[pytorch] 2.1.2-1.5.10 release run example meet error [ Pointer address of argument 0 is NULL.]

[mullerhai]

Hi, feeling exciting to use javacpp [pytorch] 2.1.2-1.5.10 ,but when I running our example meet error ,I don't know why ,but the dataset real path is exist ,why the program can not read them?

Macos latest
java 1.8 && scala 2.11.11 all try

import org.bytedeco.javacpp._
import org.bytedeco.pytorch._
import org.bytedeco.pytorch.Module
import org.bytedeco.pytorch.global.torch._


object SimpleMNIST { // Define a new Module.
  class Net() extends Module { // Construct and register two Linear submodules.
    final var fc1: LinearImpl  = register_module("fc1", new LinearImpl(784, 64))
    final var fc2: LinearImpl = register_module("fc2", new LinearImpl(64, 32))
    final var fc3: LinearImpl= register_module("fc3", new LinearImpl(32, 10))

    // Implement the Net's algorithm.
    def forward(xs: Tensor): Tensor = { // Use one of many tensor manipulation functions.
      var x = xs
      x = relu(fc1.forward(x.reshape(x.size(0), 784)))
      x = dropout(x, /*p=*/ 0.5, /*train=*/ is_training)
      x = relu(fc2.forward(x))
      x = log_softmax(fc3.forward(x), /*dim=*/ 1)
      x
    }


  }

  @throws[Exception]
  def main(args: Array[String]): Unit = {
    /* try to use MKL when available */
    System.setProperty("org.bytedeco.openblas.load", "mkl")
    // Create a new Net.
    val net = new SimpleMNIST.Net
    // Create a multi-threaded data loader for the MNIST dataset.
    val path = "/Users/zhanghaining/Downloads/mnist/" //"./data"
//    val pathz = "/Users/zhanghaining/Documents/codeWorld/untitled/data/"
    val pathz = "/Users/zhanghaining/Downloads/pytorchScala/data/"
    val paths = "/Users/zhanghaining/Downloads/pytorchScala/data/"
    val mnist = new MNIST(paths)

    val data_set = mnist.map(new ExampleStack)
    val data_loader = new MNISTRandomDataLoader(data_set, new RandomSampler(data_set.size.get), new DataLoaderOptions(/*batch_size=*/ 64))
    // Instantiate an SGD optimization algorithm to update our Net's parameters.
    val optimizer = new SGD(net.parameters, new SGDOptions(/*lr=*/ 0.01))
    for (epoch <- 1 to 10) {
      var batch_index = 0
      // Iterate the data loader to yield batches from the dataset.
      var it = data_loader.begin
      while ( {
        !(it == data_loader.end)
      }) {
        val batch = it.access
        // Reset gradients.
        optimizer.zero_grad()
        // Execute the model on the input data.
        val prediction = net.forward(batch.data)
        // Compute a loss value to judge the prediction of our model.
        val loss = nll_loss(prediction, batch.target)
        // Compute gradients of the loss w.r.t. the parameters of our model.
        loss.backward()
        // Update the parameters based on the calculated gradients.
        optimizer.step
        // Output the loss and checkpoint every 100 batches.
        if ( {
          batch_index += 1; batch_index
        } % 100 == 0) {
          System.out.println("Epoch: " + epoch + " | Batch: " + batch_index + " | Loss: " + loss.item_float)
          // Serialize your model periodically as a checkpoint.
          val archive = new OutputArchive
          net.save(archive)
          archive.save_to("net.pt")
        }

        it = it.increment
      }
    }
  }
}

Exception in thread "main" java.lang.NullPointerException: Pointer address of argument 0 is NULL.
	at org.bytedeco.pytorch.MNISTBatchDataset.map(Native Method)
	at SimpleMNIST$.main(example.scala:39)
	at SimpleMNIST.main(example.scala)

[mullerhai]

when I running the chunkdataset also meet this error

 /* try to use MKL when available */
    System.setProperty("org.bytedeco.openblas.load", "mkl")
    // Create a new Net.
    import org.bytedeco.pytorch.ChunkDataReader
    import org.bytedeco.pytorch.ChunkDataset
    import org.bytedeco.pytorch.ChunkDatasetOptions
    import org.bytedeco.pytorch.ChunkMapDataset
    import org.bytedeco.pytorch.ChunkRandomDataLoader
    import org.bytedeco.pytorch.ChunkSharedBatchDataset
    import org.bytedeco.pytorch.DataLoaderOptions
    import org.bytedeco.pytorch.Example
    import org.bytedeco.pytorch.ExampleIterator
    import org.bytedeco.pytorch.ExampleStack
    import org.bytedeco.pytorch.ExampleVector
    import org.bytedeco.pytorch.RandomSampler
    import org.bytedeco.pytorch.Tensor
    val batch_size = 10
    val prefetch_count = 1
    val data_reader = new ChunkDataReader() {

      override def read_chunk(chunk_index: Long) = new ExampleVector(new Example(torch.ones(1), torch.ones(1)), new Example(torch.ones(1), torch.ones(1)))

      override def chunk_count = 1

      override def reset(): Unit = {
      }
    }
    val sampler = new RandomSampler(0)
    val data_set = new ChunkSharedBatchDataset(new ChunkDataset(data_reader, sampler, sampler, new ChunkDatasetOptions(prefetch_count, batch_size))).map(new ExampleStack)
    val data_loaders: ChunkRandomDataLoaderBase = new ChunkRandomDataLoader(data_set, new DataLoaderOptions(batch_size))

    for (epoch <- 1 to 10) {
      var it = data_loaders.begin()
      while ( {
        !(it == data_loaders.end)
      }) {
        val batch = it.access

        println(s" ${batch.data.createIndexer } ${batch.target.createIndexer} " )

        it = it.increment
      }
    }

error

/Library/Java/JavaVirtualMachines/jdk1.8.0_191.jdk/Contents/Home/bin/java -javaagent:/Applications/IntelliJ IDEA.app/Contents/lib/idea_rt.jar=58358:/Applications/IntelliJ IDEA.app/Contents/bin -Dfile.encoding=UTF-8 -classpath /Library/Java/JavaVirtualMachines/jdk1.8.0_191.jdk/Contents/Home/jre/lib/charsets.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_191.jdk/Contents/Home/jre/lib/deploy.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_191.jdk/Contents/Home/jre/lib/ext/cldrdata.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_191.jdk/Contents/Home/jre/lib/ext/dnsns.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_191.jdk/Contents/Home/jre/lib/ext/jaccess.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_191.jdk/Contents/Home/jre/lib/ext/jfxrt.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_191.jdk/Contents/Home/jre/lib/ext/localedata.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_191.jdk/Contents/Home/jre/lib/ext/nashorn.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_191.jdk/Contents/Home/jre/lib/ext/sunec.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_191.jdk/Contents/Home/jre/lib/ext/sunjce_provider.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_191.jdk/Contents/Home/jre/lib/ext/sunpkcs11.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_191.jdk/Contents/Home/jre/lib/ext/zipfs.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_191.jdk/Contents/Home/jre/lib/javaws.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_191.jdk/Contents/Home/jre/lib/jce.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_191.jdk/Contents/Home/jre/lib/jfr.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_191.jdk/Contents/Home/jre/lib/jfxswt.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_191.jdk/Contents/Home/jre/lib/jsse.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_191.jdk/Contents/Home/jre/lib/management-agent.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_191.jdk/Contents/Home/jre/lib/plugin.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_191.jdk/Contents/Home/jre/lib/resources.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_191.jdk/Contents/Home/jre/lib/rt.jar:/Users/zhanghaining/Downloads/pytorchScala/target/scala-2.12/classes:/Users/zhanghaining/Library/Caches/Coursier/v1/https/oss.sonatype.org/content/repositories/snapshots/org/bytedeco/javacpp-platform/1.5.11-SNAPSHOT/javacpp-platform-1.5.11-20240211.152631-54.jar:/Users/zhanghaining/Library/Caches/Coursier/v1/https/oss.sonatype.org/content/repositories/snapshots/org/bytedeco/javacpp/1.5.11-SNAPSHOT/javacpp-1.5.11-20240211.152855-41-android-arm64.jar:/Users/zhanghaining/Library/Caches/Coursier/v1/https/oss.sonatype.org/content/repositories/snapshots/org/bytedeco/javacpp/1.5.11-SNAPSHOT/javacpp-1.5.11-20240211.152855-41-android-x86_64.jar:/Users/zhanghaining/Library/Caches/Coursier/v1/https/oss.sonatype.org/content/repositories/snapshots/org/bytedeco/javacpp/1.5.11-SNAPSHOT/javacpp-1.5.11-20240211.152855-41-ios-arm64.jar:/Users/zhanghaining/Library/Caches/Coursier/v1/https/oss.sonatype.org/content/repositories/snapshots/org/bytedeco/javacpp/1.5.11-SNAPSHOT/javacpp-1.5.11-20240211.152855-41-ios-x86_64.jar:/Users/zhanghaining/Library/Caches/Coursier/v1/https/oss.sonatype.org/content/repositories/snapshots/org/bytedeco/javacpp/1.5.11-SNAPSHOT/javacpp-1.5.11-20240211.152855-41.jar:/Users/zhanghaining/Library/Caches/Coursier/v1/https/oss.sonatype.org/content/repositories/snapshots/org/bytedeco/javacpp/1.5.11-SNAPSHOT/javacpp-1.5.11-20240211.152855-41-linux-arm64.jar:/Users/zhanghaining/Library/Caches/Coursier/v1/https/oss.sonatype.org/content/repositories/snapshots/org/bytedeco/javacpp/1.5.11-SNAPSHOT/javacpp-1.5.11-20240211.152855-41-linux-ppc64le.jar:/Users/zhanghaining/Library/Caches/Coursier/v1/https/oss.sonatype.org/content/repositories/snapshots/org/bytedeco/javacpp/1.5.11-SNAPSHOT/javacpp-1.5.11-20240211.152855-41-linux-x86_64.jar:/Users/zhanghaining/Library/Caches/Coursier/v1/https/oss.sonatype.org/content/repositories/snapshots/org/bytedeco/javacpp/1.5.11-SNAPSHOT/javacpp-1.5.11-20240211.152855-41-macosx-arm64.jar:/Users/zhanghaining/Library/Caches/Coursier/v1/https/oss.sonatype.org/content/repositories/snapshots/org/bytedeco/javacpp/1.5.11-SNAPSHOT/javacpp-1.5.11-20240211.152855-41-macosx-x86_64.jar:/Users/zhanghaining/Library/Caches/Coursier/v1/https/oss.sonatype.org/content/repositories/snapshots/org/bytedeco/javacpp/1.5.11-SNAPSHOT/javacpp-1.5.11-20240211.152855-41-windows-x86_64.jar:/Users/zhanghaining/Library/Caches/Coursier/v1/https/oss.sonatype.org/content/repositories/snapshots/org/bytedeco/openblas-platform/0.3.26-1.5.11-SNAPSHOT/openblas-platform-0.3.26-1.5.11-20240130.093148-17.jar:/Users/zhanghaining/Library/Caches/Coursier/v1/https/oss.sonatype.org/content/repositories/snapshots/org/bytedeco/openblas/0.3.26-1.5.11-SNAPSHOT/openblas-0.3.26-1.5.11-20240129.142557-11-android-arm64.jar:/Users/zhanghaining/Library/Caches/Coursier/v1/https/oss.sonatype.org/content/repositories/snapshots/org/bytedeco/openblas/0.3.26-1.5.11-SNAPSHOT/openblas-0.3.26-1.5.11-20240129.142557-11-android-x86_64.jar:/Users/zhanghaining/Library/Caches/Coursier/v1/https/oss.sonatype.org/content/repositories/snapshots/org/bytedeco/openblas/0.3.26-1.5.11-SNAPSHOT/openblas-0.3.26-1.5.11-20240129.142557-11-ios-arm64.jar:/Users/zhanghaining/Li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SimpleMNIST
Exception in thread "main" java.lang.NullPointerException: Pointer address of argument 0 is NULL.
	at org.bytedeco.pytorch.ChunkBatchSharedBatchDataset.map(Native Method)
	at SimpleMNIST$.main(example.scala:57)
	at SimpleMNIST.main(example.scala)

[HGuillemet]

The ExampleStack and TensorExampleStack classes have lost their native constructors in 2.1.2-1.5.10.
They are back in PR #1466.
Can you work around that in the meantime, for your needs ?
Maybe using the new DataLoader classes ?

[mullerhai]

The ExampleStack and TensorExampleStack classes have lost their native constructors in 2.1.2-1.5.10. They are back in PR #1466. Can you work around that in the meantime, for your needs ? Maybe using the new DataLoader classes ?

oh，rollback the code，then could we update 2.1.2-1.5.10 Maven public repo with our has test and correct code ？thanks

[HGuillemet]

Maybe can we release a 2.2.0-1.5.10 version based on PR 1466. What do you think @saudet ?

[saudet]

No, please report issues like that before the release, not after