code: def _simple_sphere(self, rasterizer_type):
      device = torch.device("cuda:0")
      ref_filename = (
          f"test_rasterized_sphere_{rasterizer_type.__name__}.png"
      )
      image_ref_filename = DATA_DIR / ref_filename
  
      # Rescale image_ref to the 0 - 1 range and convert to a binary mask.
      image_ref = convert_image_to_binary_mask(image_ref_filename)
  
      # Init mesh
      sphere_mesh = ico_sphere(5, device)
  
      # Init rasterizer settings
      R, T = look_at_view_transform(2.7, 0, 0)
      cameras = FoVPerspectiveCameras(device=device, R=R, T=T)
      raster_settings = RasterizationSettings(
          image_size=512, blur_radius=0.0, faces_per_pixel=1, bin_size=0
      )
  
      # Init rasterizer
      rasterizer = rasterizer_type(
          cameras=cameras, raster_settings=raster_settings
      )
  
      ####################################
      # 1. Test rasterizing a single mesh
      ####################################
  
      fragments = rasterizer(sphere_mesh)
      image = fragments.pix_to_face[0, ..., 0].squeeze().cpu()
      # Convert pix_to_face to a binary mask
      image[image >= 0] = 1.0
      image[image < 0] = 0.0
  
      if DEBUG:
          Image.fromarray((image.numpy() * 255).astype(np.uint8)).save(
              DATA_DIR
              / f"DEBUG_test_rasterized_sphere_{rasterizer_type.__name__}.png"
          )
  
      self.assertTrue(torch.allclose(image, image_ref))
  
      ##################################
      #  2. Test with a batch of meshes
      ##################################
  
      batch_size = 10
      sphere_meshes = sphere_mesh.extend(batch_size)
      fragments = rasterizer(sphere_meshes)
      for i in range(batch_size):
          image = fragments.pix_to_face[i, ..., 0].squeeze().cpu()
          image[image >= 0] = 1.0
          image[image < 0] = 0.0
          self.assertTrue(torch.allclose(image, image_ref))
  
      ####################################################
      #  3. Test that passing kwargs to rasterizer works.
      ####################################################
  
      #  Change the view transform to zoom out.
      R, T = look_at_view_transform(20.0, 0, 0, device=device)
      fragments = rasterizer(sphere_mesh, R=R, T=T)
      image = fragments.pix_to_face[0, ..., 0].squeeze().cpu()
      image[image >= 0] = 1.0
      image[image < 0] = 0.0
  
      ref_filename = (
          f"test_rasterized_sphere_zoom_{rasterizer_type.__name__}.png"
      )
      image_ref_filename = DATA_DIR / ref_filename
      image_ref = convert_image_to_binary_mask(image_ref_filename)
  
      if DEBUG:
          Image.fromarray((image.numpy() * 255).astype(np.uint8)).save(
              DATA_DIR
              / f"DEBUG_test_rasterized_sphere_zoom_{rasterizer_type.__name__}.png"
          )
      self.assertTrue(torch.allclose(image, image_ref))
  
      #################################
      #  4. Test init without cameras.
      ##################################
  
      # Create a new empty rasterizer:
      rasterizer = rasterizer_type(raster_settings=raster_settings)
  
      # Check that omitting the cameras in both initialization
      # and the forward pass throws an error:
      with self.assertRaisesRegex(
          ValueError, "Cameras must be specified"
      ):
          rasterizer(sphere_mesh)
  
      # Now pass in the cameras as a kwarg
      fragments = rasterizer(sphere_mesh, cameras=cameras)
      image = fragments.pix_to_face[0, ..., 0].squeeze().cpu()
      # Convert pix_to_face to a binary mask
      image[image >= 0] = 1.0
      image[image < 0] = 0.0
  
      if DEBUG:
          Image.fromarray((image.numpy() * 255).astype(np.uint8)).save(
              DATA_DIR
              / f"DEBUG_test_rasterized_sphere_{rasterizer_type.__name__}.png"
          )
  
      self.assertTrue(torch.allclose(image, image_ref))
  
imports: import unittest
  import numpy
  import torch
  from PIL import Image
  from pytorch3d.renderer import FoVOrthographicCameras, FoVPerspectiveCameras, look_at_view_transform, MeshRasterizer, OrthographicCameras, PerspectiveCameras, PointsRasterizationSettings, PointsRasterizer, RasterizationSettings
  from pytorch3d.renderer.fisheyecameras import FishEyeCameras
  from pytorch3d.renderer.opengl.rasterizer_opengl import _check_cameras, _check_raster_settings, _convert_meshes_to_gl_ndc, _parse_and_verify_image_size, MeshRasterizerOpenGL
  from pytorch3d.structures import Pointclouds
  from pytorch3d.structures.meshes import Meshes
  from pytorch3d.utils.ico_sphere import ico_sphere
  from .common_testing import get_tests_dir, TestCaseMixin
label_desc: Use image node_id 4 for calling the TestMeshRasterizer obj's underlying member method code with example usage: obj._simple_sphere(rasterizer_type) without return types