code: def np_doc(np_fun):
      """Attachs numpy docstring to a function.
  
      Args:
        np_fun: the numpy function whose docstring will be used.
  
      Returns:
        A function decorator that attaches the docstring from `np_fun` to the
        decorated function.
      """
      np_sig = _np_signature(np_fun)
  
      def decorator(f):
          """The decorator."""
          unsupported_params = []
          if np_sig is not None:
              sig = funcsigs.signature(f)
              for name in np_sig.parameters:
                  if name not in sig.parameters:
                      unsupported_params.append(name)
          f.__doc__ = _np_doc_helper(f, np_fun, unsupported_params)
          return f
  
      return decorator
  
imports: import funcsigs
  import numpy
  import tensorflow.compat.v2
  from trax.tf_numpy.numpy_impl import arrays
  from trax.tf_numpy.numpy_impl import dtypes
label_desc: Use image node_id 13 for calling a global function with example usage: np_doc(np_fun) and returns: decorator, f