ptrblck:

pixel_values = pixel_values.view(pixel_values.size(0), -1)
x = torch.cat([pos, pixel_values], dim=1)





RuntimeError                              Traceback (most recent call last)
/tmp/ipykernel_58/426753045.py in 
126
127 if name==“main”:
 → 128     main()
/tmp/ipykernel_58/426753045.py in main()
76             batch = batch.to(“cuda”)
77             optimizer.zero_grad()
—> 78             outputs = model(batch)
79             loss = criterion(outputs,batch.tensor)
80             loss.backward()
/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py in _call_impl(self, *input, **kwargs)
1100         if not (self._backward_hooks or self._forward_hooks or self._forward_pre_hooks or _global_backward_hooks
1101                 or _global_forward_hooks or _global_forward_pre_hooks):
 → 1102             return forward_call(*input, **kwargs)
1103         # Do not call functions when jit is used
1104         full_backward_hooks, non_full_backward_hooks = [], []
/tmp/ipykernel_58/426753045.py in forward(self, data)
30         x = torch.cat([data.pos, pixel_values], dim=1)
31         x, edge_index = x, data.edge_index
—> 32         x = self.conv1(x, edge_index)
33         x = F.relu(x)
34         x = self.conv2(x, edge_index)
/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py in _call_impl(self, *input, **kwargs)
1100         if not (self._backward_hooks or self._forward_hooks or self._forward_pre_hooks or _global_backward_hooks
1101                 or _global_forward_hooks or _global_forward_pre_hooks):
 → 1102             return forward_call(*input, **kwargs)
1103         # Do not call functions when jit is used
1104         full_backward_hooks, non_full_backward_hooks = [], []
/usr/local/lib/python3.8/dist-packages/torch_geometric/nn/conv/gcn_conv.py in forward(self, x, edge_index, edge_weight)
180                     edge_index = cache
181
 → 182         x = self.lin(x)
183
184         # propagate_type: (x: Tensor, edge_weight: OptTensor)
/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py in _call_impl(self, *input, **kwargs)
1100         if not (self._backward_hooks or self._forward_hooks or self._forward_pre_hooks or _global_backward_hooks
1101                 or _global_forward_hooks or _global_forward_pre_hooks):
 → 1102             return forward_call(*input, **kwargs)
1103         # Do not call functions when jit is used
1104         full_backward_hooks, non_full_backward_hooks = [], []
/usr/local/lib/python3.8/dist-packages/torch_geometric/nn/dense/linear.py in forward(self, x)
107     def forward(self, x: Tensor) → Tensor:
108         “”""""
 → 109         return F.linear(x, self.weight, self.bias)
110
111     @torch.no_grad()
/usr/local/lib/python3.8/dist-packages/torch/nn/functional.py in linear(input, weight, bias)
1846     if has_torch_function_variadic(input, weight, bias):
1847         return handle_torch_function(linear, (input, weight, bias), input, weight, bias=bias)
 → 1848     return torch._C._nn.linear(input, weight, bias)
1849
1850
RuntimeError: mat1 and mat2 shapes cannot be multiplied (8x6220802 and 3x64)