code: def next_frame_glow_shapes():
      """Hparams for qualitative and quantitative results on shapes dataset."""
      hparams = next_frame_glow_bair_quant()
      hparams.video_num_input_frames = 1
      hparams.video_num_target_frames = 2
      hparams.num_train_frames = 2
      hparams.num_cond_latents = 1
      hparams.coupling = "additive"
      hparams.coupling_width = 512
      hparams.latent_encoder_depth = 10
      hparams.latent_skip = False
      hparams.learning_rate_constant = 1e-4
      hparams.batch_size = 10
      return hparams
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import numpy
  from six.moves import range
  from tensor2tensor.layers import common_layers
  from tensor2tensor.layers import common_video
  from tensor2tensor.layers import modalities
  from tensor2tensor.models.research import glow
  from tensor2tensor.models.research import glow_ops
  from tensor2tensor.utils import contrib
  from tensor2tensor.utils import registry
  import tensorflow.compat.v1
  import tensorflow_probability
label_desc: Use image node_id 4 for calling a global function with example usage: next_frame_glow_shapes() and returns: hparams