code: def next_frame_basic_deterministic():
    
    hparams = base.next_frame_base()
    hparams.video_num_input_frames = 4
    hparams.video_num_target_frames = 1
    hparams.hidden_size = 64
    hparams.batch_size = 4
    hparams.num_hidden_layers = 2
    hparams.optimizer = "Adafactor"
    hparams.learning_rate_constant = 1.5
    hparams.learning_rate_warmup_steps = 8000
    hparams.learning_rate_schedule = "linear_warmup * constant * rsqrt_decay"
    hparams.label_smoothing = 0.0
    hparams.initializer = "uniform_unit_scaling"
    hparams.initializer_gain = 1.3
    hparams.weight_decay = 0.0
    hparams.clip_grad_norm = 1.0
    hparams.dropout = 0.1
    hparams.add_hparam("residual_dropout", 0.5)
    hparams.add_hparam("num_compress_steps", 6)
    hparams.add_hparam("filter_double_steps", 2)
    hparams.add_hparam("pixel_sampling_temperature", 0.0)
    hparams.add_hparam("concat_internal_states", False)
    hparams.add_hparam("do_autoregressive_rnn", False)
    hparams.add_hparam("autoregressive_rnn_lookback", 8)
    hparams.add_hparam("autoregressive_rnn_warmup_steps", 8000)
    hparams.add_hparam("activation_fn", "relu")
    hparams.bottom["inputs"] = modalities.video_identity_bottom
    hparams.bottom["targets"] = modalities.video_identity_bottom
    return hparams
docs: Basic 2-frame conv model.