>
<groupId>org.deeplearning4jgroupId>
<artifactId>deeplearning4j-ui_2.10artifactId>
<version>1.0.0-beta3version>
dependency>
<dependency>
<groupId>org.deeplearning4jgroupId>
<artifactId>deeplearning4j-scaleoutartifactId>
<version>1.0.0-beta3version>
dependency>
<dependency>
<groupId>org.nd4jgroupId>
<artifactId>nd4j-nativeartifactId>
<version>1.0.0-beta3version>
dependency>
<dependency>
<groupId>org.nd4jgroupId>
<artifactId>nd4j-cuda-9.2-platformartifactId>
<version>1.0.0-beta3version>
dependency>
<dependency>
<groupId>org.datavecgroupId>
<artifactId>datavec-apiartifactId>
<version>1.0.0-beta3version>
dependency>
<dependency>
<groupId>org.datavecgroupId>
<artifactId>datavec-localartifactId>
<version>1.0.0-beta3version>
dependency>
<dependency>
<groupId>org.datavecgroupId>
<artifactId>datavec-spark_2.10artifactId>
<version>1.0.0-beta3version>
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 data = sc.textFile("hdfs://path/to/data.txt");
JavaRDD 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。