old_contents: def _fastCopyAndTranspose(a):
      return a.T.copy()
  
  def copyto(dst, src, casting='same_kind', where=None):
      dst.fill(src)
  
  def format_longfloat(x, precision):
      return "%%.%df" % precision % x
  
  def set_typeDict(d):
      pass
  
  def may_share_memory(a, b):
      """
      Determine if two arrays can share memory
  
      The memory-bounds of a and b are computed.  If they overlap then
      this function returns True.  Otherwise, it returns False.
  
      A return of True does not necessarily mean that the two arrays
      share any element.  It just means that they *might*.
  
      Parameters
      ----------
      a, b : ndarray
  
      Returns
      -------
      out : bool
  
      Examples
      --------
      >>> np.may_share_memory(np.array([1,2]), np.array([5,8,9]))
      False
  
      """
      from ..lib import byte_bounds
      a_low, a_high = byte_bounds(a)
      b_low, b_high = byte_bounds(b)
      if b_low >= a_high or a_low >= b_high:
          return False
      return True
  
  from _numpypy.multiarray import *
  
  for name in '''
  CLIP WRAP RAISE MAXDIMS ALLOW_THREADS BUFSIZE nditer nested_iters
  broadcast empty_like fromiter fromfile frombuffer newbuffer getbuffer
  int_asbuffer set_numeric_ops can_cast promote_types
  min_scalar_type result_type lexsort compare_chararrays putmask einsum inner
  _vec_string datetime_data
  datetime_as_string busday_offset busday_count is_busday busdaycalendar
  _flagdict flagsobj
  '''.split():
      if name not in globals():
          globals()[name] = None
  
new_contents: def _fastCopyAndTranspose(a):
      return a.T.copy()
  
  def copyto(dst, src, casting='same_kind', where=None):
      if where is None:
          dst.fill(src)
      else:
          dst[where] = src
  
  def format_longfloat(x, precision):
      return "%%.%df" % precision % x
  
  def set_typeDict(d):
      pass
  
  def may_share_memory(a, b):
      """
      Determine if two arrays can share memory
  
      The memory-bounds of a and b are computed.  If they overlap then
      this function returns True.  Otherwise, it returns False.
  
      A return of True does not necessarily mean that the two arrays
      share any element.  It just means that they *might*.
  
      Parameters
      ----------
      a, b : ndarray
  
      Returns
      -------
      out : bool
  
      Examples
      --------
      >>> np.may_share_memory(np.array([1,2]), np.array([5,8,9]))
      False
  
      """
      from ..lib import byte_bounds
      a_low, a_high = byte_bounds(a)
      b_low, b_high = byte_bounds(b)
      if b_low >= a_high or a_low >= b_high:
          return False
      return True
  
  from _numpypy.multiarray import *
  
  for name in '''
  CLIP WRAP RAISE MAXDIMS ALLOW_THREADS BUFSIZE nditer nested_iters
  broadcast empty_like fromiter fromfile frombuffer newbuffer getbuffer
  int_asbuffer set_numeric_ops can_cast promote_types
  min_scalar_type result_type lexsort compare_chararrays putmask einsum inner
  _vec_string datetime_data
  datetime_as_string busday_offset busday_count is_busday busdaycalendar
  _flagdict flagsobj
  '''.split():
      if name not in globals():
          globals()[name] = None
  
subject: fix copyto with where arg