seq_imagenet_r

Classes

class datasets.seq_imagenet_r.MyImagenetR(root, train=True, transform=None, target_transform=None, download=False)

Bases: Dataset

N_CLASSES = 200

Overrides the CIFAR100 dataset to change the getitem function.

class datasets.seq_imagenet_r.SequentialImagenetR(args)

Bases: ContinualDataset

NAME: str = 'seq-imagenet-r'

N_CLASSES: int = 200

N_CLASSES_PER_TASK: int = 20

N_TASKS: int = 10

SETTING: str = 'class-il'

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

TEST_TRANSFORM = Compose(     Resize(size=(224, 224), interpolation=bicubic, max_size=None, antialias=warn)     ToTensor()     Normalize(mean=(0.0, 0.0, 0.0), std=(1.0, 1.0, 1.0)) )

TRANSFORM = Compose(     RandomResizedCrop(size=(224, 224), scale=(0.08, 1.0), ratio=(0.75, 1.3333), interpolation=bicubic, antialias=warn)     RandomHorizontalFlip(p=0.5)     ToTensor()     Normalize(mean=(0.0, 0.0, 0.0), std=(1.0, 1.0, 1.0)) )

static get_backbone(hookme=False)

static get_batch_size()

get_class_names()

get_data_loaders()

static get_denormalization_transform()

static get_epochs()

static get_loss()

static get_n_epochs_first_stage()

static get_normalization_transform()

static get_prompt_templates()

static get_transform()

static get_virtual_bn_num()

normalize = Normalize(mean=(0.0, 0.0, 0.0), std=(1.0, 1.0, 1.0))