DDP after autoanchor reorder (ultralytics#2421)

train.py

@@ -181,10 +181,6 @@ def train(hyp, opt, device, tb_writer=None, wandb=None):
         model = torch.nn.SyncBatchNorm.convert_sync_batchnorm(model).to(device)
         logger.info('Using SyncBatchNorm()')
 
-    # DDP mode
-    if cuda and rank != -1:
-        model = DDP(model, device_ids=[opt.local_rank], output_device=opt.local_rank)
-
     # Trainloader
     dataloader, dataset = create_dataloader(train_path, imgsz, batch_size, gs, opt,
                                             hyp=hyp, augment=True, cache=opt.cache_images, rect=opt.rect, rank=rank,
@@ -214,7 +210,11 @@ def train(hyp, opt, device, tb_writer=None, wandb=None):
             # Anchors
             if not opt.noautoanchor:
                 check_anchors(dataset, model=model, thr=hyp['anchor_t'], imgsz=imgsz)
-            model.half().float()  # pre-reduce anchor precision 
+            model.half().float()  # pre-reduce anchor precision
+
+    # DDP mode
+    if cuda and rank != -1:
+        model = DDP(model, device_ids=[opt.local_rank], output_device=opt.local_rank)
 
     # Model parameters
     hyp['box'] *= 3. / nl  # scale to layers