class_docstr: A variety of heterogeneous graph benchmark datasets from the
  `"Are We Really Making Much Progress? Revisiting, Benchmarking, and
  Refining Heterogeneous Graph Neural Networks"
  <http://keg.cs.tsinghua.edu.cn/jietang/publications/
  KDD21-Lv-et-al-HeterGNN.pdf>`_ paper.
  
  .. note::
      Test labels are randomly given to prevent data leakage issues.
      If you want to obtain final test performance, you will need to submit
      your model predictions to the
      `HGB leaderboard <https://www.biendata.xyz/hgb/>`_.
  
  Args:
      root (str): Root directory where the dataset should be saved.
      name (str): The name of the dataset (one of :obj:`"ACM"`,
          :obj:`"DBLP"`, :obj:`"Freebase"`, :obj:`"IMDB"`)
      transform (callable, optional): A function/transform that takes in an
          :class:`torch_geometric.data.HeteroData` object and returns a
          transformed version. The data object will be transformed before
          every access. (default: :obj:`None`)
      pre_transform (callable, optional): A function/transform that takes in
          an :class:`torch_geometric.data.HeteroData` object and returns a
          transformed version. The data object will be transformed before
          being saved to disk. (default: :obj:`None`)
      force_reload (bool, optional): Whether to re-process the dataset.
          (default: :obj:`False`)
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code: def processed_dir(self) -> str:
      return osp.join(self.root, self.name, "processed")
  
file_path: pytorch_geometric/torch_geometric/datasets/hgb_dataset.py
imports: import json
  import os
  import os.path
  from collections import defaultdict
  from typing import Callable, Dict, List, Optional
  import torch
  from torch_geometric.data import HeteroData, InMemoryDataset, download_url, extract_zip
label_desc: Use image node_id 3 for calling the HGBDataset obj's underlying member method code with example usage: obj.processed_dir() and returns: osp