Merge pull request #47 from pralab/46-rename-library-to-secml-torch

Massive refactoring

examples/mnist_example.py

@@ -1,5 +1,5 @@
 import os
-from secml2.trackers.trackers import (
+from secmlt.trackers.trackers import (
     LossTracker,
     PredictionTracker,
     PerturbationNormTracker,
@@ -8,12 +8,12 @@
 import torchvision.datasets
 from torch.utils.data import DataLoader, Subset
 from robustbench.utils import download_gdrive
-from secml2.adv.backends import Backends
-from secml2.adv.evasion.pgd import PGD
-from secml2.adv.evasion.perturbation_models import PerturbationModels
+from secmlt.adv.backends import Backends
+from secmlt.adv.evasion.pgd import PGD
+from secmlt.adv.evasion.perturbation_models import PerturbationModels
 
-from secml2.metrics.classification import Accuracy
-from secml2.models.pytorch.base_pytorch_nn import BasePytorchClassifier
+from secmlt.metrics.classification import Accuracy
+from secmlt.models.pytorch.base_pytorch_nn import BasePytorchClassifier
 
 
 class MNISTNet(torch.nn.Module):

examples/mnist_example_tensorboard.py

@@ -1,23 +1,24 @@
 import os
-from secml2.trackers.image_trackers import GradientsTracker, SampleTracker
-from secml2.trackers.trackers import (
+from secmlt.trackers import (
     GradientNormTracker,
     LossTracker,
     PredictionTracker,
     PerturbationNormTracker,
     TensorboardTracker,
+    GradientsTracker,
+    SampleTracker,
     ScoresTracker,
 )
 import torch
 import torchvision.datasets
 from torch.utils.data import DataLoader, Subset
 from robustbench.utils import download_gdrive
-from secml2.adv.backends import Backends
-from secml2.adv.evasion.pgd import PGD
-from secml2.adv.evasion.perturbation_models import PerturbationModels
+from secmlt.adv.backends import Backends
+from secmlt.adv.evasion.pgd import PGD
+from secmlt.adv.evasion.perturbation_models import PerturbationModels
 
-from secml2.metrics.classification import Accuracy
-from secml2.models.pytorch.base_pytorch_nn import BasePytorchClassifier
+from secmlt.metrics.classification import Accuracy
+from secmlt.models.pytorch.base_pytorch_nn import BasePytorchClassifier
 
 
 class MNISTNet(torch.nn.Module):

examples/run_evasion_attack.py

@@ -1,11 +1,11 @@
 import torchvision.datasets
 from torch.utils.data import DataLoader, Subset
-from secml2.adv.backends import Backends
-from secml2.adv.evasion.pgd import PGD
-from secml2.adv.evasion.perturbation_models import PerturbationModels
+from secmlt.adv.backends import Backends
+from secmlt.adv.evasion.pgd import PGD
+from secmlt.adv.evasion.perturbation_models import PerturbationModels
 
-from secml2.metrics.classification import Accuracy
-from secml2.models.pytorch.base_pytorch_nn import BasePytorchClassifier
+from secmlt.metrics.classification import Accuracy
+from secmlt.models.pytorch.base_pytorch_nn import BasePytorchClassifier
 
 from robustbench.utils import load_model
 

examples/train_model.py

@@ -3,9 +3,9 @@
 from torch.optim import Adam
 from torch.utils.data import DataLoader
 
-from secml2.metrics.classification import Accuracy
-from secml2.models.pytorch.base_pytorch_nn import BasePytorchClassifier
-from secml2.models.pytorch.base_pytorch_trainer import BasePyTorchTrainer
+from secmlt.metrics.classification import Accuracy
+from secmlt.models.pytorch.base_pytorch_nn import BasePytorchClassifier
+from secmlt.models.pytorch.base_pytorch_trainer import BasePyTorchTrainer
 
 
 class MNISTNet(torch.nn.Module):

setup.py

@@ -24,9 +24,9 @@
 """
 
 setup(
-    name="secml2",
+    name="secml-torch",
     version="1.0.0",
-    description="SecML 2.0 Library",
+    description="SecML-Torch Library",
     classifiers=[_f for _f in CLASSIFIERS.split("\n") if _f],
     long_description=long_description,
     long_description_context_type="text/markdown",
@@ -40,8 +40,6 @@
     author="Maura Pintor, Luca Demetrio",
     author_email="[email protected], [email protected]",
     install_requires=["torch>=1.4,!=1.5.*", "torchvision>=0.5,!=0.6.*"],
-    extras_require={
-        "foolbox": ["foolbox>=3.3.0"],
-    },
+    extras_require={"foolbox": ["foolbox>=3.3.0"], "tensorboard": ["tensorboard"]},
     python_requires=">=3.7",
 )

src/secml2/adv/evasion/base_evasion_attack.py → src/secmlt/adv/evasion/base_evasion_attack.py

@@ -1,15 +1,15 @@
 from abc import abstractmethod
 from typing import Callable, List, Type, Union
-from secml2.adv.evasion.perturbation_models import PerturbationModels
+from secmlt.adv.evasion.perturbation_models import PerturbationModels
 
 import torch
 from torch.utils.data import DataLoader, TensorDataset
 
-from secml2.adv.backends import Backends
-from secml2.models.base_model import BaseModel
+from secmlt.adv.backends import Backends
+from secmlt.models.base_model import BaseModel
 
 # lazy evaluation to avoid circular imports
-TRACKER_TYPE = "secml2.trackers.tracker.Tracker"
+TRACKER_TYPE = "secmlt.trackers.tracker.Tracker"
 
 
 class BaseEvasionAttackCreator:

src/secml2/adv/evasion/composite_attack.py → src/secmlt/adv/evasion/composite_attack.py

@@ -1,18 +1,18 @@
 from typing import Union, List, Type
-from secml2.adv.evasion.perturbation_models import PerturbationModels
+from secmlt.adv.evasion.perturbation_models import PerturbationModels
 
 import torch.nn
 from torch.nn import CrossEntropyLoss
 from torch.optim import Optimizer
 from functools import partial
-from secml2.adv.evasion.base_evasion_attack import BaseEvasionAttack
-from secml2.manipulations.manipulation import Manipulation
-from secml2.models.base_model import BaseModel
-from secml2.optimization.constraints import Constraint
-from secml2.optimization.gradient_processing import GradientProcessing
-from secml2.optimization.initializer import Initializer
-from secml2.optimization.optimizer_factory import OptimizerFactory
-from secml2.trackers.trackers import Tracker
+from secmlt.adv.evasion.base_evasion_attack import BaseEvasionAttack
+from secmlt.manipulations.manipulation import Manipulation
+from secmlt.models.base_model import BaseModel
+from secmlt.optimization.constraints import Constraint
+from secmlt.optimization.gradient_processing import GradientProcessing
+from secmlt.optimization.initializer import Initializer
+from secmlt.optimization.optimizer_factory import OptimizerFactory
+from secmlt.trackers.trackers import Tracker
 
 CE_LOSS = "ce_loss"
 LOGIT_LOSS = "logit_loss"

src/secml2/adv/evasion/foolbox_attacks/foolbox_base.py → src/secmlt/adv/evasion/foolbox_attacks/foolbox_base.py

@@ -1,10 +1,10 @@
 from typing import Optional, Type, Union
-from secml2.models.pytorch.base_pytorch_nn import BasePytorchClassifier
-from secml2.models.base_model import BaseModel
+from secmlt.models.pytorch.base_pytorch_nn import BasePytorchClassifier
+from secmlt.models.base_model import BaseModel
 from foolbox.attacks.base import Attack
 from foolbox.models.pytorch import PyTorchModel
 from foolbox.criteria import Misclassification, TargetedMisclassification
-from secml2.adv.evasion.base_evasion_attack import BaseEvasionAttack, TRACKER_TYPE
+from secmlt.adv.evasion.base_evasion_attack import BaseEvasionAttack, TRACKER_TYPE
 import torch
 
 

src/secml2/adv/evasion/foolbox_attacks/foolbox_pgd.py → src/secmlt/adv/evasion/foolbox_attacks/foolbox_pgd.py

@@ -1,6 +1,6 @@
 from typing import Optional
-from secml2.adv.evasion.foolbox_attacks.foolbox_base import BaseFoolboxEvasionAttack
-from secml2.adv.evasion.perturbation_models import PerturbationModels
+from secmlt.adv.evasion.foolbox_attacks.foolbox_base import BaseFoolboxEvasionAttack
+from secmlt.adv.evasion.perturbation_models import PerturbationModels
 
 from foolbox.attacks.projected_gradient_descent import (
     L1ProjectedGradientDescentAttack,

src/secml2/adv/evasion/pgd.py → src/secmlt/adv/evasion/pgd.py

@@ -6,24 +6,24 @@
     LinfProjectedGradientDescentAttack,
 )
 
-from secml2.adv.backends import Backends
-from secml2.adv.evasion import BaseFoolboxEvasionAttack
-from secml2.adv.evasion.base_evasion_attack import (
+from secmlt.adv.backends import Backends
+from secmlt.adv.evasion import BaseFoolboxEvasionAttack
+from secmlt.adv.evasion.base_evasion_attack import (
     BaseEvasionAttackCreator,
 )
-from secml2.adv.evasion.composite_attack import CompositeEvasionAttack, CE_LOSS
-from secml2.adv.evasion.perturbation_models import PerturbationModels
-from secml2.manipulations.manipulation import AdditiveManipulation
-from secml2.optimization.constraints import (
+from secmlt.adv.evasion.composite_attack import CompositeEvasionAttack, CE_LOSS
+from secmlt.adv.evasion.perturbation_models import PerturbationModels
+from secmlt.manipulations.manipulation import AdditiveManipulation
+from secmlt.optimization.constraints import (
     ClipConstraint,
     L1Constraint,
     L2Constraint,
     LInfConstraint,
 )
-from secml2.optimization.gradient_processing import LinearProjectionGradientProcessing
-from secml2.optimization.initializer import Initializer
-from secml2.optimization.optimizer_factory import OptimizerFactory
-from secml2.trackers.trackers import Tracker
+from secmlt.optimization.gradient_processing import LinearProjectionGradientProcessing
+from secmlt.optimization.initializer import Initializer
+from secmlt.optimization.optimizer_factory import OptimizerFactory
+from secmlt.trackers.trackers import Tracker
 
 
 class PGD(BaseEvasionAttackCreator):

src/secml2/manipulations/manipulation.py → src/secmlt/manipulations/manipulation.py

@@ -3,7 +3,7 @@
 
 import torch
 
-from secml2.optimization.constraints import Constraint
+from secmlt.optimization.constraints import Constraint
 
 
 class Manipulation(ABC):

src/secml2/metrics/classification.py → src/secmlt/metrics/classification.py

@@ -1,7 +1,7 @@
 import torch
 from torch.utils.data import DataLoader
 
-from secml2.models.base_model import BaseModel
+from secmlt.models.base_model import BaseModel
 
 
 def accuracy(y_pred: torch.Tensor, y_true: torch.Tensor) -> torch.Tensor:

src/secml2/models/base_model.py → src/secmlt/models/base_model.py

@@ -4,10 +4,10 @@
 import torch
 from torch.utils.data import DataLoader
 
-from secml2.models.data_processing.identity_data_processing import (
+from secmlt.models.data_processing.identity_data_processing import (
     IdentityDataProcessing,
 )
-from secml2.models.data_processing.data_processing import DataProcessing
+from secmlt.models.data_processing.data_processing import DataProcessing
 
 
 class BaseModel(ABC):

src/secml2/models/data_processing/identity_data_processing.py → src/secmlt/models/data_processing/identity_data_processing.py

@@ -1,6 +1,6 @@
 import torch
 
-from secml2.models.data_processing.data_processing import DataProcessing
+from secmlt.models.data_processing.data_processing import DataProcessing
 
 
 class IdentityDataProcessing(DataProcessing):

src/secml2/models/pytorch/base_pytorch_nn.py → src/secmlt/models/pytorch/base_pytorch_nn.py

@@ -1,9 +1,9 @@
 import torch
 from torch.utils.data import DataLoader
 
-from secml2.models.base_model import BaseModel
-from secml2.models.data_processing.data_processing import DataProcessing
-from secml2.models.pytorch.base_pytorch_trainer import BasePyTorchTrainer
+from secmlt.models.base_model import BaseModel
+from secmlt.models.data_processing.data_processing import DataProcessing
+from secmlt.models.pytorch.base_pytorch_trainer import BasePyTorchTrainer
 
 
 class BasePytorchClassifier(BaseModel):

src/secml2/models/pytorch/base_pytorch_trainer.py → src/secmlt/models/pytorch/base_pytorch_trainer.py

@@ -2,7 +2,7 @@
 from torch.optim.lr_scheduler import _LRScheduler  # noqa
 from torch.utils.data import DataLoader
 
-from secml2.models.base_trainer import BaseTrainer
+from secmlt.models.base_trainer import BaseTrainer
 
 
 class BasePyTorchTrainer(BaseTrainer):

src/secml2/optimization/gradient_processing.py → src/secmlt/optimization/gradient_processing.py

@@ -1,7 +1,7 @@
 import torch.linalg
 from torch.nn.functional import normalize
 
-from secml2.adv.evasion.perturbation_models import PerturbationModels
+from secmlt.adv.evasion.perturbation_models import PerturbationModels
 
 
 class GradientProcessing:

src/secml2/optimization/initializer.py → src/secmlt/optimization/initializer.py

@@ -1,6 +1,6 @@
 import torch
 
-from secml2.adv.evasion.perturbation_models import PerturbationModels
+from secmlt.adv.evasion.perturbation_models import PerturbationModels
 
 
 class Initializer:

src/secmlt/trackers/__init__.py

@@ -0,0 +1,9 @@
+try:
+    import tensorboard
+except ImportError:
+    pass  # tensorboard is an extra
+else:
+    from .tensorboard_tracker import TensorboardTracker
+
+from .trackers import *
+from .image_trackers import *

src/secml2/trackers/image_trackers.py → src/secmlt/trackers/image_trackers.py

@@ -1,5 +1,5 @@
-from secml2.adv.evasion.perturbation_models import PerturbationModels
-from secml2.trackers.trackers import IMAGE, Tracker
+from secmlt.adv.evasion.perturbation_models import PerturbationModels
+from secmlt.trackers.trackers import IMAGE, Tracker
 import torch
 
 

src/secmlt/trackers/tensorboard_tracker.py

@@ -0,0 +1,59 @@
+from typing import List, Type
+from secmlt.trackers.trackers import (
+    IMAGE,
+    MULTI_SCALAR,
+    SCALAR,
+    GradientNormTracker,
+    LossTracker,
+    Tracker,
+)
+import torch
+from torch.utils.tensorboard import SummaryWriter
+
+
+class TensorboardTracker(Tracker):
+    def __init__(self, logdir: str, trackers: List[Type[Tracker]] = None):
+        super().__init__("Tensorboard")
+        if trackers is None:
+            trackers = [
+                LossTracker(),
+                GradientNormTracker(),
+            ]
+        self.writer = SummaryWriter(log_dir=logdir)
+        self.trackers = trackers
+
+    def track(
+        self,
+        iteration: int,
+        loss: torch.Tensor,
+        scores: torch.Tensor,
+        x_adv: torch.tensor,
+        delta: torch.Tensor,
+        grad: torch.Tensor,
+    ):
+        for tracker in self.trackers:
+            tracker.track(iteration, loss, scores, x_adv, delta, grad)
+            tracked_value = tracker.get_last_tracked()
+            for i, sample in enumerate(tracked_value):
+                if tracker.tracked_type == SCALAR:
+                    self.writer.add_scalar(
+                        f"Sample #{i}/{tracker.name}", sample, global_step=iteration
+                    )
+                elif tracker.tracked_type == MULTI_SCALAR:
+                    self.writer.add_scalars(
+                        main_tag=f"Sample #{i}/{tracker.name}",
+                        tag_scalar_dict={
+                            f"Sample #{i}/{tracker.name}{j}": v
+                            for j, v in enumerate(sample)
+                        },
+                        global_step=iteration,
+                    )
+                elif tracker.tracked_type == IMAGE:
+                    self.writer.add_image(
+                        f"Sample #{i}/{tracker.name}", sample, global_step=iteration
+                    )
+
+    def get_last_tracked(self):
+        return NotImplementedError(
+            "Last tracked value is not available for this tracker."
+        )