index_select() received an invalid combination of arguments

[elissaross]

Hello!

I'm trying to run the MNIST example, but running into the following error. Any insights?

`---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
in
82
83 for epoch in range(1, 20):
---> 84 loss = train(epoch)
85 train_acc = test(train_loader)
86 test_acc = test(test_loader)

in train(epoch)
59 # data = rotation_2(data)
60 print(data.edge_index)
---> 61 output = model(data)
62 loss = F.nll_loss(output, data.y)
63 loss.backward()

/opt/tljh/user/lib/python3.6/site-packages/torch/nn/modules/module.py in call(self, *input, **kwargs)
530 result = self._slow_forward(*input, **kwargs)
531 else:
--> 532 result = self.forward(*input, **kwargs)
533 for hook in self._forward_hooks.values():
534 hook_result = hook(self, input, result)

in forward(self, data)
24 def forward(self, data):
25 for i in range(self.layers_num):
---> 26 data.x = self.conv_layers[i](data.x, data.pos, data.edge_index)
27
28 if self.use_cluster_pooling:

/opt/tljh/user/lib/python3.6/site-packages/torch/nn/modules/module.py in call(self, *input, **kwargs)
530 result = self._slow_forward(*input, **kwargs)
531 else:
--> 532 result = self.forward(*input, **kwargs)
533 for hook in self._forward_hooks.values():
534 hook_result = hook(self, input, result)

in forward(self, x, pos, edge_index)
22 edge_index = add_self_loops(edge_index, num_nodes=x.size(0)) # num_edges = num_edges + num_nodes
23
---> 24 return self.propagate(edge_index=edge_index, x=x, pos=pos, aggr='add') # [N, out_channels, label_dim]
25
26 def message(self, pos_i, pos_j, x_j):

~/.local/lib/python3.6/site-packages/torch_geometric/nn/conv/message_passing.py in propagate(self, edge_index, size, **kwargs)
165 assert len(size) == 2
166
--> 167 kwargs = self.collect(edge_index, size, kwargs)
168
169 msg_kwargs = self.distribute(self.msg_params, kwargs)

~/.local/lib/python3.6/site-packages/torch_geometric/nn/conv/message_passing.py in collect(self, edge_index, size, kwargs)
113
114 self.set_size(size, idx, data)
--> 115 out[arg] = data.index_select(self.node_dim, edge_index[idx])
116
117 size[0] = size[1] if size[0] is None else size[0]

TypeError: index_select() received an invalid combination of arguments - got (int, NoneType), but expected one of:

• (name dim, Tensor index)
  didn't match because some of the arguments have invalid types: (!int!, !NoneType!)
• (int dim, Tensor index)
  didn't match because some of the arguments have invalid types: (int, !NoneType!)`

[viduzz84]

Hi
I ran into the same problem these days and finally discover that the function add_self_loops in graph_conv.py, line 28, returns two arguments and you need the first one, so modify the call with:
edge_index, _ = add_self_loops(edge_index, num_nodes=x.size(0))

[elissaross]

Yes! I discovered the same fix -- thanks for your comment!