code: def _test_eigenvalues_and_eigenvectors(
      self, test_eigenvectors, test_eigenvalues, atol=1e-04, rtol=1e-04
  ):
      test_input = (
          test_eigenvectors.transpose(-2, -1)
          @ test_eigenvalues.diag_embed()
          @ test_eigenvectors
      )
  
      test_eigenvalues_sorted, _ = torch.sort(test_eigenvalues, dim=-1)
  
      eigenvalues, eigenvectors = symeig3x3(
          test_input, eigenvectors=True
      )
  
      self.assertClose(
          test_eigenvalues_sorted,
          eigenvalues,
          atol=atol,
          rtol=rtol,
      )
  
      self._test_is_not_nan_or_inf(test_input)
      self._test_is_eigen(test_input, atol=atol, rtol=rtol)
      self._test_eigenvectors_are_orthonormal(test_input)
  
imports: import unittest
  import torch
  from pytorch3d.common.workaround import symeig3x3
  from pytorch3d.transforms.rotation_conversions import random_rotations
  from .common_testing import get_random_cuda_device, TestCaseMixin
label_desc: Use image node_id 19 for calling the TestSymEig3x3 obj's underlying member method code with example usage: obj._test_eigenvalues_and_eigenvectors(test_eigenvectors, test_eigenvalues, atol, rtol) without return types