class_docstr: Transform that adds the index of the point to the data object
  This allows us to track this point from the output back to the input data object
class_docstr_tok: ["Transform","that","adds","the","index","of","the","point","to","the","data","object","This","allows","us","to","track","this","point","from","the","output","back","to","the","input","data","object"]
code: def _process(self, data):
      if hasattr(data, self.KEY):
          return data
  
      setattr(data, self.KEY, torch.arange(0, data.pos.shape[0]))
      return data
  
imports: from typing import *
  import numpy
  import numpy
  import random
  import scipy
  import re
  import torch
  import logging
  import torch.nn.functional
  from torch_scatter import scatter_mean, scatter_add
  from torch_geometric.nn.pool.consecutive import consecutive_cluster
  from torch_geometric.nn import voxel_grid
  from torch_geometric.data import Data
  from torch_cluster import grid_cluster
label_desc: Use image node_id 1 for calling the SaveOriginalPosId obj's underlying member method code with example usage: obj._process(data) and returns: data, data