class_docstr: Adapted from https://docs.dgl.ai/en/latest/_modules/dgl/data/chem/csv_dataset.html#CSVDataset
class_docstr_tok: ["Adapted","from","https",":","\/\/docs.dgl.ai\/en\/latest\/_modules\/dgl\/data\/chem\/csv_dataset.html","#","CSVDataset"]
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_dgl.py
imports: import pandas
  import shutil, os
  import os.path
  import torch
  import numpy
  from dgl.data.utils import load_graphs, save_graphs, Subset
  import dgl
  from ogb.utils.url import decide_download, download_url, extract_zip
  from ogb.io.read_graph_dgl import read_graph_dgl, read_heterograph_dgl
  from ogb.utils.torch_util import replace_numpy_with_torchtensor
label_desc: Use image node_id 3 for calling the DglLinkPropPredDataset obj's underlying member method code with example usage: obj.get_edge_split(split_type) and returns: dict, torch