class_docstr: Class for the purpose of preprocessing time series.
  
  The method make_features needs to be custom-made by inherited classes.
class_docstr_tok: ["Class","for","the","purpose","of","preprocessing","time","series",".","The","method","make_features","needs","to","be","custom-made","by","inherited","classes","."]
docstr: Makes features for the context window starting at starting_index.
  
  Parameters
  ----------
  time_series: list
  starting_index: int
      The index where the context window begins
  
  Returns
  -------
  list
docstr_tok: ["Makes","features","for","the","context","window","starting","at","starting_index",".","Parameters","--","--","--","--","--","time_series",":","list","starting_index",":","int","The","index","where","the","context","window","begins","Returns","--","--","--","-","list"]
code: def make_features(self, time_series, starting_index):
      """
      Makes features for the context window starting at starting_index.
  
      Parameters
      ----------
      time_series: list
      starting_index: int
          The index where the context window begins
  
      Returns
      -------
      list
      """
      raise NotImplementedError()
  
imports: import concurrent.futures
  import logging
  from enum import Enum
  from itertools import chain, starmap
  from typing import Dict, List, Tuple, Union, Optional, Sequence
  import numpy
  from gluonts.core.component import validated
label_desc: Use image node_id 2 for calling the PreprocessGeneric obj's underlying member method code with example usage: obj.make_features(time_series, starting_index) without return types