class_docstr: The `MoleculeNet <http://moleculenet.org/datasets-1>`_ benchmark
  collection  from the `"MoleculeNet: A Benchmark for Molecular Machine
  Learning" <https://arxiv.org/abs/1703.00564>`_ paper, containing datasets
  from physical chemistry, biophysics and physiology.
  All datasets come with the additional node and edge features introduced by
  the :ogb:`null`
  `Open Graph Benchmark <https://ogb.stanford.edu/docs/graphprop/>`_.
  
  Args:
      root (str): Root directory where the dataset should be saved.
      name (str): The name of the dataset (:obj:`"ESOL"`, :obj:`"FreeSolv"`,
          :obj:`"Lipo"`, :obj:`"PCBA"`, :obj:`"MUV"`, :obj:`"HIV"`,
          :obj:`"BACE"`, :obj:`"BBBP"`, :obj:`"Tox21"`, :obj:`"ToxCast"`,
          :obj:`"SIDER"`, :obj:`"ClinTox"`).
      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`)
      pre_filter (callable, optional): A function that takes in an
          :obj:`torch_geometric.data.Data` object and returns a boolean
          value, indicating whether the data object should be included in the
          final dataset. (default: :obj:`None`)
      force_reload (bool, optional): Whether to re-process the dataset.
          (default: :obj:`False`)
  
  **STATS:**
  
  .. list-table::
      :widths: 20 10 10 10 10 10
      :header-rows: 1
  
      * - Name
        - #graphs
        - #nodes
        - #edges
        - #features
        - #classes
      * - ESOL
        - 1,128
        - ~13.3
        - ~27.4
        - 9
        - 1
      * - FreeSolv
        - 642
        - ~8.7
        - ~16.8
        - 9
        - 1
      * - Lipophilicity
        - 4,200
        - ~27.0
        - ~59.0
        - 9
        - 1
      * - PCBA
        - 437,929
        - ~26.0
        - ~56.2
        - 9
        - 128
      * - MUV
        - 93,087
        - ~24.2
        - ~52.6
        - 9
        - 17
      * - HIV
        - 41,127
        - ~25.5
        - ~54.9
        - 9
        - 1
      * - BACE
        - 1513
        - ~34.1
        - ~73.7
        - 9
        - 1
      * - BBBP
        - 2,050
        - ~23.9
        - ~51.6
        - 9
        - 1
      * - Tox21
        - 7,831
        - ~18.6
        - ~38.6
        - 9
        - 12
      * - ToxCast
        - 8,597
        - ~18.7
        - ~38.4
        - 9
        - 617
      * - SIDER
        - 1,427
        - ~33.6
        - ~70.7
        - 9
        - 27
      * - ClinTox
        - 1,484
        - ~26.1
        - ~55.5
        - 9
        - 2
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code: def processed_file_names(self) -> str:
      return "data.pt"
  
file_path: pytorch_geometric/torch_geometric/datasets/molecule_net.py
imports: import os
  import os.path
  import re
  from typing import Callable, Dict, Optional, Tuple, Union
  import torch
  from torch_geometric.data import InMemoryDataset, download_url, extract_gz
  from torch_geometric.utils import from_smiles
label_desc: Use image node_id 5 for calling the MoleculeNet obj's underlying member method code with example usage: obj.processed_file_names() and returns: str