Model freeze capability (ultralytics#679)

train.py

@@ -73,6 +73,14 @@ def train(hyp, opt, device, tb_writer=None):
     else:
         model = Model(opt.cfg, ch=3, nc=nc).to(device)  # create
 
+    # Freeze
+    freeze = ['', ]  # parameter names to freeze (full or partial)
+    if any(freeze):
+        for k, v in model.named_parameters():
+            if any(x in k for x in freeze):
+                print('freezing %s' % k)
+                v.requires_grad = False
+
     # Optimizer
     nbs = 64  # nominal batch size
     accumulate = max(round(nbs / total_batch_size), 1)  # accumulate loss before optimizing
@@ -125,7 +133,7 @@ def train(hyp, opt, device, tb_writer=None):
             epochs += ckpt['epoch']  # finetune additional epochs
 
         del ckpt, state_dict
-    
+
     # Image sizes
     gs = int(max(model.stride))  # grid size (max stride)
     imgsz, imgsz_test = [check_img_size(x, gs) for x in opt.img_size]  # verify imgsz are gs-multiples