Comments (3)
Seems to be related to this issue: #14
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Now, I have a new question:
Traceback (most recent call last):
File "D:/g/project/Expression2graph/learndxs/S_Pretra/my_pretrain_combine.py", line 309, in
main()
File "D:/g/project/Expression2graph/learndxs/S_Pretra/my_pretrain_combine.py", line 299, in main
train_loss, train_acc_node = train(args, model_list, loader, optimizer_list, device)
File "D:/g/project/Expression2graph/learndxs/S_Pretra/my_pretrain_combine.py", line 55, in train
node_rep = model(batch.x, batch.edge_index, batch.edge_attr)
File "C:\Users\11708\Desktop\minikangda\envs\pytorch\lib\site-packages\torch\nn\modules\module.py", line 550, in call
result = self.forward(*input, **kwargs)
File "D:\g\project\Expression2graph\learndxs\S_Pretra\my_model.py", line 290, in forward
h = self.gnns[layer](h_list[layer], edge_index, edge_attr)
File "C:\Users\11708\Desktop\minikangda\envs\pytorch\lib\site-packages\torch\nn\modules\module.py", line 550, in call
result = self.forward(*input, **kwargs)
File "D:\g\project\Expression2graph\learndxs\S_Pretra\my_model.py", line 54, in forward
return self.propagate(edge_index, x=x, edge_attr=edge_embeddings)
TypeError: propagate() missing 1 required positional argument: 'edge_index'
from pretrain-gnns.
Hello,
Have you solved your first problem yet? I tried the method in #14 but still cannot solve it. Do you have any suggestions?
from pretrain-gnns.
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