--- a
+++ b/main.py
@@ -0,0 +1,22 @@
+import glob
+import sys
+
+from args import get_args_parser
+from data import get_loaders, generate_data, split_data
+from model import eegt
+from engine import prepare_training, train_model
+from torchsummary import summary
+
+if __name__ == "__main__":
+    parser = get_args_parser()
+    args = parser.parse_args(args=[])
+    sys.stdout = open('logs/exp_4000_drop_5e-6.txt', 'w')
+    model, optimizer, lr_scheduler, criterion, device, _ = prepare_training(args)
+    print(summary(model, (59, 4000)))
+
+    calib_files = glob.glob('data/*.mat')
+    X, y = generate_data(calib_files)
+    train_X, train_y, val_X, val_y, test_X, test_y = split_data(X, y)
+    dataloaders = get_loaders(train_X, train_y, val_X, val_y, test_X, test_y)
+    
+    best_model = train_model(model, criterion, optimizer, lr_scheduler, device, dataloaders)