def _get_cub200_dataset(root, train_transformation, test_transformation):
train_set = CUB200(root, train=True)
test_set = CUB200(root, train=False)
return train_test_transformation_datasets(train_set, test_set,
train_transformation,
test_transformation)
def _get_tiny_imagenet_dataset(train_transformation, test_transformation):
train_set = TinyImagenet(train=True)
test_set = TinyImagenet(train=False)
return train_test_transformation_datasets(train_set, test_set,
train_transformation,
test_transformation)
def _get_imagenet_dataset(root, train_transformation, test_transformation):
train_set = ImageNet(root, split="train")
test_set = ImageNet(root, split="val")
return train_test_transformation_datasets(train_set, test_set,
train_transformation,
test_transformation)
def _get_mini_imagenet_dataset(path, train_transformation, test_transformation):
""" Create from ImageNet. """
task_labels = None
train_set = MiniImageNetDataset(path, split='train')
test_set = MiniImageNetDataset(path, split='test')
tr_ret, test_ret = train_test_transformation_datasets(
train_set, test_set, train_transformation, test_transformation)
return tr_ret, test_ret, task_labels
def _get_mini_imagenet_dataset_preprocessed(path, train_transformation, test_transformation):
"""
Use preprocessed train/val/test split.
Download: https://github.com/yaoyao-liu/mini-imagenet-tools
"""
train_set, test_set, task_labels = get_split_mini_imagenet(path)
return train_test_transformation_datasets(
train_set, test_set, train_transformation, test_transformation), task_labels
def _get_omniglot_dataset(train_transformation, test_transform):
train = Omniglot(root=expanduser("~") + "/.avalanche/data/omniglot/",
train=True, download=True)
test = Omniglot(root=expanduser("~") + "/.avalanche/data/omniglot/",
train=False, download=True)
return train_test_transformation_datasets(
train_dataset=train,
test_dataset=test,
train_transformation=train_transformation,
test_transformation=test_transform)
def _get_fmnist_dataset(train_transformation, test_transformation):
train_set = FashionMNIST(expanduser("~") +
"/.avalanche/data/fashionmnist/",
train=True,
download=True)
test_set = FashionMNIST(expanduser("~") + "/.avalanche/data/fashionmnist/",
train=False,
download=True)
return train_test_transformation_datasets(train_set, test_set,
train_transformation,
test_transformation)
def _get_cifar10_dataset(train_transformation, test_transformation):
train_set = CIFAR10(expanduser("~") + "/.avalanche/data/cifar10/",
train=True,
download=True)
test_set = CIFAR10(expanduser("~") + "/.avalanche/data/cifar10/",
train=False,
download=True)
return train_test_transformation_datasets(train_set, test_set,
train_transformation,
test_transformation)