code: def postprocess(x, n_bits_x=8):
      """Converts x from [-0.5, 0.5], to [0, 255].
  
      Args:
        x: 3-D or 4-D Tensor normalized between [-0.5, 0.5]
        n_bits_x: Number of bits representing each pixel of the output.
                  Defaults to 8, to default to 256 possible values.
      Returns:
        x: 3-D or 4-D Tensor representing images or videos.
      """
      x = tf.where(tf.is_finite(x), x, tf.ones_like(x))
      x = tf.clip_by_value(x, -0.5, 0.5)
      x += 0.5
      x = x * 2**n_bits_x
      return tf.cast(tf.clip_by_value(x, 0, 255), dtype=tf.uint8)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import functools
  import numpy
  import scipy
  from tensor2tensor.layers import common_layers
  from tensor2tensor.layers import common_video
  from tensor2tensor.utils import contrib
  import tensorflow.compat.v1
  from tensorflow.compat.v1 import estimator
  import tensorflow_probability
label_desc: Use image node_id 3 for calling a global function with example usage: postprocess(x, n_bits_x) and returns: tf