Im not able to run train_author_disambiguation.py task for '_ML' nor '_CS' (OAG dataset) which fails with following error in gnn function.
Is there any known issue for this?
<ipython-input-113-17fa53d2f5f9> in <module>
9 # print(ylabel) #dic
10 gnn.forward(node_feature.to(device), node_type.to(device), edge_time.to(device), edge_index.to(device),
---> 11 edge_type.to(device))
~/SageMaker/datascience/pyHGT/OAG/pyHGT/model.py in forward(self, node_feature, node_type, edge_time, edge_index, edge_type)
77 del res
78 for gc in self.gcs:
---> 79 meta_xs = gc(meta_xs, node_type, edge_index, edge_type, edge_time)
80 return meta_xs
~/anaconda3/envs/gnn_hgt_gpu/lib/python3.6/site-packages/torch/nn/modules/module.py in _call_impl(self, *input, **kwargs)
1049 if not (self._backward_hooks or self._forward_hooks or self._forward_pre_hooks or _global_backward_hooks
1050 or _global_forward_hooks or _global_forward_pre_hooks):
-> 1051 return forward_call(*input, **kwargs)
1052 # Do not call functions when jit is used
1053 full_backward_hooks, non_full_backward_hooks = [], []
~/SageMaker/datascience/pyHGT/OAG/pyHGT/conv.py in forward(self, meta_xs, node_type, edge_index, edge_type, edge_time)
316 def forward(self, meta_xs, node_type, edge_index, edge_type, edge_time):
317 if self.conv_name == 'hgt':
--> 318 return self.base_conv(meta_xs, node_type, edge_index, edge_type, edge_time)
319 elif self.conv_name == 'gcn':
320 return self.base_conv(meta_xs, edge_index)
~/anaconda3/envs/gnn_hgt_gpu/lib/python3.6/site-packages/torch/nn/modules/module.py in _call_impl(self, *input, **kwargs)
1049 if not (self._backward_hooks or self._forward_hooks or self._forward_pre_hooks or _global_backward_hooks
1050 or _global_forward_hooks or _global_forward_pre_hooks):
-> 1051 return forward_call(*input, **kwargs)
1052 # Do not call functions when jit is used
1053 full_backward_hooks, non_full_backward_hooks = [], []
~/SageMaker/datascience/pyHGT/OAG/pyHGT/conv.py in forward(self, node_inp, node_type, edge_index, edge_type, edge_time)
57 def forward(self, node_inp, node_type, edge_index, edge_type, edge_time):
58 return self.propagate(edge_index, node_inp=node_inp, node_type=node_type, \
---> 59 edge_type=edge_type, edge_time = edge_time)
60
61 def message(self, edge_index_i, node_inp_i, node_inp_j, node_type_i, node_type_j, edge_type, edge_time):
~/anaconda3/envs/gnn_hgt_gpu/lib/python3.6/site-packages/torch_geometric/nn/conv/message_passing.py in propagate(self, edge_index, size, **kwargs)
308
309 coll_dict = self.__collect__(self.__user_args__, edge_index,
--> 310 size, kwargs)
311
312 msg_kwargs = self.inspector.distribute('message', coll_dict)
~/anaconda3/envs/gnn_hgt_gpu/lib/python3.6/site-packages/torch_geometric/nn/conv/message_passing.py in __collect__(self, args, edge_index, size, kwargs)
198
199 if isinstance(data, Tensor):
--> 200 self.__set_size__(size, dim, data)
201 data = self.__lift__(data, edge_index,
202 j if arg[-2:] == '_j' else i)
~/anaconda3/envs/gnn_hgt_gpu/lib/python3.6/site-packages/torch_geometric/nn/conv/message_passing.py in __set_size__(self, size, dim, src)
161 if the_size is None:
162 size[dim] = src.size(self.node_dim)
--> 163 elif the_size != src.size(self.node_dim):
164 raise ValueError(
165 (f'Encountered tensor with size {src.size(self.node_dim)} in '
IndexError: Dimension out of range (expected to be in range of [-1, 0], but got -2)```
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Im not able to run train_author_disambiguation.py task for '_ML' nor '_CS' (OAG dataset) which fails with following error in gnn function. Is there any known issue for this?