code: def test_hessian_vector_product_2x2(
      a_val, b_val, x_val, y_val, vector
  ):
      """Test for a function with two variables."""
      obs = [torch.tensor([a_val]), torch.tensor([b_val])]
      vector = torch.tensor([vector])
      x = torch.tensor(x_val, requires_grad=True)
      y = torch.tensor(y_val, requires_grad=True)
  
      def f():
          a, b = obs[0], obs[1]
          return a * (x**2) + b * (y**2)
  
      expected_hessian = compute_hessian(f(), [x, y])
      expected_hvp = torch.mm(vector, expected_hessian).detach()
      f_Ax = _build_hessian_vector_product(f, [x, y])
      hvp = f_Ax(vector[0]).detach()
      assert np.allclose(hvp, expected_hvp, atol=1e-6)
  
imports: import pickle
  import numpy
  import pytest
  import torch
  from garage.torch.optimizers.conjugate_gradient_optimizer import ConjugateGradientOptimizer
  from garage.torch.optimizers.conjugate_gradient_optimizer import _build_hessian_vector_product
  from garage.torch.optimizers.conjugate_gradient_optimizer import _conjugate_gradient
label_desc: Use image node_id 3 for calling a global function with example usage: test_hessian_vector_product_2x2(a_val, b_val, x_val, y_val, vector) and returns: unknown