code: def test_invert_colorize(rgb_min):
      transfo = T.ColorInversion(min_val=rgb_min)
      input_t = tf.cast(tf.fill([8, 32, 32, 3], 1), dtype=tf.float32)
      out = transfo(input_t)
      assert tf.reduce_all(out <= 1 - rgb_min + 1e-4)
      assert tf.reduce_all(out >= 0)
  
      input_t = tf.cast(tf.fill([8, 32, 32, 3], 255), dtype=tf.uint8)
      out = transfo(input_t)
      assert tf.reduce_all(out <= int(math.ceil(255 * (1 - rgb_min))))
      assert tf.reduce_all(out >= 0)
  
      # FP16
      input_t = tf.cast(tf.fill([8, 32, 32, 3], 1), dtype=tf.float16)
      out = transfo(input_t)
      assert out.dtype == tf.float16
  
imports: import math
  import numpy
  import pytest
  import tensorflow
  from doctr import transforms
  from doctr.transforms.functional import crop_detection, rotate_sample
label_desc: Use image node_id 6 for calling a global function with example usage: test_invert_colorize(rgb_min) without return types