code: def __getitem__(self, index):
      tensor = self.tensor
  
      def neg_step(i, s):
          if not (
              isinstance(s, slice) and s.step is not None and s.step < 0
          ):
              return s
  
          nonlocal tensor
          tensor = torch.flip(tensor, (i,))
  
          # Account for the fact that a slice includes the start but not the end
          assert isinstance(s.start, int) or s.start is None
          assert isinstance(s.stop, int) or s.stop is None
          start = s.stop + 1 if s.stop else None
          stop = s.start + 1 if s.start else None
  
          return slice(start, stop, -s.step)
  
      if isinstance(index, Sequence):
          index = type(index)(
              neg_step(i, s) for i, s in enumerate(index)
          )
      else:
          index = neg_step(0, index)
      index = _util.ndarrays_to_tensors(index)
      index = _upcast_int_indices(index)
      return ndarray(tensor.__getitem__(index))
  
imports: from __future__ import annotations
  import builtins
  import math
  import operator
  from typing import Sequence
  import torch
  from .None import _dtypes, _dtypes_impl, _funcs, _ufuncs, _util
  from ._normalizations import ArrayLike, normalize_array_like, normalizer, NotImplementedType
label_desc: Use image node_id 39 for calling the ndarray obj's underlying member method code with example usage: obj.__getitem__(index) and returns: ndarray, slice, s