YOLOv8 训练报错:PyTorch 2.6+ 模型加载兼容性问题解决

问题

训练时报错,核心错误信息为_pickle.UnpicklingError: Weights only load failed,涉及torch.load函数的weights_only参数及DetectionModel类的加载限制

bash 复制代码
yolo8) yfzx@yfzx-4090:~/project/go2/yolov8_train$ python main.py
Ultralytics YOLOv8.3.176 🚀 Python-3.10.18 torch-2.8.0+cu128 CUDA:0 (NVIDIA GeForce RTX 4090, 24092MiB)
trainer: task=detect, mode=train, model=yolov8s.pt, data=coco128.yaml, epochs=300, time=None, patience=100, batch=16, imgsz=640, save=True, save_period=-1, cache=False, device=None, workers=8, project=None, name=train8, exist_ok=False, pretrained=True, optimizer=auto, verbose=True, seed=0, deterministic=True, single_cls=False, rect=False, cos_lr=False, close_mosaic=10, resume=False, amp=True, fraction=1.0, profile=False, freeze=None, multi_scale=False, overlap_mask=True, mask_ratio=4, dropout=0.0, val=True, split=val, save_json=False, save_hybrid=False, conf=None, iou=0.7, max_det=300, half=False, dnn=False, plots=True, source=None, vid_stride=1, stream_buffer=False, visualize=False, augment=False, agnostic_nms=False, classes=None, retina_masks=False, embed=None, save_dir=runs/detect/train8, show=False, save_frames=False, save_txt=False, save_conf=False, save_crop=False, show_labels=True, show_conf=True, show_boxes=True, line_width=None, format=torchscript, keras=False, optimize=False, int8=False, dynamic=False, simplify=True, opset=None, workspace=4, nms=False, lr0=0.01, lrf=0.01, momentum=0.937, weight_decay=0.0005, warmup_epochs=3.0, warmup_momentum=0.8, warmup_bias_lr=0.1, box=7.5, cls=0.5, dfl=1.5, pose=12.0, kobj=1.0, label_smoothing=0.0, nbs=64, hsv_h=0.015, hsv_s=0.7, hsv_v=0.4, degrees=0.0, translate=0.1, scale=0.5, shear=0.0, perspective=0.0, flipud=0.0, fliplr=0.5, bgr=0.0, mosaic=1.0, mixup=0.0, copy_paste=0.0, copy_paste_mode=flip, auto_augment=randaugment, erasing=0.4, crop_fraction=1.0, cfg=None, tracker=botsort.yaml
Traceback (most recent call last):
  File "/home/yfzx/project/go2/yolov8_train/main.py", line 7, in <module>
    trainer.train()
  File "/home/yfzx/project/go2/yolov8_train/yolov8/engine/trainer.py", line 198, in train
    self._do_train(world_size)
  File "/home/yfzx/project/go2/yolov8_train/yolov8/engine/trainer.py", line 312, in _do_train
    self._setup_train(world_size)
  File "/home/yfzx/project/go2/yolov8_train/yolov8/engine/trainer.py", line 226, in _setup_train
    ckpt = self.setup_model()
  File "/home/yfzx/project/go2/yolov8_train/yolov8/engine/trainer.py", line 530, in setup_model
    weights, ckpt = attempt_load_one_weight(model)
  File "/home/yfzx/project/go2/yolov8_train/yolov8/nn/tasks.py", line 806, in attempt_load_one_weight
    ckpt, weight = torch_safe_load(weight)  # load ckpt
  File "/home/yfzx/project/go2/yolov8_train/yolov8/nn/tasks.py", line 732, in torch_safe_load
    ckpt = torch.load(file, map_location="cpu")
  File "/home/yfzx/conda/anaconda/envs/yolo8/lib/python3.10/site-packages/torch/serialization.py", line 1529, in load
    raise pickle.UnpicklingError(_get_wo_message(str(e))) from None
_pickle.UnpicklingError: Weights only load failed. This file can still be loaded, to do so you have two options, do those steps only if you trust the source of the checkpoint.
        (1) In PyTorch 2.6, we changed the default value of the `weights_only` argument in `torch.load` from `False` to `True`. Re-running `torch.load` with `weights_only` set to `False` will likely succeed, but it can result in arbitrary code execution. Do it only if you got the file from a trusted source.
        (2) Alternatively, to load with `weights_only=True` please check the recommended steps in the following error message.
        WeightsUnpickler error: Unsupported global: GLOBAL ultralytics.nn.tasks.DetectionModel was not an allowed global by default. Please use `torch.serialization.add_safe_globals([ultralytics.nn.tasks.DetectionModel])` or the `torch.serialization.safe_globals([ultralytics.nn.tasks.DetectionModel])` context manager to allowlist this global if you trust this class/function.

Check the documentation of torch.load to learn more about types accepted by default with weights_only https://pytorch.org/docs/stable/generated/torch.load.html.

报错原因

PyTorch 2.6 及以上版本中,torch.load函数的weights_only参数默认值从False改为True。

参数设为True时,为安全起见仅允许加载权重数据,禁止执行模型文件中可能包含的自定义类代码。

YOLOv8 的模型文件(如yolov8s.pt)包含自定义的DetectionModel类序列化信息,因此被拦截。

解决方法

临时允许加载完整模型

修改 YOLOv8 代码中加载模型的部分,显式设置weights_only=False。

找到报错中提到的torch_safe_load函数(路径:yolov8/nn/tasks.py第 732 行),将:

python 复制代码
ckpt = torch.load(file, map_location="cpu")

修改为

python 复制代码
ckpt = torch.load(file, map_location="cpu", weights_only=False)  # 关闭安全检查

再次运行即可

相关推荐
Hy行者勇哥1 小时前
除 OpenAI/GPT-4o 等主流头部产品外,值得关注的 AI 及 Agent 产品有哪些?
人工智能
paopaokaka_luck1 小时前
基于SpringBoot+Vue的志行交通法规在线模拟考试(AI问答、WebSocket即时通讯、Echarts图形化分析、随机测评)
vue.js·人工智能·spring boot·后端·websocket·echarts
张较瘦_2 小时前
[论文阅读] AI+软件工程(DeBug)| 从11%到53%!双LLM驱动的工业级代码修复方案,Google数据集验证有效
论文阅读·人工智能·软件工程
奔跑的石头_2 小时前
GPT-5最新特性和优点
人工智能
MPCTHU2 小时前
Deep Learning|01 RBF Network
人工智能·深度学习
wa的一声哭了2 小时前
Deep Learning Optimizer | Adam、AdamW
人工智能·深度学习·神经网络·机器学习·自然语言处理·transformer·pytest
晨曦5432102 小时前
机器学习完整流程详解
人工智能·机器学习
算法与编程之美2 小时前
探索flatten的其他参数用法及对报错异常进行修正
人工智能·pytorch·python·深度学习·机器学习
IT_陈寒2 小时前
5种JavaScript性能优化技巧:从V8引擎原理到实战提速200%
前端·人工智能·后端
N0nename2 小时前
Inception V3--J9
人工智能·深度学习·计算机视觉