code: def test_make_ggnvp():
      A = npr.randn(5, 4)
      x = npr.randn(4)
      v = npr.randn(4)
  
      fun = lambda x: np.dot(A, x)
      check_equivalent(
          make_ggnvp(fun)(x)(v), _make_explicit_ggnvp(fun)(x)(v)
      )
  
      fun2 = lambda x: np.tanh(np.dot(A, x))
      check_equivalent(
          make_ggnvp(fun2)(x)(v), _make_explicit_ggnvp(fun2)(x)(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 26 for calling a global function with example usage: test_make_ggnvp() without return types