ciss_vae.training.autotune.autotune

autotune(search_space, train_dataset, save_model_path=None, save_search_space_path=None, n_trials=20, study_name='vae_autotune', device_preference='cuda', optuna_dashboard_db=None, load_if_exists=True, seed=42, verbose=False, show_progress=False, constant_layer_size=False, evaluate_all_orders=False, max_exhaustive_orders=100, return_history=False, n_jobs=1, debug=False)

Optuna-based hyperparameter search for the CISSVAE model.

Runs initial training followed by impute-refit loops per trial, selecting the

trial with the lowest total imputation error (MSE + BCE + categorical CE). The best model is then retrained with

optimal hyperparameters and returned along with the imputed dataset.