code: def test_compositor_background_color_rgba(self):
      N, H, W, K, C, P = 1, 15, 15, 20, 4, 225
      ptclds = torch.randn((C, P))
      alphas = torch.rand((N, K, H, W))
      pix_idxs = torch.randint(
          -1, 20, (N, K, H, W)
      )  # 20 < P, large amount of -1
      background_color = [0.5, 0, 1]
  
      compositor_funcs = [
          (NormWeightedCompositor, norm_weighted_sum),
          (AlphaCompositor, alpha_composite),
      ]
  
      for compositor_class, composite_func in compositor_funcs:
          compositor = compositor_class(background_color)
  
          # run the forward method to generate masked images
          masked_images = compositor.forward(pix_idxs, alphas, ptclds)
  
          # generate unmasked images for testing purposes
          images = composite_func(pix_idxs, alphas, ptclds)
  
          is_foreground = pix_idxs[:, 0] >= 0
  
          # make sure foreground values are unchanged
          self.assertClose(
              torch.masked_select(
                  masked_images, is_foreground[:, None]
              ),
              torch.masked_select(images, is_foreground[:, None]),
          )
  
          is_background = ~is_foreground[..., None].expand(
              -1, -1, -1, C
          )
  
          # permute masked_images to correctly get rgb values
          masked_images = masked_images.permute(0, 2, 3, 1)
          for i in range(3):
              channel_color = background_color[i]
  
              # check if background colors are properly changed
              self.assertTrue(
                  masked_images[is_background]
                  .view(-1, C)[..., i]
                  .eq(channel_color)
                  .all()
              )
  
          # check background color alpha values
          self.assertTrue(
              masked_images[is_background]
              .view(-1, C)[..., 3]
              .eq(1)
              .all()
          )
  
imports: import unittest
  import warnings
  from os import path
  import numpy
  import torch
  from PIL import Image
  from pytorch3d.renderer.cameras import FoVOrthographicCameras, FoVPerspectiveCameras, look_at_view_transform, OrthographicCameras, PerspectiveCameras
  from pytorch3d.renderer.compositing import alpha_composite, norm_weighted_sum
  from pytorch3d.renderer.fisheyecameras import FishEyeCameras
  from pytorch3d.renderer.points import AlphaCompositor, NormWeightedCompositor, PointsRasterizationSettings, PointsRasterizer, PointsRenderer, PulsarPointsRenderer
  from pytorch3d.structures.pointclouds import Pointclouds
  from pytorch3d.utils.ico_sphere import ico_sphere
  from .common_testing import get_pytorch3d_dir, get_tests_dir, load_rgb_image, TestCaseMixin
label_desc: Use image node_id 7 for calling the TestRenderPoints obj's underlying member method code with example usage: obj.test_compositor_background_color_rgba() without return types