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A question about Semisupervised_TU in pre_training #61
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Hi @ytpjh, The most possible reason for this issue would be the package version. Please follow https://github.com/Shen-Lab/GraphCL/tree/master/semisupervised_TU#dependencies to set up the environment. If want to directly deal with this error, I would suggest starting from Expecially, print out |
main.py 320
run_exp_benchmark()
main.py 278 run_exp_benchmark
run_exp_lib(create_n_filter_triples(datasets, feat_strs, nets,
main.py 183 run_exp_lib
cross_validation_with_val_set(
train_eval.py 115 cross_validation_with_val_set
train_loss, _ = train(
train_eval.py 234 train
out1 = model.forward_cl(data1)
res_gcn.py 173 forward_cl
return self.forward_BNConvReLU_cl(x, edge_index, batch, xg)
res_gcn.py 180 forward_BNConvReLU_cl
x_ = F.relu(conv(x_, edge_index))
module.py 1186 _call_impl
return forward_call(*input, **kwargs)
gcn_conv.py 103 forward
edge_index, norm = GCNConv.norm(
gcn_conv.py 90 norm
deg = scatter_add(edge_weight, row, dim=0, dim_size=num_nodes)
scatter.py 27 scatter_add
return scatter_sum(src, index, dim, out, dim_size)
scatter.py 9 scatter_sum
index = broadcast(index, src, dim)
utils.py 12 broadcast
src = src.expand(other.size())
RuntimeError:
expand(torch.cuda.LongTensor{[2, 12108]}, size=[12108]): the number of sizes provided (1) must be greater or equal to the number of dimensions in the tensor (2)
There is a error in scatter_add() function,this error remain that the size of src tensor is not euqal to the size of index tensor.I have tried many times but it is still not work.Could you give a solution about this question? Thanks
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