code: def process(self):
      add_inverse_edge = self.meta_info["add_inverse_edge"] == "True"
  
      if self.meta_info["additional node files"] == "None":
          additional_node_files = []
      else:
          additional_node_files = self.meta_info[
              "additional node files"
          ].split(",")
  
      if self.meta_info["additional edge files"] == "None":
          additional_edge_files = []
      else:
          additional_edge_files = self.meta_info[
              "additional edge files"
          ].split(",")
  
      if self.is_hetero:
          data = read_heterograph_pyg(
              self.raw_dir,
              add_inverse_edge=add_inverse_edge,
              additional_node_files=additional_node_files,
              additional_edge_files=additional_edge_files,
              binary=self.binary,
          )[0]
      else:
          data = read_graph_pyg(
              self.raw_dir,
              add_inverse_edge=add_inverse_edge,
              additional_node_files=additional_node_files,
              additional_edge_files=additional_edge_files,
              binary=self.binary,
          )[0]
  
      data = (
          data
          if self.pre_transform is None
          else self.pre_transform(data)
      )
  
      print("Saving...")
      torch.save(self.collate([data]), self.processed_paths[0])
  
file_path: ogb/ogb/linkproppred/dataset_pyg.py
imports: import pandas
  import shutil, os
  import os.path
  import torch
  import numpy
  from torch_geometric.data import InMemoryDataset
  from ogb.utils.url import decide_download, download_url, extract_zip
  from ogb.io.read_graph_pyg import read_graph_pyg, read_heterograph_pyg
  from ogb.utils.torch_util import replace_numpy_with_torchtensor
label_desc: Use image node_id 6 for calling the PygLinkPropPredDataset obj's underlying member method code with example usage: obj.process() without return types