code: def next_frame_sampling_stochastic():
    
    hparams = basic_deterministic_params.next_frame_sampling()
    hparams.stochastic_model = True
    hparams.add_hparam("latent_channels", 1)
    hparams.add_hparam("latent_std_min", -5.0)
    hparams.add_hparam("num_iterations_1st_stage", 15000)
    hparams.add_hparam("num_iterations_2nd_stage", 15000)
    hparams.add_hparam("latent_loss_multiplier", 1e-3)
    hparams.add_hparam("latent_loss_multiplier_dynamic", False)
    hparams.add_hparam("latent_loss_multiplier_alpha", 1e-5)
    hparams.add_hparam("latent_loss_multiplier_epsilon", 1.0)
    hparams.add_hparam("latent_loss_multiplier_schedule", "constant")
    hparams.add_hparam("latent_num_frames", 0)  # 0 means use all frames.
    hparams.add_hparam("anneal_end", 40000)
    hparams.add_hparam("information_capacity", 0.0)
    return hparams
docs: Basic 2-frame conv model with stochastic tower.