docstr: Test with two meshes composed of different cases to check all the
  indexing is correct.
  Case 4 faces are subdivided into two faces which are referred
  to as t1 and t2.
docstr_tok: ["Test","with","two","meshes","composed","of","different","cases","to","check","all","the","indexing","is","correct",".","Case","4","faces","are","subdivided","into","two","faces","which","are","referred","to","as","t1","and","t2","."]
imports: import unittest
  import imageio
  import numpy
  import torch
  from pytorch3d.io import save_obj
  from pytorch3d.renderer.cameras import FoVPerspectiveCameras, look_at_view_transform, PerspectiveCameras
  from pytorch3d.renderer.lighting import PointLights
  from pytorch3d.renderer.mesh import clip_faces, ClipFrustum, convert_clipped_rasterization_to_original_faces, TexturesUV
  from pytorch3d.renderer.mesh.rasterize_meshes import _RasterizeFaceVerts
  from pytorch3d.renderer.mesh.rasterizer import MeshRasterizer, RasterizationSettings
  from pytorch3d.renderer.mesh.renderer import MeshRenderer
  from pytorch3d.renderer.mesh.shader import SoftPhongShader
  from pytorch3d.renderer.mesh.textures import TexturesVertex
  from pytorch3d.structures.meshes import Meshes
  from pytorch3d.utils import torus
  from .common_testing import get_tests_dir, load_rgb_image, TestCaseMixin
label_desc: Use image node_id 9 for calling the TestRenderMeshesClipping obj's underlying member method code with example usage: obj.test_mixture_of_cases() without return types