class_docstr: The TOSCA dataset from the `"Numerical Geometry of Non-Ridig Shapes"
  <https://www.amazon.com/Numerical-Geometry-Non-Rigid-Monographs-Computer/
  dp/0387733000>`_ book, containing 80 meshes.
  Meshes within the same category have the same triangulation and an equal
  number of vertices numbered in a compatible way.
  
  .. note::
  
      Data objects hold mesh faces instead of edge indices.
      To convert the mesh to a graph, use the
      :obj:`torch_geometric.transforms.FaceToEdge` as :obj:`pre_transform`.
      To convert the mesh to a point cloud, use the
      :obj:`torch_geometric.transforms.SamplePoints` as :obj:`transform` to
      sample a fixed number of points on the mesh faces according to their
      face area.
  
  Args:
      root (str): Root directory where the dataset should be saved.
      categories (list, optional): List of categories to include in the
          dataset. Can include the categories :obj:`"Cat"`, :obj:`"Centaur"`,
          :obj:`"David"`, :obj:`"Dog"`, :obj:`"Gorilla"`, :obj:`"Horse"`,
          :obj:`"Michael"`, :obj:`"Victoria"`, :obj:`"Wolf"`. If set to
          :obj:`None`, the dataset will contain all categories. (default:
          :obj:`None`)
      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`)
code: def raw_file_names(self) -> List[str]:
      return ["cat0.vert", "cat0.tri"]
  
file_path: pytorch_geometric/torch_geometric/datasets/tosca.py
imports: import glob
  import os
  import os.path
  from typing import Callable, List, Optional
  import torch
  from torch_geometric.data import Data, InMemoryDataset, download_url, extract_zip
  from torch_geometric.io import read_txt_array
label_desc: Use image node_id 2 for calling the TOSCA obj's underlying member method code with example usage: obj.raw_file_names() and returns: list