code: def test_gamma():
      transfo = T.RandomGamma(
          min_gamma=1.0, max_gamma=2.0, min_gain=0.8, max_gain=1.0
      )
      input_t = tf.cast(tf.fill([8, 32, 32, 3], 2.0), dtype=tf.float32)
      out = transfo(input_t)
  
      assert tf.reduce_all(out >= 1.6)
      assert tf.reduce_all(out <= 4.0)
  
      # FP16
      input_t = tf.cast(tf.fill([8, 32, 32, 3], 2.0), 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 11 for calling a global function with example usage: test_gamma() without return types