Error in the BondEncoder in ogb.graphpropped.mol_encoder

[vindakunte]

I am encountering the following error while extracting bond encodings. I'm passing the edge_attr to the BondEncoder but get an index out of range error. The error message is as follows:

---

IndexError Traceback (most recent call last)
Cell In[12], line 2
1 bond_encoder = BondEncoder(emb_dim=100)
----> 2 print(bond_encoder(data.edge_attr))

File /opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py:1518, in Module._wrapped_call_impl(self, *args, **kwargs)
1516 return self._compiled_call_impl(*args, **kwargs) # type: ignore[misc]
1517 else:
-> 1518 return self._call_impl(*args, **kwargs)

File /opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py:1527, in Module._call_impl(self, *args, **kwargs)
1522 # If we don't have any hooks, we want to skip the rest of the logic in
1523 # this function, and just call forward.
1524 if not (self._backward_hooks or self._backward_pre_hooks or self._forward_hooks or self._forward_pre_hooks
1525 or _global_backward_pre_hooks or _global_backward_hooks
1526 or _global_forward_hooks or _global_forward_pre_hooks):
-> 1527 return forward_call(*args, **kwargs)
1529 try:
1530 result = None

Cell In[11], line 18, in BondEncoder.forward(self, edge_attr)
16 bond_embedding = torch.zeros_like(self.bond_embedding_list[0].weight)
17 for i in range(edge_attr.shape[1]):
---> 18 bond_embedding += self.bond_embedding_listi
20 return bond_embedding

File /opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py:1518, in Module._wrapped_call_impl(self, *args, **kwargs)
1516 return self._compiled_call_impl(*args, **kwargs) # type: ignore[misc]
1517 else:
-> 1518 return self._call_impl(*args, **kwargs)

File /opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py:1527, in Module._call_impl(self, *args, **kwargs)
1522 # If we don't have any hooks, we want to skip the rest of the logic in
1523 # this function, and just call forward.
1524 if not (self._backward_hooks or self._backward_pre_hooks or self._forward_hooks or self._forward_pre_hooks
1525 or _global_backward_pre_hooks or _global_backward_hooks
1526 or _global_forward_hooks or _global_forward_pre_hooks):
-> 1527 return forward_call(*args, **kwargs)
1529 try:
1530 result = None

File /opt/conda/lib/python3.10/site-packages/torch/nn/modules/sparse.py:162, in Embedding.forward(self, input)
161 def forward(self, input: Tensor) -> Tensor:
--> 162 return F.embedding(
163 input, self.weight, self.padding_idx, self.max_norm,
164 self.norm_type, self.scale_grad_by_freq, self.sparse)

File /opt/conda/lib/python3.10/site-packages/torch/nn/functional.py:2233, in embedding(input, weight, padding_idx, max_norm, norm_type, scale_grad_by_freq, sparse)
2227 # Note [embedding_renorm set_grad_enabled]
2228 # XXX: equivalent to
2229 # with torch.no_grad():
2230 # torch.embedding_renorm_
2231 # remove once script supports set_grad_enabled
2232 no_grad_embedding_renorm(weight, input, max_norm, norm_type)
-> 2233 return torch.embedding(weight, input, padding_idx, scale_grad_by_freq, sparse)

IndexError: index out of range in self

[vindakunte]

Is there an error in how I'm passing arguments to the BondEncoder? Following is the snippet that i'm trying to run:
train_dataset = PCQM4Mv2(root = 'dataset/', split = 'test')
val_dataset = PCQM4Mv2(root = 'dataset/', split = 'val')
print(train_dataset)
data = (train_dataset.get(12))
bond_encoder = BondEncoder(emb_dim=100)
print(bond_encoder(data.edge_attr))