code: def test_hessian_matrix_product():
      fun = lambda a: np.sum(np.sin(a))
      a = npr.randn(5, 4)
      V = npr.randn(5, 4)
      H = hessian(fun)(a)
      check_equivalent(
          np.tensordot(H, V), hessian_tensor_product(fun)(a, V)
      )
  
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 11 for calling a global function with example usage: test_hessian_matrix_product() without return types