docstr: Tests if function supports arbitrary leading dimensions
docstr_tok: ["Tests","if","function","supports","arbitrary","leading","dimensions"]
code: def test_more_dimensions(self):
      """
      Tests if function supports arbitrary leading dimensions
      """
      repeat = 4
  
      test_input = self.create_random_sym3x3(self._cpu, n=16)
      test_input_4d = test_input[None, ...].expand(
          (repeat,) + test_input.shape
      )
  
      eigenvalues, eigenvectors = symeig3x3(
          test_input, eigenvectors=True
      )
      eigenvalues_4d, eigenvectors_4d = symeig3x3(
          test_input_4d, eigenvectors=True
      )
  
      eigenvalues_4d_gt = eigenvalues[None, ...].expand(
          (repeat,) + eigenvalues.shape
      )
      eigenvectors_4d_gt = eigenvectors[None, ...].expand(
          (repeat,) + eigenvectors.shape
      )
  
      self.assertClose(eigenvalues_4d_gt, eigenvalues_4d)
      self.assertClose(eigenvectors_4d_gt, eigenvectors_4d)
  
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 23 for calling the TestSymEig3x3 obj's underlying member method code with example usage: obj.test_more_dimensions() without return types