code: def _create_image_array(
      shape: tuple[int, int, int]
  ) -> np.ndarray[np.uint8]:
      height, width, channels = shape
      array = np.zeros(shape=shape, dtype=np.uint8)
      for i in range(1000):
          array[i % height, i % width, i % channels] = i % 256
      return array
  
file_path: lit/lit_nlp/lib/image_utils_test.py
imports: from absl.testing import absltest
  from absl.testing import parameterized
  from lit_nlp.lib import image_utils
  import numpy
  from PIL import Image
label_desc: Use image node_id 1 for calling a global function with example usage: _create_image_array(shape) and returns: array