在复现HybridSN时，出现data无法进行迭代问题 应如何解决

问题代码：

def __next__(self) -> Any:
        with torch.autograd.profiler.record_function(self._profile_name):
            if self._sampler_iter is None:
                self._reset()
            data=self._next_data()
            self._num_yielded += 1
            if self._dataset_kind == _DatasetKind.Iterable and \
                    self._IterableDataset_len_called is not None and \
                    self._num_yielded > self._IterableDataset_len_called:
                warn_msg = ("Length of IterableDataset {} was reported to be {} (when accessing len(dataloader)), but {} "
                            "samples have been fetched. ").format(self._dataset, self._IterableDataset_len_called,
                                                                  self._num_yielded)
                if self._num_workers > 0:
                    warn_msg += ("For multiprocessing data-loading, this could be caused by not properly configuring the "
                                 "IterableDataset replica at each worker. Please see "
                                 "https://pytorch.org/docs/stable/data.html#torch.utils.data.IterableDataset for examples.")
                warnings.warn(warn_msg)
        return data

报错：
Traceback (most recent call last):
File "C:\Users\Lenovo\AppData\Local\Programs\Python\Python38\lib\site-packages\torch\utils\data\dataloader.py", line 523, in next
data=self._next_data()
File "C:\Users\Lenovo\AppData\Local\Programs\Python\Python38\lib\site-packages\torch\utils\data\dataloader.py", line 1192, in _next_data
idx, data = self._get_data()
File "C:\Users\Lenovo\AppData\Local\Programs\Python\Python38\lib\site-packages\torch\utils\data\dataloader.py", line 1156, in _get_data
success,data = self._try_get_data()
TypeError: cannot unpack non-iterable NoneType object

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