AttributeError: 'int' object has no attribute 'new_full'

[firqaaa]

I have tried to run this code in colab, everything fine until i got an error when trying to run main function, here is the details :

Logging to /content/logs/TextGNN_twitter_asian_prejudice_small_0.8_0.1_0.1_2022-07-31T22-02-48.769172
Trying to load but no file /content/save/split/twitter_asian_prejudice_small_train_80_val_10_test_10_seed_3_window_size_10.klepto
Trying to load but no file /content/save/all/twitter_asian_prejudice_small_all_window_10.klepto
100%
1503/1503 [00:00<00:00, 15779.03it/s]
Saving to /content/save/all/twitter_asian_prejudice_small_all_window_10.klepto
Saving to /content/save/split/twitter_asian_prejudice_small_train_80_val_10_test_10_seed_3_window_size_10.klepto
(1183, 1183)
Number params:  237604

---

AttributeError                            Traceback (most recent call last)
[<ipython-input-22-263240bbee7e>](https://localhost:8080/#) in <module>()
----> 1 main()

9 frames
[<ipython-input-21-6463f33e79c1>](https://localhost:8080/#) in main()
     10     if COMET_EXPERIMENT:
     11         with COMET_EXPERIMENT.train():
---> 12             saved_model, model = train(train_data, val_data, saver)
     13     else:
     14         saved_model, model = train(train_data, val_data, saver)

[<ipython-input-18-4c4921548f33>](https://localhost:8080/#) in train(train_data, val_data, saver)
     18         model.train()
     19         model.zero_grad()
---> 20         loss, preds_train = model(pyg_graph, train_data)
     21         loss.backward()
     22         optimizer.step()

[/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py](https://localhost:8080/#) in _call_impl(self, *input, **kwargs)
   1128         if not (self._backward_hooks or self._forward_hooks or self._forward_pre_hooks or _global_backward_hooks
   1129                 or _global_forward_hooks or _global_forward_pre_hooks):
-> 1130             return forward_call(*input, **kwargs)
   1131         # Do not call functions when jit is used
   1132         full_backward_hooks, non_full_backward_hooks = [], []

[<ipython-input-14-a3723756fb22>](https://localhost:8080/#) in forward(self, pyg_graph, dataset)
     31         for i, layer in enumerate(self.layers):
     32             ins = acts[-1]
---> 33             outs = layer(ins, pyg_graph)
     34             acts.append(outs)
     35 

[/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py](https://localhost:8080/#) in _call_impl(self, *input, **kwargs)
   1128         if not (self._backward_hooks or self._forward_hooks or self._forward_pre_hooks or _global_backward_hooks
   1129                 or _global_forward_hooks or _global_forward_pre_hooks):
-> 1130             return forward_call(*input, **kwargs)
   1131         # Do not call functions when jit is used
   1132         full_backward_hooks, non_full_backward_hooks = [], []

[<ipython-input-14-a3723756fb22>](https://localhost:8080/#) in forward(self, ins, pyg_graph)
    101                 x = self.conv(ins, pyg_graph.edge_index, edge_weight=pyg_graph.edge_attr)
    102             else:
--> 103                 x = self.conv(ins, pyg_graph.edge_index)
    104         else:
    105             x = self.conv(ins, pyg_graph.edge_index)

[/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py](https://localhost:8080/#) in _call_impl(self, *input, **kwargs)
   1128         if not (self._backward_hooks or self._forward_hooks or self._forward_pre_hooks or _global_backward_hooks
   1129                 or _global_forward_hooks or _global_forward_pre_hooks):
-> 1130             return forward_call(*input, **kwargs)
   1131         # Do not call functions when jit is used
   1132         full_backward_hooks, non_full_backward_hooks = [], []

[<ipython-input-14-a3723756fb22>](https://localhost:8080/#) in forward(self, x, edge_index, edge_weight)
    254         if not self.cached or self.cached_result is None:
    255             edge_index, norm = GCNConv.norm(edge_index, x.size(0), edge_weight,
--> 256                                             self.improved, x.dtype)
    257             self.cached_result = edge_index, norm
    258 

[<ipython-input-14-a3723756fb22>](https://localhost:8080/#) in norm(edge_index, num_nodes, edge_weight, improved, dtype)
    231 
    232         edge_index, edge_weight = remove_self_loops(edge_index, edge_weight)
--> 233         edge_index = add_self_loops(edge_index, num_nodes)
    234         loop_weight = torch.full((num_nodes, ),
    235                                  1 if not improved else 2,

[/usr/local/lib/python3.7/dist-packages/torch_geometric/utils/loop.py](https://localhost:8080/#) in add_self_loops(edge_index, edge_attr, fill_value, num_nodes)
    123     if edge_attr is not None:
    124         if fill_value is None:
--> 125             loop_attr = edge_attr.new_full((N, ) + edge_attr.size()[1:], 1.)
    126 
    127         elif isinstance(fill_value, (int, float)):

AttributeError: 'int' object has no attribute 'new_full'

Why this can happen? can you give me a solution?

[NageshMashette]

can anyone give the solution, facing same issue here aswell.

[zhuluchangfeng]

in norm(edge_index, num_nodes, edge_weight, improved, dtype) 231 232 edge_index, edge_weight = remove_self_loops(edge_index, edge_weight) --> 233 edge_index = add_self_loops(edge_index, num_nodes) 234 loop_weight = torch.full((num_nodes, ), 235 1 if not improved else 2,

233行这里改成edge_index = add_self_loops(edge_index, num_nodes=num_nodes)，这里是因为num_nodes没有传递到合适的位置

[slefcourt27]

For others, make sure to install the libraries in this way: https://gist.github.com/ameya98/b193856171d11d37ada46458f60e73e7

To solve this problem, specify edge_index, _ = add_self_loops(edge_index=edge_index, num_nodes=num_nodes)