yolo加模块报错RuntimeError: Input type and weight type should be the same

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当yolo增加一些模块的时候训练完第一轮进行验证的时候就报错

RuntimeError: Input type (torch.cuda.FloatTensor) and weight type (torch.cuda.HalfTensor) should be the same

主要是混合精度的问题

解决方案:

1、把amp=False

2、到ultralytics/engine/validator.py文件里面 crtl+f搜索half

self.args.half = self.device.type != 'cpu'  # force FP16 val during training

注释掉,然后增加一个

self.args.half =False
然后重新训练就ok了,如果跑其他的再改回去

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YOLO(You Only Look Once)是一种流行的物体检测和图像分割模型,由华盛顿大学的Joseph Redmon 和Ali Farhadi 开发。 YOLO 于2015 年推出,因其高速和高精度而广受欢迎

Error: DWT did not return enough components. Traceback (most recent call last): File "E:\bug\test.py", line 3, in <module> model = YOLO(r"E:\bug\ultralytics\cfg\models\11\yolo11-WTConv.yaml") File "E:\bug\ultralytics\models\yolo\model.py", line 23, in __init__ super().__init__(model=model, task=task, verbose=verbose) File "E:\bug\ultralytics\engine\model.py", line 143, in __init__ self._new(model, task=task, verbose=verbose) File "E:\bug\ultralytics\engine\model.py", line 251, in _new self.model = (model or self._smart_load("model"))(cfg_dict, verbose=verbose and RANK == -1) # build model File "E:\bug\ultralytics\nn\tasks.py", line 337, in __init__ m.stride = torch.tensor([s / x.shape[-2] for x in _forward(torch.zeros(1, ch, s, s))]) # forward File "E:\bug\ultralytics\nn\tasks.py", line 335, in _forward return self.forward(x)[0] if isinstance(m, (Segment, Pose, OBB)) else self.forward(x) File "E:\bug\ultralytics\nn\tasks.py", line 113, in forward return self.predict(x, *args, **kwargs) File "E:\bug\ultralytics\nn\tasks.py", line 131, in predict return self._predict_once(x, profile, visualize, embed) File "E:\bug\ultralytics\nn\tasks.py", line 152, in _predict_once x = m(x) # run File "D:\Program\anaconda\envs\torch\lib\site-packages\torch\nn\modules\module.py", line 1751, in _wrapped_call_impl return self._call_impl(*args, **kwargs) File "D:\Program\anaconda\envs\torch\lib\site-packages\torch\nn\modules\module.py", line 1762, in _call_impl return forward_call(*args, **kwargs) File "E:\bug\ultralytics\nn\modules\conv.py", line 96, in forward y_LL = self.conv(Y_LL) File "D:\Program\anaconda\envs\torch\lib\site-packages\torch\nn\modules\module.py", line 1751, in _wrapped_call_impl return self._call_impl(*args, **kwargs) File "D:\Program\anaconda\envs\torch\lib\site-packages\torch\nn\modules\module.py", line 1762, in _call_impl return forward_call(*args, **kwargs) File "D:\Program\anaconda\envs\torch\lib\site-packages\torch\nn\modules\conv.py", line 554, in forward return self._conv_forward(input, self.weight, self.bias) File "D:\Program\anaconda\envs\torch\lib\site-packages\torch\nn\modules\conv.py", line 549, in _conv_forward return F.conv2d( RuntimeError: Input type (__int64) and bias type (float) should be the same
最新发布
07-30
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