📚 The doc issue

In the doc of QMNIST(), train parameter is located before **kwargs which are download, transform and target_transform parameter as shown below:

class torchvision.datasets.QMNIST(root: Union[str, Path], what: Optional[str] = None, compat: bool = True, train: bool = True, **kwargs: Any)

But train parameter is explained after download, transform and target_transform parameter as shown below:

Parameters:
...

• compat (bool,optional) – A boolean that says whether the target for each example is class number (for compatibility with the MNIST dataloader) or a torch vector containing the full qmnist information. Default=True.
• download (bool, optional) – If True, downloads the dataset from the internet and puts it in root directory. If dataset is already downloaded, it is not downloaded again.
• transform (callable, optional) – A function/transform that takes in a PIL image and returns a transformed version. E.g, transforms.RandomCrop
• target_transform (callable, optional) – A function/transform that takes in the target and transforms it.
• train (bool,optional,compatibility) – When argument ‘what’ is not specified, this boolean decides whether to load the training set or the testing set. Default: True.

Suggest a potential alternative/fix

So, train parameter should be explained before download, transform and target_transform parameter as shown below:

Parameters:
...

• compat (bool,optional) – A boolean that says whether the target for each example is class number (for compatibility with the MNIST dataloader) or a torch vector containing the full qmnist information. Default=True.
• train (bool,optional,compatibility) – When argument ‘what’ is not specified, this boolean decides whether to load the training set or the testing set. Default: True.
• download (bool, optional) – If True, downloads the dataset from the internet and puts it in root directory. If dataset is already downloaded, it is not downloaded again.
• transform (callable, optional) – A function/transform that takes in a PIL image and returns a transformed version. E.g, transforms.RandomCrop
• target_transform (callable, optional) – A function/transform that takes in the target and transforms it.