尝试计算数据集的平均值和标准差，以便随后对其进行归一化。
当前代码：

train_dataset = datasets.FashionMNIST('data', train=True, download = True, transform=[transforms.ToTensor()])
test_dataset = datasets.FashionMNIST('data', train=False, download = True, transform=[transforms.ToTensor()])

def calc_torch_mean_std(tens):   
    mean = torch.mean(tens, dim=1)
    std = torch.sqrt(torch.mean((tens - mean[:, None]) ** 2, dim=1))
    return(std, mean)

train_mean, train_std = calc_torch_mean_std(train_dataset)

test_mean, test_std = calc_torch_mean_std(test_dataset)

然而，我得到的错误：

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
/var/folders/16/crymx03s6pzfspm_3qfrlkx00000gn/T/ipykernel_72423/605045038.py in <module>
      8     return(std, mean)
      9 
---> 10 train_mean, train_std = calc_torch_mean_std(train_dataset)
     11 
     12 test_mean, test_std = calc_torch_mean_std(test_dataset)

/var/folders/16/crymx03s6pzfspm_3qfrlkx00000gn/T/ipykernel_72423/605045038.py in calc_torch_mean_std(tens)
      4 
      5 def calc_torch_mean_std(tens):
----> 6     mean = torch.mean(tens, dim=1)
      7     std = torch.sqrt(torch.mean((tens - mean[:, None]) ** 2, dim=1))
      8     return(std, mean)

TypeError: mean() received an invalid combination of arguments - got (FashionMNIST, dim=int), but expected one of:
 * (Tensor input, *, torch.dtype dtype)
 * (Tensor input, tuple of ints dim, bool keepdim, *, torch.dtype dtype, Tensor out)
 * (Tensor input, tuple of names dim, bool keepdim, *, torch.dtype dtype, Tensor out)

它应该得到一个Tensor，因为我用transforms.ToTensor（）来转换数据。
已检查转换的导入，一切正常。已检查数据集的参数。FashionMNIST（）和转换使用正确（在有和没有[ ]的情况下都应工作）。
预期无错误，并获得两个数据集的平均值和标准差。