code: def latents_to_frames(z_top_interp, level_eps_interp, hparams):
      """Decodes latents to frames."""
      # Decode [z^1_t, z^2_t .. z^l_t] to [X_t]
      images, _, _, _ = glow_ops.encoder_decoder(
          "codec",
          z_top_interp,
          hparams,
          eps=level_eps_interp,
          reverse=True,
      )
      images = glow_ops.postprocess(images)
      return images
  
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 4 for calling a global function with example usage: latents_to_frames(z_top_interp, level_eps_interp, hparams) and returns: images