code: def test_hessian():
      # Check Hessian of a quadratic function.
      D = 5
      H = npr.randn(D, D)
  
      def fun(x):
          return np.dot(np.dot(x, H), x)
  
      hess = hessian(fun)
      x = npr.randn(D)
      check_equivalent(hess(x), H + H.T)
  
imports: from __future__ import absolute_import
  from builtins import range
  import warnings
  from functools import partial
  import autograd.numpy
  import autograd.numpy.random
  from autograd.test_util import check_grads, check_equivalent
  from autograd.tracer import primitive, isbox
  from autograd import grad, elementwise_grad, jacobian, value_and_grad, hessian_tensor_product, hessian, make_hvp, tensor_jacobian_product, checkpoint, make_jvp, make_ggnvp, grad_and_aux
label_desc: Use image node_id 3 for calling a global function with example usage: test_hessian() and returns: np