code: def logsumexp(x):
      """Numerically stable log(sum(exp(x))), also defined in scipy.special"""
      max_x = np.max(x)
      return max_x + np.log(np.sum(np.exp(x - max_x)))
  
file_path: autograd/examples/define_gradient.py
imports: from __future__ import absolute_import
  from __future__ import print_function
  import autograd.numpy
  import autograd.numpy.random
  from autograd import grad
  from autograd.extend import primitive, defvjp
  from autograd.test_util import check_grads
label_desc: Use image node_id 1 for calling a global function with example usage: logsumexp(x) and returns: unknown