class torchvision.datasets.RenderedSST2(root: str, split: str = 'train', transform: Optional[Callable] = None, target_transform: Optional[Callable] = None, download: bool = False)[source]

The Rendered SST2 Dataset.

Rendered SST2 is an image classification dataset used to evaluate the models capability on optical character recognition. This dataset was generated by rendering sentences in the Standford Sentiment Treebank v2 dataset.

This dataset contains two classes (positive and negative) and is divided in three splits: a train split containing 6920 images (3610 positive and 3310 negative), a validation split containing 872 images (444 positive and 428 negative), and a test split containing 1821 images (909 positive and 912 negative).

  • root (string) – Root directory of the dataset.

  • split (string, optional) – The dataset split, supports "train" (default), “val” and "test".

  • transform (callable, optional) – A function/transform that takes in an 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. Default is False.


__getitem__(idx) Tuple[Any, Any][source]

index (int) – Index


Sample and meta data, optionally transformed by the respective transforms.

Return type:



Access comprehensive developer documentation for PyTorch

View Docs


Get in-depth tutorials for beginners and advanced developers

View Tutorials


Find development resources and get your questions answered

View Resources