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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def promote16(u, fn=None, *args, **kwargs):
 r""" Utility function for use with functions that do not support arrays of dtype ``np.float16``. This function has two distinct modes of operation. If called with only the `u` parameter specified, the returned value is either `u` itself if `u` is not of dtype ``np.float16``, or `u` promoted to ``np.float32`` dtype if it is. If the function parameter `fn` is specified then `u` is conditionally promoted as described above, passed as the first argument to function `fn`, and the returned values are converted back to dtype ``np.float16`` if `u` is of that dtype. Note that if parameter `fn` is specified, it may not be be specified as a keyword argument if it is followed by any non-keyword arguments. Parameters u : array_like Array to be promoted to np.float32 if it is of dtype ``np.float16`` fn : function or None, optional (default None) Function to be called with promoted `u` as first parameter and \*args and \*\*kwargs as additional parameters *args Variable length list of arguments for function `fn` **kwargs Keyword arguments for function `fn` Returns ------- up : ndarray Conditionally dtype-promoted version of `u` if `fn` is None, or value(s) returned by `fn`, converted to the same dtype as `u`, if `fn` is a function """


    dtype = np.float32 if u.dtype == np.float16 else u.dtype
    up = np.asarray(u, dtype=dtype)
    if fn is None:
        return up
    else:
        v = fn(up, *args, **kwargs)
        if isinstance(v, tuple):
            vp = tuple([np.asarray(vk, dtype=u.dtype) for vk in v])
        else:
            vp = np.asarray(v, dtype=u.dtype)
        return vp