update val

utils/utils_fit.py

@@ -77,12 +77,11 @@ def fit_one_epoch(model_train, model, ema, yolo_loss, loss_history, eval_callbac
     for iteration, batch in enumerate(gen_val):
         if iteration >= epoch_step_val:
             break
-        images, targets, y_trues = batch[0], batch[1], batch[2]
+        images, targets = batch[0], batch[1]
         with torch.no_grad():
             if cuda:
                 images  = images.cuda(local_rank)
-                targets = [ann.cuda(local_rank) for ann in targets]
-                y_trues = [ann.cuda(local_rank) for ann in y_trues]
+                targets = targets.cuda(local_rank)
             #----------------------#
             #   清零梯度
             #----------------------#
@@ -91,15 +90,7 @@ def fit_one_epoch(model_train, model, ema, yolo_loss, loss_history, eval_callbac
             #   前向传播
             #----------------------#
             outputs         = model_train_eval(images)
-
-            loss_value_all  = 0
-            #----------------------#
-            #   计算损失
-            #----------------------#
-            for l in range(len(outputs)):
-                loss_item = yolo_loss(l, outputs[l], targets, y_trues[l])
-                loss_value_all  += loss_item
-            loss_value  = loss_value_all
+            loss_value      = yolo_loss(outputs, targets, images)
 
         val_loss += loss_value.item()
         if local_rank == 0: