malllabiisc / asap Goto Github PK

  File "main.py", line 252, in <module>
    val_acc, test_acc   = model.run()
  File "main.py", line 167, in run
    train_loss  = self.run_epoch(train_loader)
  File "main.py", line 67, in run_epoch
    out = self.model(data)
  File "/usr1/home/rjoshi2/envs/torch140/lib/python3.7/site-packages/torch/nn/modules/module.py", line 532, in __call__
    result = self.forward(*input, **kwargs)
  File "/usr1/home/rjoshi2/negotiation_personality/src/negotiation/predict_strategy/ASAP/asap_pool_model.py", line 46, in forward
    x = F.relu(conv(x=x, edge_index=edge_index, edge_weight=edge_weight))
  File "/usr1/home/rjoshi2/envs/torch140/lib/python3.7/site-packages/torch/nn/modules/module.py", line 532, in __call__
    result = self.forward(*input, **kwargs)
  File "/usr1/home/rjoshi2/envs/torch140/lib/python3.7/site-packages/torch_geometric/nn/conv/gcn_conv.py", line 102, in forward
    x.dtype)
  File "/usr1/home/rjoshi2/envs/torch140/lib/python3.7/site-packages/torch_geometric/nn/conv/gcn_conv.py", line 83, in norm
    return edge_index, deg_inv_sqrt[row] * edge_weight * deg_inv_sqrt[col]
IndexError: index 4635 is out of bounds for dimension 0 with size 2631

((Pdb) x.shape
torch.Size([2631, 64])
(Pdb) edge_index.shape
torch.Size([2, 58576])
(Pdb) edge_weight.shape
torch.Size([58576])
(Pdb) torch.max(edge_index)
tensor(5206)
(Pdb) x = F.relu(conv(x=x, edge_index=edge_index, edge_weight=edge_weight))
*** IndexError: index 4635 is out of bounds for dimension 0 with size 2631

    if edge_weight is None:
        edge_weight = torch.ones((edge_index.size(1), ),
                                 dtype=x.dtype,
                                 device=edge_index.device)
    edge_index, edge_weight = remove_self_loops(edge_index=edge_index, edge_attr=edge_weight)
    deg = scatter_add(edge_weight, edge_index[0], dim=0, dim_size=num_nodes)  # + 1e-10

    h_j = edge_weight.view(-1, 1) * h[edge_index[1]]
    aggr_out = scatter_add(h_j, edge_index[0], dim=0, dim_size=num_nodes)
    out = ( deg.view(-1, 1) * self.lin1(x) + aggr_out) + self.lin2(x)       # ----------the question is here----------# 
    edge_index, edge_weight = add_self_loops(edge_index=edge_index, edge_weight=edge_weight, num_nodes=num_nodes)
    return out`