code: def preprocess_frame(frame):
      """Preprocess frame.
  
      1. Converts [0, 255] to [-0.5, 0.5]
      2. Adds uniform noise.
  
      Args:
        frame: 3-D Tensor representing pixels.
      Returns:
        frame: 3-D Tensor with values in between [-0.5, 0.5]
      """
      # Normalize from [0.0, 1.0] -> [-0.5, 0.5]
      frame = common_layers.convert_rgb_to_real(frame)
      frame = frame - 0.5
      frame, _ = glow_ops.uniform_binning_correction(frame)
      return frame
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  from absl import flags
  import numpy
  from six.moves import zip
  from tensor2tensor.bin import t2t_trainer
  from tensor2tensor.data_generators import image_utils
  from tensor2tensor.layers import common_layers
  from tensor2tensor.layers import common_video
  from tensor2tensor.models.research import glow_ops
  from tensor2tensor.utils import contrib
  from tensor2tensor.utils import decoding
  from tensor2tensor.utils import trainer_lib
  import tensorflow.compat.v1
  from tensorflow.compat.v1 import estimator
label_desc: Use image node_id 2 for calling a global function with example usage: preprocess_frame(frame) and returns: frame