Question

请帮帮我！我正在使用deeplearning4j开展项目。 MNIST示例运行良好，但我的数据集出错。我的数据集有两个输出。

int height = 45;
int width = 800;
int channels = 1;
int rngseed = 123;
Random randNumGen = new Random(rngseed);
int batchSize = 128;
int outputNum = 2;
int numEpochs = 15;
File trainData = new File("C:/Users/JHP/Desktop/learningData/training");
File testData = new File("C:/Users/JHP/Desktop/learningData/testing");
FileSplit train = new FileSplit(trainData, NativeImageLoader.ALLOWED_FORMATS, randNumGen);
FileSplit test = new FileSplit(testData, NativeImageLoader.ALLOWED_FORMATS, randNumGen);
ParentPathLabelGenerator labelMaker = new ParentPathLabelGenerator();

ImageRecordReader recordReader = new ImageRecordReader(height, width, channels, labelMaker);
ImageRecordReader recordReader2 = new ImageRecordReader(height, width, channels, labelMaker);
recordReader.initialize(train);
recordReader2.initialize(test);

DataSetIterator dataIter = new RecordReaderDataSetIterator(recordReader, batchSize, 1, outputNum);
DataSetIterator testIter = new RecordReaderDataSetIterator(recordReader2, batchSize, 1, outputNum);

DataNormalization scaler = new ImagePreProcessingScaler(0, 1);
scaler.fit(dataIter);
dataIter.setPreProcessor(scaler);

System.out.println("Build model....");
MultiLayerConfiguration conf = new NeuralNetConfiguration.Builder()
        .seed(rngseed)
        .optimizationAlgo(OptimizationAlgorithm.STOCHASTIC_GRADIENT_DESCENT)
        .iterations(1)
        .learningRate(0.006)
        .updater(Updater.NESTEROVS).momentum(0.9)
        .regularization(true).l2(1e-4)
        .list()
        .layer(0,   new DenseLayer.Builder()
                .nIn(height * width)
                .nOut(1000)
                .activation(Activation.RELU)
                .weightInit(WeightInit.XAVIER)
                .build()
                )
        .layer(1, newOutputLayer.Builder(LossFunction.NEGATIVELOGLIKELIHOOD)
                .nIn(1000)
                .nOut(outputNum)
                .activation(Activation.SOFTMAX)
                .weightInit(WeightInit.XAVIER)
                .build()
                )
        .pretrain(false).backprop(true)
        .build();

MultiLayerNetwork model = new MultiLayerNetwork(conf);
model.init();
model.setListeners(new ScoreIterationListener(1));

System.out.println("Train model....");
for (int i = 0; i < numEpochs; i++) {
    try {
        model.fit(dataIter);
    } catch (Exception e) {
        System.out.println(e);
    }
}

错误是

org.deeplearning4j.exception.DL4JInvalidInputException：输入不是矩阵;预期矩阵（等级2），得到排名4阵列的形状 [128,1,45,800]

Answer 1

您正在初始化神经网络错误。如果您仔细观察dl4j示例中的每个 cnn示例（提示：这是您应该从中提取代码的规范来源，其他任何内容都可能无效或过时：{{ 3}}）您将在我们的所有示例中注意到我们有一个inputType配置： https://github.com/deeplearning4j/dl4j-examples

如果从不手动设置nIn，您应该使用各种类型。只是nOut。

对于mnist，我们使用卷积平面并将其转换为自动4d数据集。

Mnist以平面向量开始，但是cnn只能理解3d数据。我们为您做过这种转变并重塑。

使用deeprearning4j的MNIST示例的代码错误

1 个答案: