code: def _prepare_np_fun_name_and_fun(np_fun_name, np_fun):
      """Mutually propagates information between `np_fun_name` and `np_fun`.
  
      If one is None and the other is not, we'll try to make the former not None in
      a best effort.
  
      Args:
        np_fun_name: name for the np_fun symbol. At least one of np_fun or
          np_fun_name shoud be set.
        np_fun: the numpy function whose docstring will be used.
  
      Returns:
        Processed `np_fun_name` and `np_fun`.
      """
      if np_fun_name is not None:
          assert isinstance(np_fun_name, str)
      if np_fun is not None:
          assert not isinstance(np_fun, str)
      if np_fun is None:
          assert np_fun_name is not None
          try:
              np_fun = getattr(np, str(np_fun_name))
          except AttributeError:
              np_fun = None
      if np_fun_name is None:
          assert np_fun is not None
          np_fun_name = np_fun.__name__
      return np_fun_name, np_fun
  
imports: import inspect
  import numbers
  import os
  import re
  import numpy
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import flexible_dtypes
  from tensorflow.python.framework import indexed_slices
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import cond
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops.numpy_ops import np_arrays
  from tensorflow.python.ops.numpy_ops import np_dtypes
  from tensorflow.python.types import core
  from tensorflow.python.util import nest
  from tensorflow.python.util import tf_export
label_desc: Use image node_id 11 for calling a global function with example usage: _prepare_np_fun_name_and_fun(np_fun_name, np_fun) and returns: np_fun_name,  np_fun