code: def test_should_transform_gradients_to_grayscale():
      gradients = tf.random.uniform((4, 28, 28, 3))
  
      grayscale_gradients = transform_to_normalized_grayscale(gradients)
      expected_output_shape = (4, 28, 28)
  
      assert grayscale_gradients.shape == expected_output_shape
  
imports: import numpy
  import tensorflow
  from tf_explain.utils.image import apply_grey_patch, transform_to_normalized_grayscale
label_desc: Use image node_id 2 for calling a global function with example usage: test_should_transform_gradients_to_grayscale() without return types