AttributeError: Can't get attribute 'DataEdgeAttr'

[xyang2316]

Hi, I followed the environment creation and when I tried to direct run the vanilla classification with the given yml, the error happened. I spent some time but still have no clue how to fix this. Could you help to look into this and help me out? Thank you so much!

(gpn) labcluster@lambda-:/data/xueyingy/Graph-Posterior-Network$ python3 train_and_eval.py with configs/gpn/classification_gpn_10.yaml data.dataset=CoraML
WARNING:root:The OGB package is out of date. Your version is 1.3.1, while the latest version is 1.3.4.
Using backend: pytorch
2022-10-25 23:30:22.619741: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
WARNING:root:Added new config entry: "data.dataset"
WARNING:root:Added new config entry: "data.ood_flag"
WARNING:root:Added new config entry: "data.root"
WARNING:root:Added new config entry: "data.split"
WARNING:root:Added new config entry: "data.split_no"
WARNING:root:Added new config entry: "data.test_samples_per_class"
WARNING:root:Added new config entry: "data.train_samples_per_class"
WARNING:root:Added new config entry: "data.val_samples_per_class"
WARNING:root:Added new config entry: "model.K"
WARNING:root:Added new config entry: "model.add_self_loops"
WARNING:root:Added new config entry: "model.alpha_evidence_scale"
WARNING:root:Added new config entry: "model.alpha_teleport"
WARNING:root:Added new config entry: "model.approximate_reg"
WARNING:root:Added new config entry: "model.dim_hidden"
WARNING:root:Added new config entry: "model.dim_latent"
WARNING:root:Added new config entry: "model.dropout_prob"
WARNING:root:Added new config entry: "model.entropy_reg"
WARNING:root:Added new config entry: "model.flow_weight_decay"
WARNING:root:Added new config entry: "model.gaussian_layers"
WARNING:root:Added new config entry: "model.init_no"
WARNING:root:Added new config entry: "model.loss_reduction"
WARNING:root:Added new config entry: "model.maf_layers"
WARNING:root:Added new config entry: "model.model_name"
WARNING:root:Added new config entry: "model.pre_train_mode"
WARNING:root:Added new config entry: "model.radial_layers"
WARNING:root:Added new config entry: "model.seed"
WARNING:root:Added new config entry: "model.use_batched_flow"
WARNING:root:Added new config entry: "run.eval_mode"
WARNING:root:Added new config entry: "run.experiment_directory"
WARNING:root:Added new config entry: "run.experiment_name"
WARNING:root:Added new config entry: "run.gpu"
WARNING:root:Added new config entry: "run.job"
WARNING:root:Added new config entry: "run.save_model"
WARNING:root:Added new config entry: "training.epochs"
WARNING:root:Added new config entry: "training.finetune_epochs"
WARNING:root:Added new config entry: "training.lr"
WARNING:root:Added new config entry: "training.stopping_metric"
WARNING:root:Added new config entry: "training.stopping_minimize"
WARNING:root:Added new config entry: "training.stopping_mode"
WARNING:root:Added new config entry: "training.stopping_patience"
WARNING:root:Added new config entry: "training.stopping_restore_best"
WARNING:root:Added new config entry: "training.warmup_epochs"
WARNING:root:Added new config entry: "training.weight_decay"
WARNING:train_and_eval:No observers have been added to this run
ERROR:train_and_eval:Failed after 0:00:00!
Traceback (most recent calls WITHOUT Sacred internals):
  File "train_and_eval.py", line 65, in run_experiment
    results = experiment.run()
  File "/data/xueyingy/Graph-Posterior-Network/gpn/experiments/multiple_run_experiment.py", line 50, in run
    results = self.run_transductive_experiment()
  File "/data/xueyingy/Graph-Posterior-Network/gpn/experiments/multiple_run_experiment.py", line 75, in run_transductive_experiment
    experiment = TransductiveExperiment(
  File "/data/xueyingy/Graph-Posterior-Network/gpn/experiments/transductive_experiment.py", line 96, in __init__
    self.dataset = ExperimentDataset(data_cfg, to_sparse=data_cfg.to_sparse)
  File "/data/xueyingy/Graph-Posterior-Network/gpn/experiments/dataset.py", line 58, in __init__
    dataset = DatasetManager(**data_cfg.to_dict())
  File "/data/xueyingy/Graph-Posterior-Network/gpn/data/dataset_manager.py", line 124, in DatasetManager
    data = D.CitationFull(root, 'Cora_ML', default_transform, None)
  File "/home/labcluster/.local/lib/python3.8/site-packages/torch_geometric/datasets/citation_full.py", line 39, in __init__
    self.data, self.slices = torch.load(self.processed_paths[0])
  File "/home/labcluster/.local/lib/python3.8/site-packages/torch/serialization.py", line 607, in load
    return _load(opened_zipfile, map_location, pickle_module, **pickle_load_args)
  File "/home/labcluster/.local/lib/python3.8/site-packages/torch/serialization.py", line 882, in _load
    result = unpickler.load()
  File "/home/labcluster/.local/lib/python3.8/site-packages/torch/serialization.py", line 875, in find_class
    return super().find_class(mod_name, name)
AttributeError: Can't get attribute 'DataEdgeAttr' on <module 'torch_geometric.data.data' from '/home/labcluster/.local/lib/python3.8/site-packages/torch_geometric/data/data.py'>

[stadlmax]

As far as I know,DataEdgeAttr is part of the more recent idea of connecting the Data class to the GraphStorage class (see PR). This definitely shouldn't be in the tagged version of 2.0.2.

I see two potential problems causing this issue

• You already have existing datasets on your machine, but from more recent PyG versions. In this case, try deleting them and downloading them again inside the gpn environment or keep two different copies and ensure that you select the right path.
• You somehow are using a different version of PyG e.g. by manually updating it inside the environment.

The issue is most likely not caused by our side as it occurs in File "/home/labcluster/.local/lib/python3.8/site-packages/torch_geometric/datasets/citation_full.py". Please check if those hints the issue solve the issue and close it eventually. Otherwise, come back to us in this thread.