code: def next_frame_sv2p_discrete():
      """SV2P discrete model hparams."""
      hparams = next_frame_sv2p()
      hparams.action_injection = "multiplicative"
      hparams.small_mode = True
      hparams.add_hparam("bottleneck_bits", 128)
      hparams.add_hparam("bottleneck_noise", 0.02)
      hparams.add_hparam("discrete_warmup_steps", 40000)
      hparams.add_hparam("full_latent_tower", False)
      hparams.add_hparam("latent_predictor_state_size", 128)
      hparams.add_hparam("latent_predictor_temperature", 0.5)
      hparams.add_hparam("discretize_warmup_steps", 40000)
      return hparams
  
file_path: tensor2tensor/tensor2tensor/models/video/sv2p_params.py
imports: from __future__ import division
  from __future__ import print_function
  from tensor2tensor.layers import modalities
  from tensor2tensor.models.video import basic_stochastic
  from tensor2tensor.utils import registry
label_desc: Use image node_id 2 for calling a global function with example usage: next_frame_sv2p_discrete() and returns: hparams