code: def may_share_memory(a, b, raise_other_type=True):
      a_ndarray = isinstance(a, np.ndarray)
      b_ndarray = isinstance(b, np.ndarray)
      if a_ndarray and b_ndarray:
          return TensorType.may_share_memory(a, b)
  
      a_sparse = _is_sparse(a)
      b_sparse = _is_sparse(b)
      if not (a_ndarray or a_sparse) or not (b_ndarray or b_sparse):
          if raise_other_type:
              raise TypeError(
                  "may_share_memory support only ndarray and scipy.sparse"
              )
          return False
  
      return SparseTensorType.may_share_memory(a, b)
  
label_desc: Use image node_id 1 for calling a global function with example usage: may_share_memory(a, b, raise_other_type) and returns: SparseTensorType, TensorType, False