code: def make_grad_logsumexp(ans, x, axis=None, b=1.0, keepdims=False):
      shape, dtype = np.shape(x), np.result_type(x)
  
      def vjp(g):
          g_repeated, _ = repeat_to_match_shape(
              g, shape, dtype, axis, keepdims
          )
          ans_repeated, _ = repeat_to_match_shape(
              ans, shape, dtype, axis, keepdims
          )
          return g_repeated * b * np.exp(x - ans_repeated)
  
      return vjp
  
file_path: autograd/autograd/scipy/special.py
imports: from __future__ import absolute_import
  import scipy.special
  import autograd.numpy
  from autograd.extend import primitive, defvjp, defjvp
  from autograd.numpy.numpy_vjps import unbroadcast_f, repeat_to_match_shape
label_desc: Use image node_id 2 for calling a global function with example usage: make_grad_logsumexp(ans, x, axis, b, keepdims) and returns: vjp, unknown