code: def may_share_memory(a, b, max_work=None):
      """
      may_share_memory(a, b, /, max_work=None)
  
      Determine if two arrays might share memory
  
      A return of True does not necessarily mean that the two arrays
      share any element.  It just means that they *might*.
  
      Only the memory bounds of a and b are checked by default.
  
      Parameters
      ----------
      a, b : ndarray
          Input arrays
      max_work : int, optional
          Effort to spend on solving the overlap problem.  See
          `shares_memory` for details.  Default for ``may_share_memory``
          is to do a bounds check.
  
      Returns
      -------
      out : bool
  
      See Also
      --------
      shares_memory
  
      Examples
      --------
      >>> np.may_share_memory(np.array([1,2]), np.array([5,8,9]))
      False
      >>> x = np.zeros([3, 4])
      >>> np.may_share_memory(x[:,0], x[:,1])
      True
  
      """
      return (a, b)
  
imports: import functools
  from .None import overrides
  from .None import _multiarray_umath
  from ._multiarray_umath import *
  from ._multiarray_umath import fastCopyAndTranspose, _flagdict, from_dlpack, _place, _reconstruct, _vec_string, _ARRAY_API, _monotonicity, _get_ndarray_c_version, _get_madvise_hugepage, _set_madvise_hugepage, _get_promotion_state, _set_promotion_state, _using_numpy2_behavior
label_desc: Use image node_id 19 for calling a global function with example usage: may_share_memory(a, b, max_work) and returns: a,  b