code: def test_make_jvp():
      A = npr.randn(3, 5)
      x = npr.randn(5)
      v = npr.randn(5)
      fun = lambda x: np.tanh(np.dot(A, x))
  
      jvp_explicit = lambda x: lambda v: np.dot(jacobian(fun)(x), v)
      jvp = make_jvp(fun)
  
      check_equivalent(jvp_explicit(x)(v), jvp(x)(v)[1])
  
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 24 for calling a global function with example usage: test_make_jvp() without return types