code: def next_frame_emily():
      """Emily's model hparams."""
      hparams = sv2p_params.next_frame_sv2p()
      hparams.video_num_input_frames = 2
      hparams.video_num_target_frames = 10
      hparams.learning_rate_constant = 1e-4
      seq_length = (
          hparams.video_num_input_frames
          + hparams.video_num_target_frames
      )
      # The latent_loss_multiplier is divided by the number of frames because
      # the image sequence loss in t2t is averaged instead of added through
      # time as they do in the SVG-LP paper
      hparams.latent_loss_multiplier = 1e-4 / seq_length
      hparams.reward_prediction = False
      hparams.num_iterations_1st_stage = -1
      hparams.num_iterations_2nd_stage = -1
      hparams.optimizer_adam_beta1 = 0.9
      hparams.optimizer_adam_beta2 = 0.999
      hparams.optimizer_adam_epsilon = 1e-08
      hparams.anneal_end = -1
      hparams.clip_grad_norm = 5.0
      hparams.add_hparam("learned_prior", True)
      hparams.add_hparam("z_dim", 64)
      hparams.add_hparam("g_dim", 128)
      hparams.add_hparam("rnn_size", 256)
      hparams.add_hparam("prior_rnn_layers", 1)
      hparams.add_hparam("posterior_rnn_layers", 1)
      hparams.add_hparam("predictor_rnn_layers", 2)
      hparams.add_hparam("has_skips", True)
      hparams.add_hparam("has_batchnorm", True)
      # Repeat actions to signify gradients.
      # Action type can be '', 'image' or 'vector'.
      hparams.add_hparam("action_repeat", 40)
      hparams.add_hparam("action_type", "")
      return hparams
  
file_path: tensor2tensor/tensor2tensor/models/video/emily.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from tensor2tensor.layers import common_layers
  from tensor2tensor.layers import common_video
  from tensor2tensor.models.video import sv2p
  from tensor2tensor.models.video import sv2p_params
  from tensor2tensor.utils import contrib
  from tensor2tensor.utils import registry
  import tensorflow.compat.v1
label_desc: Use image node_id 1 for calling a global function with example usage: next_frame_emily() and returns: hparams