code: def create_random_sym3x3(device, n):
      random_3x3 = torch.randn((n, 3, 3), device=device)
      random_3x3_T = torch.transpose(random_3x3, 1, 2)
      random_sym_3x3 = (random_3x3 * random_3x3_T).contiguous()
  
      return random_sym_3x3
  
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 1 for calling the TestSymEig3x3 obj's underlying member method code with example usage: obj.create_random_sym3x3(device, n) and returns: random_sym_3x3