Preprocessing with deepchem. Issue with positions

[KeremKurban]

I was runing train.py with recent installation of libraries. I think there is a mismatch of versions such that im getting

 File "../venv2023/lib/python3.8/site-packages/deepchem/feat/graph_data.py", line 151, in to_pyg_graph
    return Data(x=torch.from_numpy(self.node_features).float(),
TypeError: type object got multiple values for keyword argument 'pos'

I found a workaround by ignoring the positional information since f=featurizer._featurize(mol) later shows:

>>>f
GraphData(node_features=[75, 30], edge_index=[2, 162], edge_features=[162, 11], pos=[0])

The workaround is to write a custom function to convert into pyg_graph from f

    def _custom_to_pyg_graph(self,graph_data):
        from torch_geometric.data import Data
        return Data(x=torch.from_numpy(graph_data.node_features).float(),
                    edge_index=torch.from_numpy(graph_data.edge_index).long(),
                    edge_attr=torch.from_numpy(graph_data.edge_features).float())

    def process(self):
        self.data = pd.read_csv(self.raw_paths[0]).reset_index()
        featurizer = dc.feat.MolGraphConvFeaturizer(use_edges=True)
        for index, row in tqdm(self.data.iterrows(), total=self.data.shape[0]):
            # Featurize molecule
            mol = Chem.MolFromSmiles(row["smiles"])
            f = featurizer._featurize(mol)
            data = self._custom_to_pyg_graph(f)
            # data = f.to_pyg_graph()
            data.y = self._get_label(row["HIV_active"])
            data.smiles = row["smiles"]
            if self.test:
                torch.save(data, 
                    os.path.join(self.processed_dir, 
                                 f'data_test_{index}.pt'))
            else:
                torch.save(data, 
                    os.path.join(self.processed_dir, 
                                 f'data_{index}.pt'))

So far it is working in processing. But future versions with positions included needs to considered for general purpose solution.

Also, perhaps requirements didnt have some of the toolboxes like deepchem , providing a version for each tool or dockerizing the venv you have used could help.

[mahsayazdani]

@KeremKurban Thanks for the solution. I had the exact same problem.