import os
import argparse
import warnings
from train import Trainer
import sklearn.exceptions
warnings.filterwarnings("ignore", category=sklearn.exceptions.UndefinedMetricWarning)

parser = argparse.ArgumentParser()

# ========  Experiments Name ================
parser.add_argument('--save_dir',               default='experiments_logs',         type=str,
                    help='Directory containing all experiments')
parser.add_argument('--experiment_description', default='Exp1',   type=str, help='experiment name')
parser.add_argument('--run_description',        default='run1',     type=str, help='run name')

# ========= Select the DATASET ==============
parser.add_argument('--dataset',                default='mit',           type=str, help='mit, ptb')
parser.add_argument('--seed_id',                default='0',             type=str,
                    help='to fix a seed while training')

# ========= Experiment settings ===============
parser.add_argument('--data_path',              default=r'/Users/splendor1811/datn/ECGTransForm/datasets',
                    type=str, help='Path containing dataset')

parser.add_argument('--num_runs',               default=1,                 type=int,
                    help='Number of consecutive run with different seeds')
parser.add_argument('--device',                 default='mps',            type=str,
                    help='cpu or cuda')


args = parser.parse_args()

if __name__ == "__main__":
    trainer = Trainer(args)
    trainer.train()