code: def test_all_equal(self):
      # If all colors are equal and on a regular grid, all weights and reweighted
      # colors should be equal given a specific splatting direction.
      splatting_colors_and_weights = (
          _compute_splatting_colors_and_weights(
              self.pixel_coords_screen,
              self.colors * 0.2345,
              sigma=0.5,
              offsets=offsets,
          )
      )
  
      # Splatting directly to the top/bottom/left/right should have the same strenght.
      non_diag_splats = splatting_colors_and_weights[
          :, :, :, :, torch.tensor([1, 3, 5, 7])
      ]
  
      # Same for diagonal splats.
      diag_splats = splatting_colors_and_weights[
          :, :, :, :, torch.tensor([0, 2, 6, 8])
      ]
  
      # And for self-splats.
      self_splats = splatting_colors_and_weights[
          :, :, :, :, torch.tensor([4])
      ]
  
      for splats in non_diag_splats, diag_splats, self_splats:
          # Colors should be equal.
          self.assertTrue(
              torch.all(splats[..., :4] == splats[0, 0, 0, 0, 0, 0])
          )
  
          # Weights should be equal.
          self.assertTrue(
              torch.all(splats[..., 4] == splats[0, 0, 0, 0, 0, 4])
          )
  
      # Non-diagonal weights should be greater than diagonal weights.
      self.assertGreater(
          non_diag_splats[0, 0, 0, 0, 0, 0],
          diag_splats[0, 0, 0, 0, 0, 0],
      )
  
      # Self-splats should be strongest of all.
      self.assertGreater(
          self_splats[0, 0, 0, 0, 0, 0],
          non_diag_splats[0, 0, 0, 0, 0, 0],
      )
  
      # Splatting colors should be reweighted proportionally to their splat weights.
      diag_self_color_ratio = (
          diag_splats[0, 0, 0, 0, 0, 0] / self_splats[0, 0, 0, 0, 0, 0]
      )
      diag_self_weight_ratio = (
          diag_splats[0, 0, 0, 0, 0, 4] / self_splats[0, 0, 0, 0, 0, 4]
      )
      self.assertEqual(diag_self_color_ratio, diag_self_weight_ratio)
  
      non_diag_self_color_ratio = (
          non_diag_splats[0, 0, 0, 0, 0, 0]
          / self_splats[0, 0, 0, 0, 0, 0]
      )
      non_diag_self_weight_ratio = (
          non_diag_splats[0, 0, 0, 0, 0, 4]
          / self_splats[0, 0, 0, 0, 0, 4]
      )
      self.assertEqual(
          non_diag_self_color_ratio, non_diag_self_weight_ratio
      )
  
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 2 for calling the TestComputeSplattingColorsAndWeights obj's underlying member method code with example usage: obj.test_all_equal() without return types