GNN Explainer example not running

[Everyday-seu]

hello dear,

I tried to run gnn_explainer example. I am getting the following error.

Traceback (most recent call last):
File "D:\Anaconda3\lib\site-packages\IPython\core\interactiveshell.py", line 2961, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "", line 1, in
runfile('D:/PycharmProjects/HGT_test/GNNExplainer.py', wdir='D:/PycharmProjects/HGT_test')
File "D:\JetBrains\PyCharm 2021.2.2\plugins\python\helpers\pydev_pydev_bundle\pydev_umd.py", line 198, in runfile
pydev_imports.execfile(filename, global_vars, local_vars) # execute the script
File "D:\JetBrains\PyCharm 2021.2.2\plugins\python\helpers\pydev_pydev_imps_pydev_execfile.py", line 18, in execfile
exec(compile(contents+"\n", file, 'exec'), glob, loc)
File "D:/PycharmProjects/HGT_test/GNNExplainer.py", line 48, in
edge_weight=edge_weight)
File "D:\Anaconda3\lib\site-packages\torch_geometric\nn\models\gnn_explainer.py", line 208, in explain_node
prediction = self.get_initial_prediction(x, edge_index, **kwargs)
File "D:\Anaconda3\lib\site-packages\torch\autograd\grad_mode.py", line 28, in decorate_context
return func(*args, **kwargs)
File "D:\Anaconda3\lib\site-packages\torch_geometric\nn\models\explainer.py", line 235, in get_initial_prediction
out = self.model(x, edge_index, **kwargs)
File "D:\Anaconda3\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "D:/PycharmProjects/HGT_test/GNNExplainer.py", line 25, in forward
x = F.relu(self.conv1(x, edge_index, edge_weight))
File "D:\Anaconda3\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "D:\Anaconda3\lib\site-packages\torch_geometric\nn\conv\gcn_conv.py", line 195, in forward
size=None)
File "D:\Anaconda3\lib\site-packages\torch_geometric\nn\conv\message_passing.py", line 317, in propagate
out = self.message(**msg_kwargs)
File "D:\Anaconda3\lib\site-packages\torch_geometric\nn\conv\gcn_conv.py", line 203, in message
return x_j if edge_weight is None else edge_weight.view(-1, 1) * x_j
RuntimeError: The size of tensor a (13264) must match the size of tensor b (19) at non-singleton dimension 0

I'm using torch_geometric 2.0.4

[rusty1s]

Yes, this is sadly a bug in PyG 2.0.4, but it is fixed in master. See here on how to upgrade.