class_docstr: The WILLOW-ObjectClass dataset from the `"Learning Graphs to Match"
  <https://www.di.ens.fr/willow/pdfscurrent/cho2013.pdf>`_ paper,
  containing 10 equal keypoints of at least 40 images in each category.
  The keypoints contain interpolated features from a pre-trained VGG16 model
  on ImageNet (:obj:`relu4_2` and :obj:`relu5_1`).
  
  Args:
      root (str): Root directory where the dataset should be saved.
      category (str): The category of the images (one of :obj:`"Car"`,
          :obj:`"Duck"`, :obj:`"Face"`, :obj:`"Motorbike"`,
          :obj:`"Winebottle"`).
      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`)
      device (str or torch.device, optional): The device to use for
          processing the raw data. If set to :obj:`None`, will utilize
          GPU-processing if available. (default: :obj:`None`)
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code: def download(self) -> None:
      path = download_url(self.url, self.root)
      extract_zip(path, self.root)
      os.unlink(path)
      os.unlink(osp.join(self.root, "README"))
      os.unlink(osp.join(self.root, "demo_showAnno.m"))
      fs.rm(self.raw_dir)
      os.rename(osp.join(self.root, "WILLOW-ObjectClass"), self.raw_dir)
  
file_path: pytorch_geometric/torch_geometric/datasets/willow_object_class.py
imports: import glob
  import os
  import os.path
  from typing import Callable, List, Optional
  import torch
  import torch.nn.functional
  from torch import Tensor
  from torch.utils.data import DataLoader
  from torch_geometric.data import Data, InMemoryDataset, download_url, extract_zip
  from torch_geometric.io import fs
label_desc: Use image node_id 6 for calling the WILLOWObjectClass obj's underlying member method code with example usage: obj.download() without return types