zzaebok / kgcn-pytorch Goto Github PK

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RuntimeError                              Traceback (most recent call last)
Cell In[7], line 11
      9 user_ids, item_ids, labels = user_ids.to(device), item_ids.to(device), labels.to(device)
     10 optimizer.zero_grad()
---> 11 outputs = net(user_ids, item_ids)
     12 loss = criterion(outputs, labels)
     13 loss.backward()

File ~/miniconda3/envs/pt/lib/python3.10/site-packages/torch/nn/modules/module.py:1194, in Module._call_impl(self, *input, **kwargs)
   1190 # If we don't have any hooks, we want to skip the rest of the logic in
   1191 # this function, and just call forward.
   1192 if not (self._backward_hooks or self._forward_hooks or self._forward_pre_hooks or _global_backward_hooks
   1193         or _global_forward_hooks or _global_forward_pre_hooks):
-> 1194     return forward_call(*input, **kwargs)
   1195 # Do not call functions when jit is used
   1196 full_backward_hooks, non_full_backward_hooks = [], []

File ~/coding/KGCN-pytorch/model.py:62, in KGCN.forward(self, u, v)
     59 # [batch_size, dim]
     60 user_embeddings = self.usr(u).squeeze(dim = 1)
---> 62 entities, relations = self._get_neighbors(v)
     64 item_embeddings = self._aggregate(user_embeddings, entities, relations)
     66 scores = (user_embeddings * item_embeddings).sum(dim = 1)

File ~/coding/KGCN-pytorch/model.py:79, in KGCN._get_neighbors(self, v)
     76 relations = []
     78 for h in range(self.n_iter):
---> 79     neighbor_entities = torch.LongTensor(self.adj_ent[entities[h]]).view((self.batch_size, -1)).to(self.device)
     80     neighbor_relations = torch.LongTensor(self.adj_rel[entities[h]]).view((self.batch_size, -1)).to(self.device)
     81     entities.append(neighbor_entities)

RuntimeError: indices should be either on cpu or on the same device as the indexed tensor (CPU)

python==3.10.9
pytorch==1.13.1
pytorch-cuda==11.7