code: def grad_np_mean(ans, x, axis=None, keepdims=False):
      shape, dtype = anp.shape(x), anp.result_type(x)
  
      def vjp(g):
          g_repeated, num_reps = repeat_to_match_shape(
              g, shape, dtype, axis, keepdims
          )
          return g_repeated / num_reps
  
      return vjp
  
imports: from __future__ import absolute_import
  from six import string_types
  from functools import partial
  import numpy
  from ..util import func
  from .None import numpy_wrapper
  from .numpy_boxes import ArrayBox
  from autograd.extend import primitive, vspace, defvjp, defvjp_argnum, SparseObject, VJPNode, register_notrace
label_desc: Use image node_id 11 for calling a global function with example usage: grad_np_mean(ans, x, axis, keepdims) and returns: vjp, unknown