[NeurIPS 2020] "Graph Contrastive Learning with Augmentations" by Yuning You, Tianlong Chen, Yongduo Sui, Ting Chen, Zhangyang Wang, Yang Shen
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ValueError: `MessagePassing.propagate` only supports `torch.LongTensor` of shape `[2, num_messages]` or `torch_sparse.SparseTensor` for argument `edge_index`. #53
Hi! Thanks for the amazing work and released code. They are really interesting.
When I run ./transferLearning_MoleculeNet_PPI/chem/pretrain_graphcl.py, the error occur.
When I print it, i got the value of edge_index, but it is a str "add" instead of a tensor. Can someone help me?
Traceback (most recent call last):
File "pretrain_graphcl.py", line 185, in
main()
File "pretrain_graphcl.py", line 176, in main
train_acc, train_loss = train(args, model, device, dataset, optimizer)
File "pretrain_graphcl.py", line 103, in train
x1 = model.forward_cl(batch1.x, batch1.edge_index, batch1.edge_attr, batch1.batch)
File "pretrain_graphcl.py", line 61, in forward_cl
x = self.gnn(x, edge_index, edge_attr)
File "/opt/anaconda3/envs/torch170/lib/python3.7/site-packages/torch/nn/modules/module.py", line 727, in _call_impl
result = self.forward(*input, *kwargs)
File "/root/GSSL/Molecular/GraphCL/transferLearning_MoleculeNet_PPI/chem/model.py", line 277, in forward
h = self.gnns[layer](h_list[layer], edge_index, edge_attr)
File "/opt/anaconda3/envs/torch170/lib/python3.7/site-packages/torch/nn/modules/module.py", line 727, in _call_impl
result = self.forward(input, **kwargs)
File "/root/GSSL/Molecular/GraphCL/transferLearning_MoleculeNet_PPI/chem/model.py", line 55, in forward
return self.propagate(self.aggr, edge_index, x=x, edge_attr=edge_embeddings)
File "/opt/anaconda3/envs/torch170/lib/python3.7/site-packages/torch_geometric/nn/conv/message_passing.py", line 272, in propagate
size = self.check_input__(edge_index, size)
File "/opt/anaconda3/envs/torch170/lib/python3.7/site-packages/torch_geometric/nn/conv/message_passing.py", line 158, in check_input__
('MessagePassing.propagate only supports torch.LongTensor of '
ValueError: MessagePassing.propagate only supports torch.LongTensor of shape [2, num_messages] or torch_sparse.SparseTensor for argument edge_index.
Hi! Thanks for the amazing work and released code. They are really interesting. When I run ./transferLearning_MoleculeNet_PPI/chem/pretrain_graphcl.py, the error occur. When I print it, i got the value of edge_index, but it is a str "add" instead of a tensor. Can someone help me? Traceback (most recent call last): File "pretrain_graphcl.py", line 185, in
main()
File "pretrain_graphcl.py", line 176, in main
train_acc, train_loss = train(args, model, device, dataset, optimizer)
File "pretrain_graphcl.py", line 103, in train
x1 = model.forward_cl(batch1.x, batch1.edge_index, batch1.edge_attr, batch1.batch)
File "pretrain_graphcl.py", line 61, in forward_cl
x = self.gnn(x, edge_index, edge_attr)
File "/opt/anaconda3/envs/torch170/lib/python3.7/site-packages/torch/nn/modules/module.py", line 727, in _call_impl
result = self.forward(*input, *kwargs)
File "/root/GSSL/Molecular/GraphCL/transferLearning_MoleculeNet_PPI/chem/model.py", line 277, in forward
h = self.gnns[layer](h_list[layer], edge_index, edge_attr)
File "/opt/anaconda3/envs/torch170/lib/python3.7/site-packages/torch/nn/modules/module.py", line 727, in _call_impl
result = self.forward(input, **kwargs)
File "/root/GSSL/Molecular/GraphCL/transferLearning_MoleculeNet_PPI/chem/model.py", line 55, in forward
return self.propagate(self.aggr, edge_index, x=x, edge_attr=edge_embeddings)
File "/opt/anaconda3/envs/torch170/lib/python3.7/site-packages/torch_geometric/nn/conv/message_passing.py", line 272, in propagate
size = self.check_input__(edge_index, size)
File "/opt/anaconda3/envs/torch170/lib/python3.7/site-packages/torch_geometric/nn/conv/message_passing.py", line 158, in check_input__
('
MessagePassing.propagate
only supportstorch.LongTensor
of ' ValueError:MessagePassing.propagate
only supportstorch.LongTensor
of shape[2, num_messages]
ortorch_sparse.SparseTensor
for argumentedge_index
.