yolov5报错:RuntimeError: a view of a leaf Variable that requires grad is being used in an in-place

在执行下面代码时

python train.py --img 640 --batch 16 --epochs 5 --data ./data/coco128.yaml --cfg ./models/yolov5s.yaml --weights ''

我遇到了此报错

Traceback (most recent call last):
  File "train.py", line 456, in <module>
    train(hyp, opt, device, tb_writer)
  File "train.py", line 77, in train
    model = Model(opt.cfg, ch=3, nc=nc).to(device)  # create
  File "C:\Users\it possible\Documents\yolov5Project\yolov5-master\models\yolo.py", line 87, in __init__
    self._initialize_biases()  # only run once
  File "C:\Users\it possible\Documents\yolov5Project\yolov5-master\models\yolo.py", line 145, in _initialize_biases
    b[:, 4] += math.log(8 / (640 / s) ** 2)  # obj (8 objects per 640 image)
RuntimeError: a view of a leaf Variable that requires grad is being used in an in-place operation.

解决方法

找到在File "C:\Users\it possible\Documents\yolov5Project\yolov5-master\models\yolo.py"的line 145
将代码修改为：

    def _initialize_biases(self, cf=None):  # initialize biases into Detect(), cf is class frequency
        # cf = torch.bincount(torch.tensor(np.concatenate(dataset.labels, 0)[:, 0]).long(), minlength=nc) + 1.
        m = self.model[-1]  # Detect() module
        for mi, s in zip(m.m, m.stride):  # from
            b = mi.bias.view(m.na, -1)  # conv.bias(255) to (3,85)
            with torch.no_grad():
                b[:, 4] += math.log(8 / (640 / s) ** 2)  # obj (8 objects per 640 image)
                b[:, 5:] += math.log(0.6 / (m.nc - 0.99)) if cf is None else torch.log(cf / cf.sum())  # cls
            mi.bias = torch.nn.Parameter(b.view(-1), requires_grad=True)

再次测试，bug修复