I was trying the script in dgl-lifesci/examples/property_prediction/moleculenet for molecular property prediction. I got the following error when running command python classification.py -d ClinTox -mo gin_supervised_masking
Using backend: pytorch
Directory classification_results already exists.
Processing dgl graphs from scratch...
Traceback (most recent call last):
File "classification.py", line 186, in
n_jobs=1 if args['num_workers'] == 0 else args['num_workers'])
File "/export/scratch/Zeren/conda/lib/python3.7/site-packages/dgllife/data/clintox.py", line 109, in init
n_jobs=n_jobs)
File "/export/scratch/Zeren/conda/lib/python3.7/site-packages/dgllife/data/csv_dataset.py", line 78, in init
load, log_every, init_mask, n_jobs, error_log)
File "/export/scratch/Zeren/conda/lib/python3.7/site-packages/dgllife/data/csv_dataset.py", line 139, in _pre_process
edge_featurizer=edge_featurizer))
File "/export/scratch/Zeren/conda/lib/python3.7/site-packages/dgllife/utils/mol_to_graph.py", line 375, in smiles_to_bigraph
canonical_atom_order, explicit_hydrogens, num_virtual_nodes)
File "/export/scratch/Zeren/conda/lib/python3.7/site-packages/dgllife/utils/mol_to_graph.py", line 276, in mol_to_bigraph
canonical_atom_order, explicit_hydrogens, num_virtual_nodes)
File "/export/scratch/Zeren/conda/lib/python3.7/site-packages/dgllife/utils/mol_to_graph.py", line 90, in mol_to_graph
g.ndata.update(node_featurizer(mol))
File "/export/scratch/Zeren/conda/lib/python3.7/site-packages/dgllife/utils/featurizers.py", line 1293, in call
self._atomic_number_types.index(atom.GetAtomicNum()),
ValueError: 0 is not in list
It seems that there exist atoms in the ClinTox dataset that return 0 when calling GetAtomicNum() that is out of the default atomic_number_types of PretrainAtomFeaturizer(). The problem could be resolved by passing node_featurizer=PretrainAtomFeaturizer(atomic_number_types=list(range(119))) when constructing the ClinTox dataset. But not sure what does a 0 atomic number mean.
Hi,
I was trying the script in dgl-lifesci/examples/property_prediction/moleculenet for molecular property prediction. I got the following error when running command
python classification.py -d ClinTox -mo gin_supervised_masking
It seems that there exist atoms in the ClinTox dataset that return 0 when calling GetAtomicNum() that is out of the default atomic_number_types of PretrainAtomFeaturizer(). The problem could be resolved by passing node_featurizer=PretrainAtomFeaturizer(atomic_number_types=list(range(119))) when constructing the ClinTox dataset. But not sure what does a 0 atomic number mean.