# archai.datasets package

## Subpackages

- archai.datasets.providers package
  - Submodules
  - archai.datasets.providers.cifar100_provider module
  - archai.datasets.providers.cifar10_provider module
  - archai.datasets.providers.fashion_mnist_provider module
  - archai.datasets.providers.flower102_provider module
  - archai.datasets.providers.food101_provider module
  - archai.datasets.providers.imagenet_folder module
  - archai.datasets.providers.imagenet_provider module
  - archai.datasets.providers.mit67_provider module
  - archai.datasets.providers.mnist_provider module
  - archai.datasets.providers.sport8_provider module
  - archai.datasets.providers.svhn_provider module
  - Module contents
- archai.datasets.transforms package
  - Submodules
  - archai.datasets.transforms.brightness module
  - archai.datasets.transforms.cutout_custom module
  - archai.datasets.transforms.lighting module
  - Module contents

## Submodules

## archai.datasets.aug_policies module

`archai.datasets.aug_policies.``fa_reduced_cifar10`()

`archai.datasets.aug_policies.``fa_reduced_svhn`()

`archai.datasets.aug_policies.``fa_resnet50_rimagenet`()

## archai.datasets.augmentation module

class `archai.datasets.augmentation.``Augmentation`(policies)

  Bases: `object`

`archai.datasets.augmentation.``AutoContrast`(img, _)

`archai.datasets.augmentation.``Brightness`(img, v)

`archai.datasets.augmentation.``Color`(img, v)

`archai.datasets.augmentation.``Contrast`(img, v)

`archai.datasets.augmentation.``Cutout`(img, v)

`archai.datasets.augmentation.``CutoutAbs`(img, v)

`archai.datasets.augmentation.``Equalize`(img, _)

`archai.datasets.augmentation.``Flip`(img, _)

`archai.datasets.augmentation.``Invert`(img, _)

`archai.datasets.augmentation.``Posterize`(img, v)

`archai.datasets.augmentation.``Posterize2`(img, v)

`archai.datasets.augmentation.``Rotate`(img, v)

`archai.datasets.augmentation.``SamplePairing`(imgs)

`archai.datasets.augmentation.``Sharpness`(img, v)

`archai.datasets.augmentation.``ShearX`(img, v)

`archai.datasets.augmentation.``ShearY`(img, v)

`archai.datasets.augmentation.``Solarize`(img, v)

`archai.datasets.augmentation.``TranslateX`(img, v)

`archai.datasets.augmentation.``TranslateXAbs`(img, v)

`archai.datasets.augmentation.``TranslateY`(img, v)

`archai.datasets.augmentation.``TranslateYAbs`(img, v)

`archai.datasets.augmentation.``add_named_augs`(transform_train, aug: Union[List, str], cutout: int)

`archai.datasets.augmentation.``apply_augment`(img, name, level)

`archai.datasets.augmentation.``arsaug_policy`()

`archai.datasets.augmentation.``augment_list`(for_autoaug=True)

`archai.datasets.augmentation.``autoaug2arsaug`(f)

`archai.datasets.augmentation.``autoaug_paper_cifar10`()

`archai.datasets.augmentation.``autoaug_policy`()

`archai.datasets.augmentation.``float_parameter`(level, maxval)

`archai.datasets.augmentation.``get_augment`(name)

`archai.datasets.augmentation.``int_parameter`(level, maxval)

`archai.datasets.augmentation.``no_duplicates`(f)

`archai.datasets.augmentation.``policy_decoder`(augment, num_policy, num_op)

`archai.datasets.augmentation.``remove_deplicates`(policies)

## archai.datasets.data module

class `archai.datasets.data.``SubsetSampler`(indices)

  Bases: `torch.utils.data.sampler.Sampler`

  Samples elements from a given list of indices, without replacement.

  Arguments:

    indices (sequence): a sequence of indices

`archai.datasets.data.``create_dataset_provider`(conf_dataset: archai.common.config.Config) → archai.datasets.dataset_provider.DatasetProvider

`archai.datasets.data.``get_data`(conf_loader: archai.common.config.Config) → Tuple[Optional[torch.utils.data.dataloader.DataLoader], Optional[torch.utils.data.dataloader.DataLoader], Optional[torch.utils.data.dataloader.DataLoader]]

`archai.datasets.data.``get_dataloaders`(ds_provider: archai.datasets.dataset_provider.DatasetProvider, load_train: bool, train_batch_size: int, load_test: bool, test_batch_size: int, aug, cutout: int, val_ratio: float, apex: archai.common.apex_utils.ApexUtils, val_fold=0, train_workers: Optional[int] = None, test_workers: Optional[int] = None, target_lb=- 1, max_batches: int = - 1) → Tuple[Optional[torch.utils.data.dataloader.DataLoader], Optional[torch.utils.data.dataloader.DataLoader], Optional[torch.utils.data.dataloader.DataLoader]]

## archai.datasets.dataset_provider module

class `archai.datasets.dataset_provider.``DatasetProvider`(conf_dataset: archai.common.config.Config)

  Bases: `overrides.enforce.EnforceOverrides`

  abstract `get_datasets`(load_train: bool, load_test: bool, transform_train, transform_test) → Tuple[Optional[torch.utils.data.dataset.Dataset], Optional[torch.utils.data.dataset.Dataset]]
  abstract `get_transforms`() → tuple

`archai.datasets.dataset_provider.``get_provider_type`(name: str) → overrides.enforce.EnforceOverridesMeta

`archai.datasets.dataset_provider.``register_dataset_provider`(name: str, class_type: overrides.enforce.EnforceOverridesMeta) → None

## archai.datasets.distributed_stratified_sampler module

class `archai.datasets.distributed_stratified_sampler.``DistributedStratifiedSampler`(dataset: torch.utils.data.dataset.Dataset, world_size: Optional[int] = None, rank: Optional[int] = None, shuffle=True, val_ratio: Optional[float] = 0.0, is_val=False, max_items: Optional[int] = None)

  Bases: `torch.utils.data.sampler.Sampler`

  `set_epoch`(epoch)

## archai.datasets.limit_dataset module

class `archai.datasets.limit_dataset.``LimitDataset`(dataset, n)

  Bases: `torch.utils.data.dataset.Dataset`

## Module contents

Contents:

- archai
  - archai package

- Github