SEQ SUN397#

Classes#

class datasets.seq_sun397.MySUN397(root, split, transform=None, target_transform=None)[source]#: Bases: Dataset

class datasets.seq_sun397.SequentialSUN397(args, transform_type='weak')[source]#

Bases: ContinualDataset

MEAN = (0.48145466, 0.4578275, 0.40821073)#

NAME: str = 'seq-sun397'#

N_CLASSES: int = 397#

N_CLASSES_PER_TASK: int = [50, 50, 50, 50, 50, 50, 50, 47]#

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=256, interpolation=bilinear, max_size=None, antialias=True) CenterCrop(size=(224, 224)) 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) RandomHorizontalFlip(p=0.5) 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]#

static get_loss()[source]#

static get_normalization_transform()[source]#

static get_prompt_templates()[source]#

static get_transform()[source]#

class datasets.seq_sun397.custom_import(module_name)[source]#

Bases: object

Context manager for importing packages with the same name while avoiding conflicts.

clean_cache()[source]#

load_package(package_name, basepath)[source]#

rename_cache(old_module_name, new_module_name)[source]#

Functions#

datasets.seq_sun397.download_SUN(force_download=False)[source]#

datasets.seq_sun397.download_SUN(force_download=False)[source]#