[20230424 v0.4.0] Fix: drop_last=True

main.py

@@ -14,7 +14,7 @@
 from termcolor import cprint
 
 from engine import evaluate, train_one_epoch
-from qtcls import build_criterion, build_dataset, build_model, build_optimizer, build_scheduler
+from qtcls import __version__, build_criterion, build_dataset, build_model, build_optimizer, build_scheduler
 from qtcls.utils.io import checkpoint_saver, checkpoint_loader, variables_loader, variables_saver
 from qtcls.utils.misc import makedirs, init_distributed_mode, init_seeds, is_main_process
 
@@ -44,7 +44,7 @@ def get_args_parser():
     parser.add_argument('--print_freq', type=int, default=50)
     parser.add_argument('--need_targets', action='store_true', help='need targets for training')
     parser.add_argument('--drop_lr_now', action='store_true')
-    parser.add_argument('--drop_last', action='store_true')
+    parser.add_argument('--drop_last', type=bool, default=True)
     parser.add_argument('--amp', action='store_true', help='automatic mixed precision training')
     parser.add_argument('--no_dist', action='store_true', help='forcibly disable distributed mode')
 
@@ -108,6 +108,7 @@ def get_args_parser():
 def main(args):
     init_seeds(args.seed)
     init_distributed_mode(args)
+    cprint(f'QTClassification v{__version__}', 'light_green', attrs=['bold'])
     device = torch.device(args.device if torch.cuda.is_available() else 'cpu')
     if device.type == 'cpu' or args.eval:
         args.amp = False