code: def test_random_inputs(self):
      pixel_coords_screen = (
          self.pixel_coords_screen
          + torch.randn((self.N, self.H, self.W, self.K, 2)) * 0.1
      )
      colors = torch.rand((self.N, self.H, self.W, self.K, 4))
      splatting_colors_and_weights = (
          _compute_splatting_colors_and_weights(
              pixel_coords_screen, colors, sigma=0.5, offsets=offsets
          )
      )
      naive_colors_and_weights = (
          compute_splatting_colors_and_weights_naive(
              pixel_coords_screen, colors, sigma=0.5
          )
      )
  
      self.assertClose(
          splatting_colors_and_weights,
          naive_colors_and_weights,
          atol=0.01,
      )
  
imports: import unittest
  import torch
  from pytorch3d.common.compat import meshgrid_ij
  from pytorch3d.renderer.cameras import FoVPerspectiveCameras
  from pytorch3d.renderer.splatter_blend import _compute_occlusion_layers, _compute_splatted_colors_and_weights, _compute_splatting_colors_and_weights, _get_splat_kernel_normalization, _normalize_and_compose_all_layers, _offset_splats, _precompute, _prepare_pixels_and_colors
  from .common_testing import TestCaseMixin
label_desc: Use image node_id 4 for calling the TestComputeSplattingColorsAndWeights obj's underlying member method code with example usage: obj.test_random_inputs() without return types