Home - News ( United States | United Kingdom | Italy | Germany ) - Football scores

Showing content from https://docs.pytorch.org/vision/stable/generated/torchvision.datasets.FashionMNIST.html below:

FashionMNIST — Torchvision 0.23 documentation

class torchvision.datasets.FashionMNIST(root: Union[str, Path], train: bool = True, transform: Optional[Callable] = None, target_transform: Optional[Callable] = None, download: bool = False)[source]¶

Fashion-MNIST Dataset.

Parameters:

• root (str or pathlib.Path) – Root directory of dataset where FashionMNIST/raw/train-images-idx3-ubyte and FashionMNIST/raw/t10k-images-idx3-ubyte exist.

• train (bool, optional) – If True, creates dataset from train-images-idx3-ubyte, otherwise from t10k-images-idx3-ubyte.

• 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.

• 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.

Special-members:

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

Parameters:

index (int) – Index

Returns:

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

Return type:

tuple

RetroSearch is an open source project built by @garambo | Open a GitHub Issue

Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo

HTML: 3.2 | Encoding: UTF-8 | Version: 0.7.4