problem with dataload2 chunk

🐛 Describe the bug

Dataloader2 returned DataChunk, and can not be moved to device.

def TFRLoader(path):
    record_pipe = FileLister(path)
    file_pipe = FileOpener(record_pipe, mode="b")
    return file_pipe.load_from_tfrecord().map(tfrecord_praser).batch(batch_size)

rs = MultiProcessingReadingService(num_workers=cfg.num_workers)
train_dataloader = DataLoader2(train_dataset, reading_service=rs)

for i, d in enumerate(train_dataloader):
    d = d.to(device)

AttributeError: 'DataChunk' object has no attribute 'to'

also can not input to model

TypeError: conv2d() received an invalid combination of arguments - got (DataChunk, Parameter, Parameter, tuple, tuple, tuple, int), but expected one of:
 * (Tensor input, Tensor weight, Tensor bias, tuple of ints stride, tuple of ints padding, tuple of ints dilation, int groups)
      didn't match because some of the arguments have invalid types: (DataChunk of [Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor,

Set the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.

Currently a work around is convert chunk to tensor

d = torch.stack(d.items)

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Latest

Reproduce the TFRLoader and DataLoader2 example, then inspect how DataChunk is produced and how its items differ from the tensor expected by the model. Compare the failing .to(device) and model calls with the torch.stack(d.items) workaround. Done means the dataloader output can be moved to the device and passed to the model without that conversion.