code: def test_offset(self):
      device = torch.device("cuda:0")
      N, H, W, K = 2, 3, 4, 5
      colors_and_weights = torch.rand((N, H, W, K, 9, 5), device=device)
      crop_ids_h, crop_ids_w, _ = _precompute(
          (N, H, W, K), device=device
      )
      offset_colors_and_weights = _offset_splats(
          colors_and_weights, crop_ids_h, crop_ids_w
      )
  
      # Check each splatting direction individually, for clarity.
      # offset_x, offset_y = (-1, -1)
      direction = 0
      self.assertClose(
          offset_colors_and_weights[:, 1:, 1:, :, direction],
          colors_and_weights[:, :-1, :-1, :, direction],
          atol=0.001,
      )
      self.assertTrue(
          torch.all(
              offset_colors_and_weights[:, 0, :, :, direction] == 0.0
          )
      )
      self.assertTrue(
          torch.all(
              offset_colors_and_weights[:, :, 0, :, direction] == 0.0
          )
      )
  
      # offset_x, offset_y = (-1, 0)
      direction = 1
      self.assertClose(
          offset_colors_and_weights[:, :, 1:, :, direction],
          colors_and_weights[:, :, :-1, :, direction],
          atol=0.001,
      )
      self.assertTrue(
          torch.all(
              offset_colors_and_weights[:, :, 0, :, direction] == 0.0
          )
      )
  
      # offset_x, offset_y = (-1, 1)
      direction = 2
      self.assertClose(
          offset_colors_and_weights[:, :-1, 1:, :, direction],
          colors_and_weights[:, 1:, :-1, :, direction],
          atol=0.001,
      )
      self.assertTrue(
          torch.all(
              offset_colors_and_weights[:, -1, :, :, direction] == 0.0
          )
      )
      self.assertTrue(
          torch.all(
              offset_colors_and_weights[:, :, 0, :, direction] == 0.0
          )
      )
  
      # offset_x, offset_y = (0, -1)
      direction = 3
      self.assertClose(
          offset_colors_and_weights[:, 1:, :, :, direction],
          colors_and_weights[:, :-1, :, :, direction],
          atol=0.001,
      )
      self.assertTrue(
          torch.all(
              offset_colors_and_weights[:, 0, :, :, direction] == 0.0
          )
      )
  
      # self-splat
      direction = 4
      self.assertClose(
          offset_colors_and_weights[..., direction, :],
          colors_and_weights[..., direction, :],
          atol=0.001,
      )
  
      # offset_x, offset_y = (0, 1)
      direction = 5
      self.assertClose(
          offset_colors_and_weights[:, :-1, :, :, direction],
          colors_and_weights[:, 1:, :, :, direction],
          atol=0.001,
      )
      self.assertTrue(
          torch.all(
              offset_colors_and_weights[:, -1, :, :, direction] == 0.0
          )
      )
  
      # offset_x, offset_y = (1, -1)
      direction = 6
      self.assertClose(
          offset_colors_and_weights[:, 1:, :-1, :, direction],
          colors_and_weights[:, :-1, 1:, :, direction],
          atol=0.001,
      )
      self.assertTrue(
          torch.all(
              offset_colors_and_weights[:, 0, :, :, direction] == 0.0
          )
      )
      self.assertTrue(
          torch.all(
              offset_colors_and_weights[:, :, -1, :, direction] == 0.0
          )
      )
  
      # offset_x, offset_y = (1, 0)
      direction = 7
      self.assertClose(
          offset_colors_and_weights[:, :, :-1, :, direction],
          colors_and_weights[:, :, 1:, :, direction],
          atol=0.001,
      )
      self.assertTrue(
          torch.all(
              offset_colors_and_weights[:, :, -1, :, direction] == 0.0
          )
      )
  
      # offset_x, offset_y = (1, 1)
      direction = 8
      self.assertClose(
          offset_colors_and_weights[:, :-1, :-1, :, direction],
          colors_and_weights[:, 1:, 1:, :, direction],
          atol=0.001,
      )
      self.assertTrue(
          torch.all(
              offset_colors_and_weights[:, -1, :, :, direction] == 0.0
          )
      )
      self.assertTrue(
          torch.all(
              offset_colors_and_weights[:, :, -1, :, direction] == 0.0
          )
      )
  
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 1 for calling the TestOffsetSplats obj's underlying member method code with example usage: obj.test_offset() without return types