class_docstr: The relational entities networks :obj:`"AIFB"`, :obj:`"MUTAG"`,
  :obj:`"BGS"` and :obj:`"AM"` from the `"Modeling Relational Data with Graph
  Convolutional Networks" <https://arxiv.org/abs/1703.06103>`_ paper.
  Training and test splits are given by node indices.
  
  Args:
      root (str): Root directory where the dataset should be saved.
      name (str): The name of the dataset (:obj:`"AIFB"`, :obj:`"MUTAG"`,
          :obj:`"BGS"`, :obj:`"AM"`).
      hetero (bool, optional): If set to :obj:`True`, will save the dataset
          as a :class:`~torch_geometric.data.HeteroData` object.
          (default: :obj:`False`)
      transform (callable, optional): A function/transform that takes in an
          :obj:`torch_geometric.data.Data` 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 :obj:`torch_geometric.data.Data` 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`)
  
  **STATS:**
  
  .. list-table::
      :widths: 10 10 10 10 10
      :header-rows: 1
  
      * - Name
        - #nodes
        - #edges
        - #features
        - #classes
      * - AIFB
        - 8,285
        - 58,086
        - 0
        - 4
      * - AM
        - 1,666,764
        - 11,976,642
        - 0
        - 11
      * - MUTAG
        - 23,644
        - 148,454
        - 0
        - 2
      * - BGS
        - 333,845
        - 1,832,398
        - 0
        - 2
code: def __repr__(self) -> str:
      return f"{self.name.upper()}{self.__class__.__name__}()"
  
imports: import logging
  import os
  import os.path
  from collections import Counter
  from typing import Any, Callable, List, Optional
  import torch
  from torch_geometric.data import Data, HeteroData, InMemoryDataset, download_url, extract_tar
  from torch_geometric.utils import index_sort
label_desc: Use image node_id 10 for calling the Entities obj's underlying member method code with example usage: obj.__repr__() and returns: self, self, str