chumingqian
commented
5 months ago Hi, @ChunhuaLab : I faced the same problem, then i used this, and it's worked;
for G in G_list:
#adj = np.array(nx.to_numpy_matrix(G))
adj = np.array(nx.to_numpy_array(G))
I was trying to run the file example.sh. The first command runs fine, but it throws an exception on the second one:
$ python -m train --bmname=ENZYMES --assign-ratio=0.1 --hidden-dim=30 --output-dim=30 --cuda=1 --num-classes=6 --method=soft-assign
The output is as follows. Any idea what is going on? Given that I haven't changed anything, maybe the version of packages are different?
CUDA 1 Using node labels Num training graphs: 540 ; Num validation graphs: 60 Number of graphs: 600 Number of edges: 37282 Max, avg, std of graph size: 125 , 32.46 , 14.87 Method: soft-assign /home/sunxiaohan/paper2/diffpool-master/encoders.py:71: UserWarning: nn.init.xavier_uniform is now deprecated in favor of nn.init.xavier_uniform_. m.weight.data = init.xavier_uniform(m.weight.data, gain=nn.init.calculate_gain('relu')) /home/sunxiaohan/paper2/diffpool-master/encoders.py:73: UserWarning: nn.init.constant is now deprecated in favor of nn.init.constant_. m.bias.data = init.constant(m.bias.data, 0.0) /home/sunxiaohan/paper2/diffpool-master/encoders.py:293: UserWarning: nn.init.xavier_uniform is now deprecated in favor of nn.init.xavier_uniform_ . m.weight.data = init.xavier_uniform(m.weight.data, gain=nn.init.calculate_gain('relu')) /home/sunxiaohan/paper2/diffpool-master/encoders.py:295: UserWarning: nn.init.constant is now deprecated in favor of nn.init.constant_. m.bias.data = init.constant(m.bias.data, 0.0) Epoch: 0 Traceback (most recent call last): File "/home/sunxiaohan/anaconda3/envs/pep/lib/python3.8/runpy.py", line 194, in _run_module_as_main return _run_code(code, main_globals, None, File "/home/sunxiaohan/anaconda3/envs/pep/lib/python3.8/runpy.py", line 87, in _run_code exec(code, run_globals) File "/home/sunxiaohan/paper2/diffpool-master/train.py", line 652, in <module> main() File "/home/sunxiaohan/paper2/diffpool-master/train.py", line 640, in main benchmark_task_val(prog_args, writer=writer) File "/home/sunxiaohan/paper2/diffpool-master/train.py", line 519, in benchmark_task_val _, val_accs = train(train_dataset, model, args, val_dataset=val_dataset, test_dataset=None, File "/home/sunxiaohan/paper2/diffpool-master/train.py", line 199, in train for batch_idx, data in enumerate(dataset): File "/home/sunxiaohan/anaconda3/envs/pep/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 652, in __next__ data = self._next_data() File "/home/sunxiaohan/anaconda3/envs/pep/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 1347, in _next_data return self._process_data(data) File "/home/sunxiaohan/anaconda3/envs/pep/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 1373, in _process_data data.reraise() File "/home/sunxiaohan/anaconda3/envs/pep/lib/python3.8/site-packages/torch/_utils.py", line 461, in reraise raise exception IndexError: Caught IndexError in DataLoader worker process 0. Original Traceback (most recent call last): File "/home/sunxiaohan/anaconda3/envs/pep/lib/python3.8/site-packages/torch/utils/data/_utils/worker.py", line 302, in _worker_loop data = fetcher.fetch(index) File "/home/sunxiaohan/anaconda3/envs/pep/lib/python3.8/site-packages/torch/utils/data/_utils/fetch.py", line 49, in fetch data = [self.dataset[idx] for idx in possibly_batched_index] File "/home/sunxiaohan/anaconda3/envs/pep/lib/python3.8/site-packages/torch/utils/data/_utils/fetch.py", line 49, in <listcomp> data = [self.dataset[idx] for idx in possibly_batched_index] File "/home/sunxiaohan/paper2/diffpool-master/graph_sampler.py", line 101, in __getitem__ num_nodes = adj.shape[0] IndexError: tuple index out of range