TypeError: propagate() got an unexpected keyword argument 'input'

[zhangyxrepo]

Hi @migalkin , thanks for open-sourcing this great work, but I countered an issue when I was trying to run this demo on GPU by:

python script/run.py -c /home/ULTRA/config/transductive/inference.yaml --dataset CoDExSmall --epochs 0 --bpe null --gpus [0] --ckpt /home/ULTRA/ckpts/ultra_4g.pth

Specifically, the output and error message is:

18:04:55   Random seed: 1024
18:04:55   Config file: /home/ULTRA/config/transductive/inference.yaml
18:04:55   {'checkpoint': '/home/ULTRA/ckpts/ultra_4g.pth',
 'dataset': {'class': 'CoDExSmall', 'root': '~/git/ULTRA/kg-datasets/'},
 'model': {'class': 'Ultra',
           'entity_model': {'aggregate_func': 'sum',
                            'class': 'EntityNBFNet',
                            'hidden_dims': [64, 64, 64, 64, 64, 64],
                            'input_dim': 64,
                            'layer_norm': True,
                            'message_func': 'distmult',
                            'short_cut': True},
           'relation_model': {'aggregate_func': 'sum',
                              'class': 'RelNBFNet',
                              'hidden_dims': [64, 64, 64, 64, 64, 64],
                              'input_dim': 64,
                              'layer_norm': True,
                              'message_func': 'distmult',
                              'short_cut': True}},
 'optimizer': {'class': 'AdamW', 'lr': 0.0005},
 'output_dir': '~/git/ULTRA/output',
 'task': {'adversarial_temperature': 1,
          'metric': ['mr', 'mrr', 'hits@1', 'hits@3', 'hits@10'],
          'name': 'TransductiveInference',
          'num_negative': 256,
          'strict_negative': True},
 'train': {'batch_per_epoch': None,
           'batch_size': 8,
           'gpus': [0],
           'log_interval': 100,
           'num_epoch': 0}}
18:04:55   CoDExSmall dataset
18:04:55   #train: 32888, #valid: 1827, #test: 1828
18:04:56   >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>
18:04:56   Evaluate on valid
Traceback (most recent call last):
  File "/home/ULTRA/script/run.py", line 297, in <module>
    test(cfg, model, valid_data, filtered_data=val_filtered_data, device=device, logger=logger)
  File "/home/miniconda3/envs/pt201py39/lib/python3.9/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
    return func(*args, **kwargs)
  File "/home/ULTRA/script/run.py", line 136, in test
    t_pred = model(test_data, t_batch)
  File "/home/miniconda3/envs/pt201py39/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
    return forward_call(*args, **kwargs)
  File "/home/ULTRA/ultra/models.py", line 23, in forward
    relation_representations = self.relation_model(data.relation_graph, query=query_rels)
  File "/home/miniconda3/envs/pt201py39/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
    return forward_call(*args, **kwargs)
  File "/home/ULTRA/ultra/models.py", line 100, in forward
    output = self.bellmanford(rel_graph, h_index=query)["node_feature"]  # (batch_size, num_nodes, hidden_dim）
  File "/home/ULTRA/ultra/models.py", line 76, in bellmanford
    hidden = layer(layer_input, query, boundary, data.edge_index, data.edge_type, size, edge_weight)
  File "/home/miniconda3/envs/pt201py39/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
    return forward_call(*args, **kwargs)
  File "/home/ULTRA/ultra/layers.py", line 86, in forward
    output = self.propagate(input=input, relation=relation, boundary=boundary, edge_index=edge_index,

This should be an obvious problem, but no one seems to have encountered it before according to issues of this repo, which puzzles me.
Thanks for your reply in advance!

[migalkin]

Hi, which version of PyG are you using?

[zhangyxrepo]

Hi, which version of PyG are you using?

hi @migalkin , my pyg version is 2.5.0 and torch version is 2.1.0

[migalkin]

Yeah, that's a known bug with pyg 2.5.0 - I'd recommend either downgrading pyg to 2.4.0 or upgrading to anything >= 2.5.2

[zhangyxrepo]

Yeah, that's a known bug with pyg 2.5.0 - I'd recommend either downgrading pyg to 2.4.0 or upgrading to anything >= 2.5.2

Hi @migalkin, thanks for your reply in time, but this error still exists after I upgraded Pig to 2.5.2. In fact, the only difference between our environments lies in the CUDA Driver version. Mine is 11.7, but it seems that you recommend running under 11.8. Could it be a possible reason?

[migalkin]

No, this is a pyg version issue, try 2.4.0 as in requirements.txt or the latest 2.6.1?

[zhangyxrepo]

No, this is a pyg version issue, try 2.4.0 as in requirements.txt or the latest 2.6.1?

@migalkin After I downgraded pyg to 2.4.0, this problem no longer seems to occur, but new problems have appeared. Specifically, when I run:

python script/run.py -c /home/ULTRA/config/transductive/inference.yaml --dataset CoDExSmall --epochs 0 --bpe null --gpus [0] --ckpt /home/ULTRA/ckpts/ultra_4g.pth

it will counter a compile error:

...
16:25:30   CoDExSmall dataset
16:25:30   #train: 32888, #valid: 1827, #test: 1828
16:25:30   >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>
16:25:30   Evaluate on valid
Load rspmm extension. This may take a while...
Traceback (most recent call last):
  File "/home/ULTRA/script/run.py", line 297, in <module>
    test(cfg, model, valid_data, filtered_data=val_filtered_data, device=device, logger=logger)
  File "/home/miniconda3/envs/pt201pg240/lib/python3.9/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
    return func(*args, **kwargs)
  File "/home/ULTRA/script/run.py", line 136, in test
    t_pred = model(test_data, t_batch)
  File "/home/miniconda3/envs/pt201pg240/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
    return forward_call(*args, **kwargs)
  File "/home/ULTRA/ultra/models.py", line 23, in forward
    relation_representations = self.relation_model(data.relation_graph, query=query_rels)
  File "/home/miniconda3/envs/pt201pg240/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
    return forward_call(*args, **kwargs)
  File "/home/ULTRA/ultra/models.py", line 100, in forward
    output = self.bellmanford(rel_graph, h_index=query)["node_feature"]  # (batch_size, num_nodes, hidden_dim）
  File "/home/ULTRA/ultra/models.py", line 76, in bellmanford
    hidden = layer(layer_input, query, boundary, data.edge_index, data.edge_type, size, edge_weight)
  File "/home/miniconda3/envs/pt201pg240/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
    return forward_call(*args, **kwargs)
  File "/home/ULTRA/ultra/layers.py", line 86, in forward
    output = self.propagate(input=input, relation=relation, boundary=boundary, edge_index=edge_index,
  File "/hom/ULTRA/ultra/layers.py", line 118, in propagate
    out = self.message_and_aggregate(edge_index, **msg_aggr_kwargs)
  File "/home/ULTRA/ultra/layers.py", line 187, in message_and_aggregate
    from .rspmm import generalized_rspmm
  File "/home/ULTRA/ultra/rspmm/__init__.py", line 1, in <module>
    from .rspmm import generalized_rspmm
  File "/home/ULTRA/ultra/rspmm/rspmm.py", line 207, in <module>
    rspmm = load_extension("rspmm", [os.path.join(path, "rspmm.cpp"), os.path.join(path, "rspmm.cu")])
  File "/home/ULTRA/ultra/rspmm/rspmm.py", line 202, in load_extension
    return cpp_extension.load(name, sources, extra_cflags, extra_cuda_cflags, **kwargs)
  File "/home/miniconda3/envs/pt201pg240/lib/python3.9/site-packages/torch/utils/cpp_extension.py", line 1284, in load
    return _jit_compile(
  File "/home/miniconda3/envs/pt201pg240/lib/python3.9/site-packages/torch/utils/cpp_extension.py", line 1535, in _jit_compile
    return _import_module_from_library(name, build_directory, is_python_module)
  File "/home/miniconda3/envs/pt201pg240/lib/python3.9/site-packages/torch/utils/cpp_extension.py", line 1929, in _import_module_from_library
    module = importlib.util.module_from_spec(spec)
ImportError: /home/.cache/torch_extensions/py39_cu117/rspmm/rspmm.so: cannot open shared object file: No such file or directory

I looked through the README of this repo but I still don't understand why, could you help me on this?

[migalkin]

You need to clean the cache of previously compiled kernels (and other jit-compiled code from previous pyg versions), delete the /home/.cache/torch_extensions/ folder, and kernels will be re-built upon the next launch

[zhangyxrepo]

You need to clean the cache of previously compiled kernels (and other jit-compiled code from previous pyg versions), delete the /home/.cache/torch_extensions/ folder, and kernels will be re-built upon the next launch

I did clean the cache by

rm -rf /home/.cache/*

but what is weird is that it didn't work as expected and the error still exists.

[migalkin]

Looking at the error trace, it appears that the previously compiled python code (.pyc files) asks for older kernels, the best approach would be to remove the repo entirely and just make a clean clone and start again (a more tedious approach is to remove all *.pyc files and __pycache__ folders everywhere in the repo).

Besides, I see your env name is pt201pg240 - does it mean you are on PyTorch 2.0.1? The minimal required torch version for Ultra is 2.1.0, please make sure you install correct package versions in your env according to requirements.txt