Set of hyperparameters.

def cycle_gan_small():
  """Set of hyperparameters."""
  hparams = transformer_vae.transformer_ae_small()
  hparams.batch_size = 2048
  hparams.bottom = {
      "inputs": modalities.identity_bottom,
      "targets": modalities.identity_bottom,
  }
  hparams.top = {
      "targets": modalities.identity_top,
  }
  hparams.weight_decay = 3.0
  hparams.learning_rate = 0.05
  hparams.kl_warmup_steps = 5000
  hparams.learning_rate_warmup_steps = 3000
  hparams.add_hparam("vocab_size", 66)  # Vocabulary size, need to set here.
  hparams.add_hparam("cycle_loss_multiplier1", 10.0)
  hparams.add_hparam("cycle_loss_multiplier2", 10.0)
  return hparams