class_docstr: The `TrackML Particle Tracking Challenge
  <https://www.kaggle.com/c/trackml-particle-identification>`_ dataset to
  reconstruct particle tracks from 3D points left in the silicon detectors.
  
  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.Data` object and returns a transformed
          version. The data object will be transformed before every access.
          (default: :obj:`None`)
class_docstr_tok: ["The","`","TrackML","Particle","Tracking","Challenge","<","https",":","\/\/www.kaggle.com\/c\/trackml-particle-identification",">","`","_","dataset","to","reconstruct","particle","tracks","from","3D","points","left","in","the","silicon","detectors",".","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.Data","`","object","and","returns","a","transformed","version",".","The","data","object","will","be","transformed","before","every","access",".","(","default",":",":","obj",":","`","None","`",")"]
code: def len(self) -> int:
      return len(glob.glob(osp.join(self.raw_dir, "event*-hits.csv")))
  
file_path: pytorch_geometric/torch_geometric/datasets/particle.py
imports: import glob
  import os.path
  from typing import Any, Callable, List, Optional
  import numpy
  import torch
  from torch_geometric.data import Data, Dataset
  from torch_geometric.utils import index_sort, scatter
label_desc: Use image node_id 4 for calling the TrackMLParticleTrackingDataset obj's underlying member method code with example usage: obj.len() and returns: len