In my customized dataset there are only feature matrices and adjacency matrices.The feature matrix is a 4000×3000 one-dimensional tensor,and edge_index is torch.Size([2, 18708])
My code is :

from torch_geometric.data import Data
data = Data(x=features,edge_index=edge_index.t().contiguous())
from torch_geometric.data import DataLoader
loader = DataLoader(data,batch_size=128,shuffle=True)
for batch in loader:
    batch

bug is :

File ~/miniconda3/envs/spacel/lib/python3.8/site-packages/torch/utils/data/dataloader.py:521, in _BaseDataLoaderIter.__next__(self)
    519 if self._sampler_iter is None:
    520     self._reset()
--> 521 data = self._next_data()
    522 self._num_yielded += 1
    523 if self._dataset_kind == _DatasetKind.Iterable and 
    524         self._IterableDataset_len_called is not None and 
    525         self._num_yielded > self._IterableDataset_len_called:

File ~/miniconda3/envs/spacel/lib/python3.8/site-packages/torch/utils/data/dataloader.py:561, in _SingleProcessDataLoaderIter._next_data(self)
    559 def _next_data(self):
    560     index = self._next_index()  # may raise StopIteration
--> 561     data = self._dataset_fetcher.fetch(index)  # may raise StopIteration
    562     if self._pin_memory:
    563         data = _utils.pin_memory.pin_memory(data)

File ~/miniconda3/envs/spacel/lib/python3.8/site-packages/torch/utils/data/_utils/fetch.py:49, in _MapDatasetFetcher.fetch(self, possibly_batched_index)
     47 def fetch(self, possibly_batched_index):
     48     if self.auto_collation:
...
File ~/miniconda3/envs/spacel/lib/python3.8/site-packages/torch_geometric/data/storage.py:111, in BaseStorage.__getitem__(self, key)
    110 def __getitem__(self, key: str) -> Any:
--> 111     return self._mapping[key]

KeyError: 0

Why is there this bug?And how to fix it.