code: def get_edge_split(self, split_type=None):
      if split_type is None:
          split_type = self.meta_info["split"]
  
      path = osp.join(self.root, "split", split_type)
  
      # short-cut if split_dict.pt exists
      if os.path.isfile(os.path.join(path, "split_dict.pt")):
          return torch.load(os.path.join(path, "split_dict.pt"))
  
      train = replace_numpy_with_torchtensor(
          torch.load(osp.join(path, "train.pt"))
      )
      valid = replace_numpy_with_torchtensor(
          torch.load(osp.join(path, "valid.pt"))
      )
      test = replace_numpy_with_torchtensor(
          torch.load(osp.join(path, "test.pt"))
      )
  
      return {"train": train, "valid": valid, "test": test}
  
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 2 for calling the PygLinkPropPredDataset obj's underlying member method code with example usage: obj.get_edge_split(split_type) and returns: dict, torch