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Merge pull request #882 from AntonioCarta/pnn_fix
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Pnn fix
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@AntonioCarta
AntonioCarta authored Jan 25, 2022
2 parents efa5223 + 7035521 commit d13b1ea
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Showing 183 changed files with 15,350 additions and 10,453 deletions.
2 changes: 2 additions & 0 deletions avalanche/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -12,6 +12,7 @@

def _avdataset_radd(self, other, *args, **kwargs):
from avalanche.benchmarks.utils import AvalancheDataset

global _dataset_add
if isinstance(other, AvalancheDataset):
return NotImplemented
Expand All @@ -21,6 +22,7 @@ def _avdataset_radd(self, other, *args, **kwargs):

def _avalanche_monkey_patches():
from torch.utils.data.dataset import Dataset

global _dataset_add
_dataset_add = Dataset.__add__
Dataset.__add__ = _avdataset_radd
Expand Down
70 changes: 39 additions & 31 deletions avalanche/benchmarks/classic/ccifar10.py
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Original file line number Diff line number Diff line change
Expand Up @@ -14,36 +14,44 @@
from torchvision import transforms

from avalanche.benchmarks import nc_benchmark, NCScenario
from avalanche.benchmarks.classic.classic_benchmarks_utils import \
check_vision_benchmark
from avalanche.benchmarks.classic.classic_benchmarks_utils import (
check_vision_benchmark,
)
from avalanche.benchmarks.datasets import default_dataset_location

_default_cifar10_train_transform = transforms.Compose([
transforms.RandomCrop(32, padding=4),
transforms.RandomHorizontalFlip(),
transforms.ToTensor(),
transforms.Normalize((0.4914, 0.4822, 0.4465),
(0.2023, 0.1994, 0.2010))
])

_default_cifar10_eval_transform = transforms.Compose([
transforms.ToTensor(),
transforms.Normalize((0.4914, 0.4822, 0.4465),
(0.2023, 0.1994, 0.2010))
])
_default_cifar10_train_transform = transforms.Compose(
[
transforms.RandomCrop(32, padding=4),
transforms.RandomHorizontalFlip(),
transforms.ToTensor(),
transforms.Normalize(
(0.4914, 0.4822, 0.4465), (0.2023, 0.1994, 0.2010)
),
]
)

_default_cifar10_eval_transform = transforms.Compose(
[
transforms.ToTensor(),
transforms.Normalize(
(0.4914, 0.4822, 0.4465), (0.2023, 0.1994, 0.2010)
),
]
)


def SplitCIFAR10(
n_experiences: int,
*,
first_exp_with_half_classes: bool = False,
return_task_id=False,
seed: Optional[int] = None,
fixed_class_order: Optional[Sequence[int]] = None,
shuffle: bool = True,
train_transform: Optional[Any] = _default_cifar10_train_transform,
eval_transform: Optional[Any] = _default_cifar10_eval_transform,
dataset_root: Union[str, Path] = None) -> NCScenario:
n_experiences: int,
*,
first_exp_with_half_classes: bool = False,
return_task_id=False,
seed: Optional[int] = None,
fixed_class_order: Optional[Sequence[int]] = None,
shuffle: bool = True,
train_transform: Optional[Any] = _default_cifar10_train_transform,
eval_transform: Optional[Any] = _default_cifar10_eval_transform,
dataset_root: Union[str, Path] = None
) -> NCScenario:
"""
Creates a CL benchmark using the CIFAR10 dataset.
Expand Down Expand Up @@ -120,7 +128,8 @@ def SplitCIFAR10(
per_exp_classes={0: 5} if first_exp_with_half_classes else None,
class_ids_from_zero_in_each_exp=True,
train_transform=train_transform,
eval_transform=eval_transform)
eval_transform=eval_transform,
)
else:
return nc_benchmark(
train_dataset=cifar_train,
Expand All @@ -132,12 +141,13 @@ def SplitCIFAR10(
shuffle=shuffle,
per_exp_classes={0: 5} if first_exp_with_half_classes else None,
train_transform=train_transform,
eval_transform=eval_transform)
eval_transform=eval_transform,
)


def _get_cifar10_dataset(dataset_root):
if dataset_root is None:
dataset_root = default_dataset_location('cifar10')
dataset_root = default_dataset_location("cifar10")

train_set = CIFAR10(dataset_root, train=True, download=True)
test_set = CIFAR10(dataset_root, train=False, download=True)
Expand All @@ -152,6 +162,4 @@ def _get_cifar10_dataset(dataset_root):
check_vision_benchmark(benchmark_instance)
sys.exit(0)

__all__ = [
'SplitCIFAR10'
]
__all__ = ["SplitCIFAR10"]
105 changes: 58 additions & 47 deletions avalanche/benchmarks/classic/ccifar100.py
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Original file line number Diff line number Diff line change
Expand Up @@ -15,39 +15,48 @@
from torchvision.datasets import CIFAR100
from torchvision import transforms

from avalanche.benchmarks.classic.classic_benchmarks_utils import \
check_vision_benchmark
from avalanche.benchmarks.classic.classic_benchmarks_utils import (
check_vision_benchmark,
)
from avalanche.benchmarks.datasets import CIFAR10, default_dataset_location
from avalanche.benchmarks.utils.avalanche_dataset import \
concat_datasets_sequentially
from avalanche.benchmarks.utils.avalanche_dataset import (
concat_datasets_sequentially,
)
from avalanche.benchmarks import nc_benchmark, NCScenario

_default_cifar100_train_transform = transforms.Compose([
transforms.RandomCrop(32, padding=4),
transforms.RandomHorizontalFlip(),
transforms.ToTensor(),
transforms.Normalize((0.5071, 0.4865, 0.4409),
(0.2673, 0.2564, 0.2762))
])

_default_cifar100_eval_transform = transforms.Compose([
transforms.ToTensor(),
transforms.Normalize((0.5071, 0.4865, 0.4409),
(0.2673, 0.2564, 0.2762))
])
_default_cifar100_train_transform = transforms.Compose(
[
transforms.RandomCrop(32, padding=4),
transforms.RandomHorizontalFlip(),
transforms.ToTensor(),
transforms.Normalize(
(0.5071, 0.4865, 0.4409), (0.2673, 0.2564, 0.2762)
),
]
)

_default_cifar100_eval_transform = transforms.Compose(
[
transforms.ToTensor(),
transforms.Normalize(
(0.5071, 0.4865, 0.4409), (0.2673, 0.2564, 0.2762)
),
]
)


def SplitCIFAR100(
n_experiences: int,
*,
first_exp_with_half_classes: bool = False,
return_task_id=False,
seed: Optional[int] = None,
fixed_class_order: Optional[Sequence[int]] = None,
shuffle: bool = True,
train_transform: Optional[Any] = _default_cifar100_train_transform,
eval_transform: Optional[Any] = _default_cifar100_eval_transform,
dataset_root: Union[str, Path] = None):
n_experiences: int,
*,
first_exp_with_half_classes: bool = False,
return_task_id=False,
seed: Optional[int] = None,
fixed_class_order: Optional[Sequence[int]] = None,
shuffle: bool = True,
train_transform: Optional[Any] = _default_cifar100_train_transform,
eval_transform: Optional[Any] = _default_cifar100_eval_transform,
dataset_root: Union[str, Path] = None
):
"""
Creates a CL benchmark using the CIFAR100 dataset.
Expand Down Expand Up @@ -124,7 +133,8 @@ def SplitCIFAR100(
per_exp_classes={0: 50} if first_exp_with_half_classes else None,
class_ids_from_zero_in_each_exp=True,
train_transform=train_transform,
eval_transform=eval_transform)
eval_transform=eval_transform,
)
else:
return nc_benchmark(
train_dataset=cifar_train,
Expand All @@ -136,18 +146,20 @@ def SplitCIFAR100(
shuffle=shuffle,
per_exp_classes={0: 50} if first_exp_with_half_classes else None,
train_transform=train_transform,
eval_transform=eval_transform)
eval_transform=eval_transform,
)


def SplitCIFAR110(
n_experiences: int,
*,
seed: Optional[int] = None,
fixed_class_order: Optional[Sequence[int]] = None,
train_transform: Optional[Any] = _default_cifar100_train_transform,
eval_transform: Optional[Any] = _default_cifar100_eval_transform,
dataset_root_cifar10: Union[str, Path] = None,
dataset_root_cifar100: Union[str, Path] = None) -> NCScenario:
n_experiences: int,
*,
seed: Optional[int] = None,
fixed_class_order: Optional[Sequence[int]] = None,
train_transform: Optional[Any] = _default_cifar100_train_transform,
eval_transform: Optional[Any] = _default_cifar100_eval_transform,
dataset_root_cifar10: Union[str, Path] = None,
dataset_root_cifar100: Union[str, Path] = None
) -> NCScenario:
"""
Creates a CL benchmark using both the CIFAR100 and CIFAR10 datasets.
Expand Down Expand Up @@ -229,20 +241,22 @@ def SplitCIFAR110(
class_order.extend(cifar_100_class_order)

return nc_benchmark(
cifar_10_100_train, cifar_10_100_test,
cifar_10_100_train,
cifar_10_100_test,
n_experiences=n_experiences,
task_labels=False,
shuffle=False,
seed=None,
fixed_class_order=class_order,
per_exp_classes={0: 10},
train_transform=train_transform,
eval_transform=eval_transform)
eval_transform=eval_transform,
)


def _get_cifar10_dataset(dataset_root):
if dataset_root is None:
dataset_root = default_dataset_location('cifar10')
dataset_root = default_dataset_location("cifar10")

train_set = CIFAR10(dataset_root, train=True, download=True)
test_set = CIFAR10(dataset_root, train=False, download=True)
Expand All @@ -252,7 +266,7 @@ def _get_cifar10_dataset(dataset_root):

def _get_cifar100_dataset(dataset_root):
if dataset_root is None:
dataset_root = default_dataset_location('cifar100')
dataset_root = default_dataset_location("cifar100")

train_set = CIFAR100(dataset_root, train=True, download=True)
test_set = CIFAR100(dataset_root, train=False, download=True)
Expand All @@ -263,18 +277,15 @@ def _get_cifar100_dataset(dataset_root):
if __name__ == "__main__":
import sys

print('Split 100')
print("Split 100")
benchmark_instance = SplitCIFAR100(5)
check_vision_benchmark(benchmark_instance)

print('Split 110')
print("Split 110")
benchmark_instance = SplitCIFAR110(5)
check_vision_benchmark(benchmark_instance)

sys.exit(0)


__all__ = [
'SplitCIFAR100',
'SplitCIFAR110'
]
__all__ = ["SplitCIFAR100", "SplitCIFAR110"]
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