def hetero2homo_graph(hetero_graph,mol):
rd_mol = mol
rdkit.Chem.SanitizeMol(rd_mol)
atom_featurizer = CanonicalAtomFeaturizer()
### convert DGL hetero graph to DGL graph
homo_graph = dgl.DGLGraph()
homo_graph.from_networkx(hetero_graph.to_networkx())
homo_graph.ndata.update(atom_featurizer(rd_mol))
homo_graph.edata['e'] = hetero_graph.edata['distance']
return homo_graph
from utils import chirality
GCN_Tox21 = {
'random_seed': 0,
'batch_size': 128,
'lr': 1e-3,
'num_epochs': 100,
'atom_data_field': 'h',
'frac_train': 0.8,
'frac_val': 0.1,
'frac_test': 0.1,
'in_feats': 74,
'gcn_hidden_feats': [64, 64],
'classifier_hidden_feats': 64,
'patience': 10,
'atom_featurizer': CanonicalAtomFeaturizer(),
'metric_name': 'roc_auc'
}
GAT_Tox21 = {
'random_seed': 0,
'batch_size': 128,
'lr': 1e-3,
'num_epochs': 100,
'atom_data_field': 'h',
'frac_train': 0.8,
'frac_val': 0.1,
'frac_test': 0.1,
'in_feats': 74,
'gat_hidden_feats': [32, 32],
'classifier_hidden_feats': 64,
def smiles_to_dgl_graph(
smiles_str: str,
node_featurizer: BaseAtomFeaturizer = CanonicalAtomFeaturizer()
) -> DGLGraph:
return smiles_to_bigraph(smiles_str, atom_featurizer=node_featurizer)