docstr: Obtain a sub-squence given a list of indices of the elements
  to include.
  
  Element ids are the ones of the originating sequence
  (that is, the non-sliced sequence).
docstr_tok: ["Obtain","a","sub-squence","given","a","list","of","indices","of","the","elements","to","include",".","Element","ids","are","the","ones","of","the","originating","sequence","(","that","is",",","the","non-sliced","sequence",")","."]
code: def _make_slice(
      self: TSliceSequence, sequence_slice: Optional[Iterable[int]]
  ) -> TSliceSequence:
      """
      Obtain a sub-squence given a list of indices of the elements
      to include.
  
      Element ids are the ones of the originating sequence
      (that is, the non-sliced sequence).
      """
      stream_copy = copy.copy(self)
      stream_copy.slice_ids = (
          list(sequence_slice) if sequence_slice is not None else None
      )
      return stream_copy
  
imports: from abc import ABC, abstractmethod
  import bisect
  import copy
  from typing import Iterator, overload
  from typing_extensions import final
  import numpy
  from numpy import ndarray
  from torch import Tensor
  from torch.utils.data import Subset
  from .dataset_definitions import IDatasetWithTargets
  from typing import Sequence, List, Iterable, Union, Optional, TypeVar, Callable, Generic
label_desc: Use image node_id 11 for calling the SliceSequence obj's underlying member method code with example usage: obj._make_slice(sequence_slice) and returns: stream_copy