yolov5训练出现错误解决方法

本人在训练时出现的错误如下

Traceback (most recent call last):
  File "train.py", line 670, in 
    main(opt)
  File "train.py", line 565, in main
    train(opt.hyp, opt, device, callbacks)
  File "train.py", line 352, in train
    pred = model(imgs)  # forward
  File "/home/lly/anaconda3/envs/pytorch/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
    return forward_call(*input, **kwargs)
  File "/home/lly/anaconda3/envs/pytorch/yolov5/models/yolo.py", line 135, in forward
    return self._forward_once(x, profile, visualize)  # single-scale inference, train
  File "/home/lly/anaconda3/envs/pytorch/yolov5/models/yolo.py", line 158, in _forward_once
    x = m(x)  # run
  File "/home/lly/anaconda3/envs/pytorch/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
    return forward_call(*input, **kwargs)
  File "/home/lly/anaconda3/envs/pytorch/yolov5/models/common.py", line 128, in forward
    y1 = self.cv3(self.m(self.cv1(x)))
  File "/home/lly/anaconda3/envs/pytorch/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
    return forward_call(*input, **kwargs)
  File "/home/lly/anaconda3/envs/pytorch/lib/python3.8/site-packages/torch/nn/modules/container.py", line 141, in forward
    input = module(input)
  File "/home/lly/anaconda3/envs/pytorch/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
    return forward_call(*input, **kwargs)
  File "/home/lly/anaconda3/envs/pytorch/yolov5/models/common.py", line 111, in forward
    return x + self.cv2(self.cv1(x)) if self.add else self.cv2(self.cv1(x))
  File "/home/lly/anaconda3/envs/pytorch/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
    return forward_call(*input, **kwargs)
  File "/home/lly/anaconda3/envs/pytorch/yolov5/models/common.py", line 47, in forward
    return self.act(self.bn(self.conv(x)))
  File "/home/lly/anaconda3/envs/pytorch/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
    return forward_call(*input, **kwargs)
  File "/home/lly/anaconda3/envs/pytorch/lib/python3.8/site-packages/torch/nn/modules/conv.py", line 446, in forward
    return self._conv_forward(input, self.weight, self.bias)
  File "/home/lly/anaconda3/envs/pytorch/lib/python3.8/site-packages/torch/nn/modules/conv.py", line 442, in _conv_forward
    return F.conv2d(input, weight, bias, self.stride,
RuntimeError: Unable to find a valid cuDNN algorithm to run convolution
wandb: Waiting for W&B process to finish... (failed 1). Press Control-C to abort syncing.
wandb:
wandb: Synced major-glitter-8: https://wandb.ai/llyue/YOLOv5/runs/1nah9k13
wandb: Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
wandb: Find logs at: ./wandb/run-20220617_165328-1nah9k13/logs

最后我发现是训练时batch参数设置过大导致训练出错

修改之前使用的训练代码

python train.py --img 640 --batch 8 --epochs 30 --data coco128.yaml --weights yolov5s.pt

把batch参数改到8之后我发现我的训练可以正常进行了

这里最好修改的时候把batch参数修改成8的倍数，例如8,16,24

修改之后使用的代码

python train.py --img 640 --batch 8 --epochs 8 --data coco128.yaml --weights yolov5s.pt

关于batch参数的理解：

一般训练主要需要调整的参数是这两个：

workers

指数据装载时cpu所使用的线程数，默认为8。代码解释如下

parser.add_argument('--workers', type=int, default=8, help='max dataloader workers (per RANK in DDP mode)')

一般默使用8的话，会报错~~。原因是爆系统内存，除了物理内存外，需要调整系统的虚拟内存。训练时主要看已提交哪里的实际值是否会超过最大值，超过了不是强退程序就是报错。

所以需要根据实际情况分配系统虚拟内存(python执行程序所在的盘)的最大值

第二个参数

batch-size

就是一次往GPU哪里塞多少张图片了。决定了显存占用大小，默认是16

parser.add_argument('--batch-size', type=int, default=16, help='total batch size for all GPUs, -1 for autobatch')

训练时显存占用越大当然效果越好，但如果爆显存，也是会无法训练的。

对于workers，并不是越大越好，太大时gpu其实处理不过来，训练速度一样，但虚拟内存（磁盘空间）会成倍占用。

workers为4时的内存占用

workers为8时的内存占用

我的显卡是rtx3050，实际使用中上到4以上就差别不大了，gpu完全吃满了。但是如果设置得太小，gpu会跑不满。比如当workers=1时，显卡功耗只得72W，速度慢了一半；workers=4时，显卡功耗能上到120+w，完全榨干了显卡的算力。所以需要根据你实际的算力调整这个参数。

2. 对于batch-size，有点玄学。理论是能尽量跑满显存为佳，但实际测试下来，发现当为8的倍数时效率更高一点。就是8时的训练效率会比10的高一点，这里就不太清楚原理是什么了，实际操作下来是这样。

总结

以上参数的调整能最大化显卡的使用效率，其中的具体数值和电脑的实际配置还有模型大小、数据集大小有关，需要根据实际情况反复调整。当然，要实质提升训练速度，还是得有好显卡（钞能力）~~~~