SEQ 8VISION#

Classes#

class datasets.seq_8vision.Sequential8Vision(args)[source]#

Bases: ContinualDataset

Sequential 8 Vision dataset. Each task is a different vision dataset, and the model is trained on them sequentially.

The datasets are: Cars196, DTD, EuroSat RGB, GTSRB, MNIST-224, Resisc45, SUN397 and SVHN.

DATASETS = [<class 'datasets.seq_cars196.SequentialCars196'>, <class 'datasets.seq_dtd.SequentialDTD'>, <class 'datasets.seq_eurosat_rgb.SequentialEuroSatRgb'>, <class 'datasets.seq_gtrsrb.SequentialGTSRB'>, <class 'datasets.seq_mnist_224.SequentialMNIST224'>, <class 'datasets.seq_resisc45.SequentialResisc45'>, <class 'datasets.seq_sun397.SequentialSUN397'>, <class 'datasets.seq_svhn.SequentialSVHN'>]#

DATASET_NAMES = ['seq-cars196', 'seq-dtd', 'seq-eurosat-rgb', 'seq-gtsrb', 'seq-mnist-224', 'seq-resisc45', 'seq-sun397', 'seq-svhn']#

MEAN = (0.48145466, 0.4578275, 0.40821073)#

NAME: str = 'seq-8vision'#

N_CLASSES: int = 758#

N_CLASSES_PER_TASK: int = [196, 47, 10, 43, 10, 45, 397, 10]#

N_TASKS: int = 8#

SETTING: str = 'class-il'#

SIZE: Tuple[int] = (224, 224)#

STD = (0.26862954, 0.26130258, 0.27577711)#

TEST_TRANSFORM = Compose( Resize(size=224, interpolation=bicubic, max_size=None, antialias=True) CenterCrop(size=(224, 224)) <function _convert_to_rgb> ToTensor() Normalize(mean=(0.48145466, 0.4578275, 0.40821073), std=(0.26862954, 0.26130258, 0.27577711)) )#

TRANSFORM = Compose( RandomResizedCrop(size=(224, 224), scale=(0.8, 1.0), ratio=(0.75, 1.3333), interpolation=bilinear, antialias=True) ColorJitter(brightness=(0.8, 1.2), contrast=(0.8, 1.2), saturation=(0.8, 1.2), hue=(-0.1, 0.1)) ToTensor() Normalize(mean=(0.48145466, 0.4578275, 0.40821073), std=(0.26862954, 0.26130258, 0.27577711)) )#

get_backbone()[source]#

get_batch_size()[source]#

get_class_names()[source]#

get_data_loaders()[source]#

Return type:: Tuple[DataLoader, DataLoader]

static get_denormalization_transform()[source]#

get_epochs()[source]#

get_iters()[source]#

static get_loss()[source]#

static get_normalization_transform()[source]#

static get_prompt_templates()[source]#

get_task_epochs(t)[source]#

static get_transform()[source]#