code: def _groupby(self, data, colunm):
      # group the data using unique values in column
      # This code is adapted from https://github.com/pytorch/pytorch/issues/20613
  
      sorted_values, order = colunm.sort(0)
      delta = colunm[1:] - colunm[:-1]
      non_zero = delta.nonzero()
  
      if len(non_zero) == 0:
          return [data]
  
      cutpoints = non_zero[0]
      cutpoints: List[int] = cutpoints.add(1).tolist()
      res: List[torch.Tensor] = []
      for start, end in zip([0] + cutpoints, cutpoints + [len(colunm)]):
          index, _ = order[start:end].sort(0)
          res.append(data[index])
  
      return res
  
imports: import torch
  import torch.nn
  from typing import List
  from sklearn.preprocessing import StandardScaler, MaxAbsScaler, MinMaxScaler, RobustScaler
  from .utils import _to_list
label_desc: Use image node_id 3 for calling the ExportJIT obj's underlying member method code with example usage: obj._groupby(data, colunm) and returns: res, list