testDs/src/main/java/org/example/Main.java

package org.example;

import org.deeplearning4j.nn.api.OptimizationAlgorithm;
import org.deeplearning4j.nn.conf.MultiLayerConfiguration;
import org.deeplearning4j.nn.conf.NeuralNetConfiguration;
import org.deeplearning4j.nn.conf.layers.DenseLayer;
import org.deeplearning4j.nn.conf.layers.OutputLayer;
import org.deeplearning4j.nn.multilayer.MultiLayerNetwork;
import org.deeplearning4j.nn.weights.WeightInit;
import org.nd4j.linalg.activations.Activation;
import org.nd4j.linalg.learning.config.Nesterovs;
import org.nd4j.linalg.lossfunctions.LossFunctions;

public class Main {
    public static void main(String[] args) {

        MultiLayerConfiguration conf = new NeuralNetConfiguration.Builder()
                .optimizationAlgo(OptimizationAlgorithm.STOCHASTIC_GRADIENT_DESCENT)
                .updater(new Nesterovs(0.01, 0.9))
                .weightInit(WeightInit.XAVIER)
                .list()
                .layer(new DenseLayer.Builder().nIn(784).nOut(250).activation(Activation.RELU).build())
                .layer(new OutputLayer.Builder().nIn(250).nOut(10).activation(Activation.SOFTMAX).lossFunction(LossFunctions.LossFunction.MCXENT).build())
                .build();
        // 生成MultiLayerNetwork实例
        MultiLayerNetwork model = new MultiLayerNetwork(conf);
        model.init();
        // 在此添加训练代码

        System.out.println("Hello world!");
    }
}