class_docstr: A dataset describing the `Product ecology
  <https://wiki.opensourceecology.org/wiki/Product_Ecologies>`_ of the Open
  Source Ecology's iconoclastic `Global Village Construction Set
  <https://wiki.opensourceecology.org/wiki/
  Global_Village_Construction_Set>`_.
  GVCS is a modular, DIY, low-cost set of blueprints that enables the
  fabrication of the 50 different industrial machines that it takes to
  build a small, sustainable civilization with modern comforts.
  
  The dataset contains a heterogenous graphs with 50 :obj:`machine` nodes,
  composing the GVCS, and 290 directed edges, each representing one out of
  three relationships between machines.
  
  Args:
      root (str): Root directory where the dataset should be saved.
      transform (callable, optional): A function/transform that takes in an
          :obj:`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 :obj:`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 __init__(
      self,
      root: str,
      transform: Optional[Callable] = None,
      pre_transform: Optional[Callable] = None,
      force_reload: bool = False,
  ) -> None:
      super().__init__(
          root, transform, pre_transform, force_reload=force_reload
      )
      self.load(self.processed_paths[0], data_cls=HeteroData)
  
file_path: pytorch_geometric/torch_geometric/datasets/ose_gvcs.py
imports: import json
  import os
  from collections import defaultdict
  from typing import Callable, List, Optional
  import torch
  from torch_geometric.data import HeteroData, InMemoryDataset, download_url, extract_tar
label_desc: Use image node_id 1 to create a new OSE_GVCS object from inherited base classes: InMemoryDataset with example: obj = OSE_GVCS(root, transform, pre_transform, force_reload)