code: def test_adjust_random_value_in_yiq():
      x_shapes = [
          [2, 2, 3],
          [4, 2, 3],
          [2, 4, 3],
          [2, 5, 3],
          [1000, 1, 3],
      ]
      test_styles = [
          "all_random",
          "rg_same",
          "rb_same",
          "gb_same",
          "rgb_same",
      ]
      for x_shape in x_shapes:
          for test_style in test_styles:
              x_np = np.random.rand(*x_shape) * 255.0
              scale = np.random.rand() * 2.0 - 1.0
              if test_style == "all_random":
                  pass
              elif test_style == "rg_same":
                  x_np[..., 1] = x_np[..., 0]
              elif test_style == "rb_same":
                  x_np[..., 2] = x_np[..., 0]
              elif test_style == "gb_same":
                  x_np[..., 2] = x_np[..., 1]
              elif test_style == "rgb_same":
                  x_np[..., 1] = x_np[..., 0]
                  x_np[..., 2] = x_np[..., 0]
              else:
                  raise AssertionError(
                      "Invalid test style: %s" % (test_style)
                  )
              y_np = _adjust_value_in_yiq_np(x_np, scale)
              y_tf = _adjust_value_in_yiq_tf(x_np, scale)
              np.testing.assert_allclose(
                  y_tf, y_np, rtol=2e-4, atol=1e-4
              )
  
imports: import pytest
  import numpy
  import tensorflow
  from tensorflow_addons.image import distort_image_ops
  from tensorflow_addons.utils import test_utils
label_desc: Use image node_id 10 for calling a global function with example usage: test_adjust_random_value_in_yiq() without return types