code: def test_simple_sphere_fisheye_against_perspective(self):
      device = torch.device("cuda:0")
  
      # Rescale image_ref to the 0 - 1 range and convert to a binary mask.
      sphere_mesh = ico_sphere(1, device)
      verts_padded = sphere_mesh.verts_padded()
      verts_padded[..., 1] += 0.2
      verts_padded[..., 0] += 0.2
      pointclouds = Pointclouds(points=verts_padded)
      R, T = look_at_view_transform(2.7, 0.0, 0.0)
      perspective_cameras = PerspectiveCameras(
          R=R,
          T=T,
          device=device,
      )
      fisheye_cameras = FishEyeCameras(
          device=device,
          R=R,
          T=T,
          world_coordinates=True,
          use_radial=False,
          use_tangential=False,
          use_thin_prism=False,
      )
      raster_settings = PointsRasterizationSettings(
          image_size=256, radius=5e-2, points_per_pixel=1
      )
  
      #################################
      #  1. Test init without cameras.
      ##################################
  
      # Initialize without passing in the cameras
      rasterizer = PointsRasterizer()
  
      # Check that omitting the cameras in both initialization
      # and the forward pass throws an error:
      with self.assertRaisesRegex(
          ValueError, "Cameras must be specified"
      ):
          rasterizer(pointclouds)
  
      ########################################################################################
      # 2. Test rasterizing a single pointcloud with fisheye camera agasint perspective camera
      ########################################################################################
  
      perspective_fragments = rasterizer(
          pointclouds,
          cameras=perspective_cameras,
          raster_settings=raster_settings,
      )
      fisheye_fragments = rasterizer(
          pointclouds,
          cameras=fisheye_cameras,
          raster_settings=raster_settings,
      )
  
      # Convert idx to a binary mask
      perspective_image = (
          perspective_fragments.idx[0, ..., 0].squeeze().cpu()
      )
      perspective_image[perspective_image >= 0] = 1.0
      perspective_image[perspective_image < 0] = 0.0
  
      fisheye_image = fisheye_fragments.idx[0, ..., 0].squeeze().cpu()
      fisheye_image[fisheye_image >= 0] = 1.0
      fisheye_image[fisheye_image < 0] = 0.0
  
      if DEBUG:
          Image.fromarray(
              (perspective_image.numpy() * 255).astype(np.uint8)
          ).save(
              DATA_DIR
              / "DEBUG_test_rasterized_perspective_sphere_points.png"
          )
          Image.fromarray(
              (fisheye_image.numpy() * 255).astype(np.uint8)
          ).save(
              DATA_DIR
              / "DEBUG_test_rasterized_fisheye_sphere_points.png"
          )
  
      self.assertTrue(torch.allclose(fisheye_image, perspective_image))
  
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 2 for calling the TestPointRasterizer obj's underlying member method code with example usage: obj.test_simple_sphere_fisheye_against_perspective() without return types