from typing import Optional, List, Dict
from torchvision import datasets, transforms
from extorch.vision.dataset import CVClassificationDataset
[docs]class CIFAR10(CVClassificationDataset):
def __init__(self, data_dir: str,
train_transform: Optional[transforms.Compose] = None,
test_transform: Optional[transforms.Compose] = None,
cutout_length: Optional[int] = None,
cutout_n_holes: Optional[int] = 1) -> None:
super(CIFAR10, self).__init__(data_dir, train_transform, test_transform, cutout_length, cutout_n_holes)
self.datasets["train"] = datasets.CIFAR10(root = self.data_dir, train = True,
download = True, transform = self.transforms["train"])
self.datasets["test"] = datasets.CIFAR10(root = self.data_dir, train = False,
download = True, transform = self.transforms["test"])
@classmethod
def num_classes(cls) -> int:
return 10
@classmethod
def mean(cls) -> List[float]:
return [0.49139968, 0.48215827, 0.44653124]
@classmethod
def std(cls) -> List[float]:
return [0.24703233, 0.24348505, 0.26158768]
@property
def default_transform(self) -> Dict[str, transforms.Compose]:
default_transforms = {
"train": transforms.Compose([transforms.RandomCrop(32, padding = 4),
transforms.RandomHorizontalFlip(),
transforms.ToTensor(),
transforms.Normalize(self.mean(), self.std())]),
"test": transforms.Compose([transforms.ToTensor(),
transforms.Normalize(self.mean(), self.std())])
}
return default_transforms