code: def autoencoder_residual():
    
    hparams = autoencoder_autoregressive()
    hparams.optimizer = "Adafactor"
    hparams.clip_grad_norm = 1.0
    hparams.learning_rate_constant = 0.5
    hparams.learning_rate_warmup_steps = 500
    hparams.learning_rate_schedule = "constant * linear_warmup * rsqrt_decay"
    hparams.num_hidden_layers = 5
    hparams.hidden_size = 64
    hparams.max_hidden_size = 1024
    hparams.add_hparam("num_residual_layers", 2)
    hparams.add_hparam("residual_kernel_height", 3)
    hparams.add_hparam("residual_kernel_width", 3)
    hparams.add_hparam("residual_filter_multiplier", 2.0)
    hparams.add_hparam("residual_dropout", 0.2)
    hparams.add_hparam("residual_use_separable_conv", int(True))
    hparams.add_hparam("kl_beta", 1.0)
    return hparams
docs: Residual autoencoder model.