class_docstr: A variety of artificially and semi-artificially generated graph
  datasets from the `"Benchmarking Graph Neural Networks"
  <https://arxiv.org/abs/2003.00982>`_ paper.
  
  .. note::
      The ZINC dataset is provided via
      :class:`torch_geometric.datasets.ZINC`.
  
  Args:
      root (str): Root directory where the dataset should be saved.
      name (str): The name of the dataset (one of :obj:`"PATTERN"`,
          :obj:`"CLUSTER"`, :obj:`"MNIST"`, :obj:`"CIFAR10"`,
          :obj:`"TSP"`, :obj:`"CSL"`)
      split (str, optional): If :obj:`"train"`, loads the training dataset.
          If :obj:`"val"`, loads the validation dataset.
          If :obj:`"test"`, loads the test dataset.
          (default: :obj:`"train"`)
      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
      * - PATTERN
        - 10,000
        - ~118.9
        - ~6,098.9
        - 3
        - 2
      * - CLUSTER
        - 10,000
        - ~117.2
        - ~4,303.9
        - 7
        - 6
      * - MNIST
        - 55,000
        - ~70.6
        - ~564.5
        - 3
        - 10
      * - CIFAR10
        - 45,000
        - ~117.6
        - ~941.2
        - 5
        - 10
      * - TSP
        - 10,000
        - ~275.4
        - ~6,885.0
        - 2
        - 2
      * - CSL
        - 150
        - ~41.0
        - ~164.0
        - 0
        - 10
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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/gnn_benchmark_dataset.py
imports: import logging
  import os
  import os.path
  import pickle
  from typing import Callable, List, Optional
  import torch
  from torch_geometric.data import Data, InMemoryDataset, download_url, extract_zip
  from torch_geometric.utils import remove_self_loops
label_desc: Use image node_id 3 for calling the GNNBenchmarkDataset obj's underlying member method code with example usage: obj.processed_dir() and returns: osp