code: def cycle_gan_small():
    
    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
docs: Set of hyperparameters.