code: def _test(self, xp):
      # A must be symmetric and positive-definite
      random_mat = xp.random.normal(size=(self.n, self.n)).astype(
          self.dtype
      )
      A = random_mat.dot(random_mat.T)
      x_ans = xp.random.normal(size=self.n).astype(self.dtype)
      b = A.dot(x_ans)
  
      def A_product_func(vec):
          self.assertEqual(xp, chainer.cuda.get_array_module(vec))
          self.assertEqual(vec.shape, b.shape)
          return A.dot(vec)
  
      x = chainerrl.misc.conjugate_gradient(A_product_func, b)
      self.assertEqual(x.dtype, self.dtype)
      self.assertTrue(chainer.cuda.get_array_module(x), xp)
      xp.testing.assert_allclose(x, x_ans, rtol=1e-3)
  
file_path: chainerrl/tests/misc_tests/test_conjugate_gradient.py
imports: import unittest
  import chainer
  from chainer import testing
  from chainer.testing import condition
  import numpy
  import chainerrl
label_desc: Use image node_id 1 for calling the TestConjugateGradient obj's underlying member method code with example usage: obj._test(xp) and returns: A