code: def test_invalid_channels_value():
      x_np = np.random.rand(4, 2, 4) * 255.0
      scale = np.random.rand() * 2.0 - 1.0
      if tf.executing_eagerly():
          with pytest.raises(
              (tf.errors.InvalidArgumentError, ValueError),
              match="input must have 3 channels but instead has 4",
          ):
              _adjust_value_in_yiq_tf(x_np, scale)
      else:
          with pytest.raises(
              ValueError, match="Dimension must be 3 but is 4"
          ):
              _adjust_value_in_yiq_tf(x_np, scale)
  
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 12 for calling a global function with example usage: test_invalid_channels_value() without return types