yolov5模型修改报错

Traceback (most recent call last):
  File "G:/yolov5/yolov5-6.1/train.py", line 651, in
    main(opt)
  File "G:/yolov5/yolov5-6.1/train.py", line 544, in main
    train(opt.hyp, opt, device, callbacks)
  File "G:/yolov5/yolov5-6.1/train.py", line 129, in train
    model = Model(cfg or ckpt['model'].yaml, ch=3, nc=nc, anchors=hyp.get('anchors')).to(device)  # create
  File "G:\yolov5\yolov5-6.1\models\yolo.py", line 112, in __init__
    m.stride = torch.tensor([s / x.shape[-2] for x in self.forward(torch.zeros(1, ch, s, s))])  # forward
  File "G:\yolov5\yolov5-6.1\models\yolo.py", line 126, in forward
    return self._forward_once(x, profile, visualize)  # single-scale inference, train
  File "G:\yolov5\yolov5-6.1\models\yolo.py", line 149, in _forward_once
    x = m(x)  # run
  File "D:\programfiles\miniconda\envs\py38torch_gpu\lib\site-packages\torch\nn\modules\module.py", line 1051, in _call_impl
    return forward_call(*input, **kwargs)
  File "G:\yolov5\yolov5-6.1\models\common.py", line 139, in forward
    return self.cv3(torch.cat((self.m(self.cv1(x)), self.cv2(x)), dim=1))
  File "D:\programfiles\miniconda\envs\py38torch_gpu\lib\site-packages\torch\nn\modules\module.py", line 1051, in _call_impl
    return forward_call(*input, **kwargs)
  File "G:\yolov5\yolov5-6.1\models\common.py", line 47, in forward
    return self.act(self.bn(self.conv(x)))
  File "D:\programfiles\miniconda\envs\py38torch_gpu\lib\site-packages\torch\nn\modules\module.py", line 1051, in _call_impl
    return forward_call(*input, **kwargs)
  File "D:\programfiles\miniconda\envs\py38torch_gpu\lib\site-packages\torch\nn\modules\batchnorm.py", line 167, in forward
    return F.batch_norm(
  File "D:\programfiles\miniconda\envs\py38torch_gpu\lib\site-packages\torch\nn\functional.py", line 2279, in batch_norm
    _verify_batch_size(input.size())
  File "D:\programfiles\miniconda\envs\py38torch_gpu\lib\site-packages\torch\nn\functional.py", line 2247, in _verify_batch_size
    raise ValueError("Expected more than 1 value per channel when training, got input size {}".format(size))
ValueError: Expected more than 1 value per channel when training, got input size torch.Size([1, 256, 1, 1])

Process finished with exit code 1

Traceback (most recent call last):
  File "G:/yolov5/Yolov5_Magic-main/train.py", line 677, in
    main(opt)
  File "G:/yolov5/Yolov5_Magic-main/train.py", line 572, in main
    train(opt.hyp, opt, device, callbacks)
  File "G:/yolov5/Yolov5_Magic-main/train.py", line 124, in train
    model = Model(cfg or ckpt['model'].yaml, ch=3, nc=nc, anchors=hyp.get('anchors')).to(device)  # create
  File "G:\yolov5\Yolov5_Magic-main\models\yolo.py", line 173, in __init__
    m.stride = torch.tensor([s / x.shape[-2] for x in self.forward(torch.zeros(1, ch, s, s))])  # forward
  File "G:\yolov5\Yolov5_Magic-main\models\yolo.py", line 190, in forward
    return self._forward_once(x, profile, visualize)  # single-scale inference, train
  File "G:\yolov5\Yolov5_Magic-main\models\yolo.py", line 233, in _forward_once
    x = m(x)  # run
  File "D:\programfiles\miniconda\envs\py38torch_gpu\lib\site-packages\torch\nn\modules\module.py", line 1051, in _call_impl
    return forward_call(*input, **kwargs)
  File "G:\yolov5\Yolov5_Magic-main\models\common.py", line 330, in forward
    return torch.cat(x, self.d)
RuntimeError: torch.cat(): Sizes of tensors must match except in dimension 1. Got 16 and 32 in dimension 2 (The offending index is 1)

Process finished with exit code 1

我在修改v5模型的时候，在添加一些模块的时候，一运行就出现了很多错误，刚开始去检查源码里面有没有问题，找了半天，也没找到，后来在模型文件周到了很多问题，比如一些添加了一些层，导致了一些层没有连接对，同理，当添加一些层后，检查一些层有没有连接对，就可以解决一些报错！！！下图是连接规则，同理，当你添加一些层后，需要去调整相应的变化部分。