code: def test_tiler_handles_single_image_without_batch_dimension(
      image_size, tile_size, stride, shape, use_random_tiling
  ):
      """Tiler should add batch dimension if image is 3D (CxHxW)."""
      tiler = Tiler(tile_size=tile_size, stride=stride)
      image = torch.rand(image_size)
      patches = tiler.tile(image, use_random_tiling=use_random_tiling)
      assert patches.shape == shape
  
file_path: anomalib/tests/pre_merge/datasets/test_tiler.py
imports: import pytest
  import torch
  from omegaconf import ListConfig
  from anomalib.pre_processing.tiler import StrideSizeError, Tiler
label_desc: Use image node_id 2 for calling a global function with example usage: test_tiler_handles_single_image_without_batch_dimension(image_size, tile_size, stride, shape, use_random_tiling) without return types