调试

app/yolov5/train_server.py

@@ -467,18 +467,14 @@ def train(hyp, opt, device, data_list,id,callbacks):  # hyp is path/to/hyp.yaml
     # end training -----------------------------------------------------------------------------------------------------
     if RANK in {-1, 0}:
         LOGGER.info(f'\n{epoch - start_epoch + 1} epochs completed in {(time.time() - t0) / 3600:.3f} hours.')
-        print('##############',best)
-        for f in best:
-            print('##################',f)
         if os.path.exists(best):
-                strip_optimizer(f)  # strip optimizers
-                if f is best:
+            strip_optimizer(best)  # strip optimizers
             LOGGER.info(f'\nValidating {f}...')
             results, _, _ = validate.run(
                 data_dict,
                 batch_size=batch_size // WORLD_SIZE * 2,
                 imgsz=imgsz,
-                        model=attempt_load(f, device).half(),
+                model=attempt_load(best, device).half(),
                 iou_thres=0.65 if is_coco else 0.60,  # best pycocotools at iou 0.65
                 single_cls=single_cls,
                 dataloader=val_loader,
@@ -490,7 +486,6 @@ def train(hyp, opt, device, data_list,id,callbacks):  # hyp is path/to/hyp.yaml
                 compute_loss=compute_loss)  # val best model with plots
             if is_coco:
                 callbacks.run('on_fit_epoch_end', list(mloss) + list(results) + lr, epoch, best_fitness, fi)
-
         #callbacks.run('on_train_end', best, epoch, results)
 
     torch.cuda.empty_cache()