DL4J-无法获得非2D矩阵的行数

Question

我目前使用nd4j和dl4j来实现一些深度学习算法。然而，我不能让datavec+dl4j工作在第一位。

以下是我的图像转换器：

public class ImageConverter {

    private static Logger log = LoggerFactory.getLogger(ImageConverter.class);

    public DataSetIterator Convert() throws IOException, InterruptedException {
        log.info("Start to convert images...");

        File parentDir = new File(System.getProperty("user.dir"), "src/main/resources/images/");
        ParentPathLabelGenerator parentPathLabelGenerator = new ParentPathLabelGenerator();

        ImageRecordReader recordReader = new ImageRecordReader(28,28,1,parentPathLabelGenerator);

        FileSplit fs = new FileSplit(parentDir);
        InputSplit[] filesInDirSplit = fs.sample(null, 100);

        recordReader.initialize(filesInDirSplit[0]);
        DataSetIterator dataIter = new RecordReaderDataSetIterator(recordReader, 2, 1, 2);

        log.info("Image convert finished.");

        return dataIter;
    }

}

下面是主要类：

ImageConverter icv = new ImageConverter();
        DataSetIterator dataSetIterator = icv.Convert();

        log.info("Build model....");
        int numEpochs = 10;

        MultiLayerConfiguration conf = new NeuralNetConfiguration.Builder()
              .seed(123)
              .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 ConvolutionLayer.Builder(5, 5)
                      .nIn(28 * 28)
                      .stride(1, 1)
                      .nOut(20)
                      .activation("identity")
                      .build())
              .layer(1, new OutputLayer.Builder(LossFunction.NEGATIVELOGLIKELIHOOD)
                      .nIn(24 * 24)
                      .nOut(2)
                      .activation("softmax")
                      .build())
              .pretrain(false)
              .backprop(true)
              .build();

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


        log.info("Train model....");
        for( int i=0; i<numEpochs; i++ ){
            model.fit(dataSetIterator);
        }

[[[...],
...
]]

=================OUTPUT==================
[[1.00, 0.00],
 [1.00, 0.00]]

[[[[...],
...
]]]

=================OUTPUT==================
[1.00, 0.00]

[[...]...]
=================OUTPUT==================
[[0.00, 0.00, 1.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00],
...]

从中我推断返回的DataSetiterator包含格式错误的数据。

有人知道怎么修吗？

Answer 1

我们已经在我们的示例中为您实现了这一点。

4D和2D对我们来说并不重要，只需指定卷积层设置:https://github.com/deeplearning4j/dl4j-examples/blob/master/dl4j-examples/src/main/java/org/deeplearning4j/examples/convolution/lenetMnistexample.java#l84

如果你再面临麻烦，在你认为讨论会更容易的地方，来我们的gitter:https://gitter.im/deeplearning4j/deeplearning4j