code: def test_tiles_split_merge():
      image = np.random.random((500, 500, 3)).astype(np.uint8)
      tiler = ImageSlicer(
          image.shape, tile_size=51, tile_step=26, weight="mean"
      )
      tiles = tiler.split(image)
      merged = tiler.merge(tiles, dtype=np.uint8)
      np.testing.assert_equal(merged, image)
  
file_path: pytorch-toolbelt/tests/test_tiles.py
imports: import numpy
  import torch
  from pytorch_toolbelt.inference.tiles import ImageSlicer, CudaTileMerger
  from pytorch_toolbelt.utils.torch_utils import tensor_from_rgb_image, rgb_image_from_tensor, to_numpy
  from torch import nn
  from torch.utils.data import DataLoader
  import pytest
label_desc: Use image node_id 1 for calling a global function with example usage: test_tiles_split_merge() without return types