def METHOD_NAME(self):
    for raw_path, path in zip(self.raw_paths, self.processed_paths):
        with open(raw_path, 'rb') as f:
            graphs = pickle.load(f)
        data_list: List[Data] = []
        for graph in graphs:
            x, edge_attr, edge_index, y = graph
            x = torch.from_numpy(x)
            edge_attr = torch.from_numpy(edge_attr)
            edge_index = torch.from_numpy(edge_index)
            y = torch.tensor([y]).float()
            if edge_index.numel() == 0:
                continue  # Skipping for graphs with no bonds/edges.
            data = Data(x=x, edge_index=edge_index, edge_attr=edge_attr,
                        y=y)
            if self.pre_filter is not None and not self.pre_filter(data):
                continue
            if self.pre_transform is not None:
                data = self.pre_transform(data)
            data_list.append(data)
        torch.save(self.collate(data_list), path)