`--freeze` fix (#6044)

train.py

@@ -60,7 +60,7 @@ def train(hyp,  # path/to/hyp.yaml or hyp dictionary
           device,
           callbacks
           ):
-    save_dir, epochs, batch_size, weights, single_cls, evolve, data, cfg, resume, noval, nosave, workers, freeze, = \
+    save_dir, epochs, batch_size, weights, single_cls, evolve, data, cfg, resume, noval, nosave, workers, freeze = \
         Path(opt.save_dir), opt.epochs, opt.batch_size, opt.weights, opt.single_cls, opt.evolve, opt.data, opt.cfg, \
         opt.resume, opt.noval, opt.nosave, opt.workers, opt.freeze
 
@@ -124,7 +124,7 @@ def train(hyp,  # path/to/hyp.yaml or hyp dictionary
         model = Model(cfg, ch=3, nc=nc, anchors=hyp.get('anchors')).to(device)  # create
 
     # Freeze
-    freeze = [f'model.{x}.' for x in (freeze if isinstance(freeze, list) else range(freeze))]  # layers to freeze
+    freeze = [f'model.{x}.' for x in (freeze if len(freeze) > 1 else range(freeze[0]))]  # layers to freeze
     for k, v in model.named_parameters():
         v.requires_grad = True  # train all layers
         if any(x in k for x in freeze):
@@ -469,7 +469,7 @@ def parse_opt(known=False):
     parser.add_argument('--linear-lr', action='store_true', help='linear LR')
     parser.add_argument('--label-smoothing', type=float, default=0.0, help='Label smoothing epsilon')
     parser.add_argument('--patience', type=int, default=100, help='EarlyStopping patience (epochs without improvement)')
-    parser.add_argument('--freeze', nargs='+', type=int, default=0, help='Freeze layers: backbone=10, first3=0 1 2')
+    parser.add_argument('--freeze', nargs='+', type=int, default=[0], help='Freeze layers: backbone=10, first3=0 1 2')
     parser.add_argument('--save-period', type=int, default=-1, help='Save checkpoint every x epochs (disabled if < 1)')
     parser.add_argument('--local_rank', type=int, default=-1, help='DDP parameter, do not modify')