QMNIST — Torchvision 0.22 documentation (original) (raw)

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

QMNIST Dataset.

Parameters:

• root (str or pathlib.Path) – Root directory of dataset whose rawsubdir contains binary files of the datasets.
• what (string , optional) – Can be ‘train’, ‘test’, ‘test10k’, ‘test50k’, or ‘nist’ for respectively the mnist compatible training set, the 60k qmnist testing set, the 10k qmnist examples that match the mnist testing set, the 50k remaining qmnist testing examples, or all the nist digits. The default is to select ‘train’ or ‘test’ according to the compatibility argument ‘train’.
• 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.

Special-members:

__getitem__(index: int) → Tuple[Any, Any][source]¶

Parameters:

index (int) – Index

Returns:

(image, target) where target is index of the target class.

Return type:

tuple