code: def next_frame_basic_deterministic():
      """Basic 2-frame conv model."""
      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
  
imports: from __future__ import division
  from __future__ import print_function
  from tensor2tensor.layers import modalities
  from tensor2tensor.models.video import base
  from tensor2tensor.utils import registry
label_desc: Use image node_id 1 for calling a global function with example usage: next_frame_basic_deterministic() and returns: hparams