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@m-melis m-melis released this 24 Jul 14:42
· 396 commits to master since this release
v0.13
4f01486

See full release here: https://gitlab.com/secml/secml/-/releases/v0.13

CHANGELOG

  • #814 Added new evasion attack CAttackEvasionPGDExp.
  • #780 Added new classifier CClassifierDNR implementing Deep Neural Rejection (DNR). See Sotgiu et al. “Deep neural rejection against adversarial examples”, EURASIP J. on Info. Security (2020).
  • #47 Added new classifier CClassifierMulticlassOVO implementing One-vs-One multiclass classification scheme.
  • #765 Extended CModule to support trainable modules via fit and fit_forward functions.
  • #800 Security evaluation can now be run using Cleverhans attacks. The name of the parameter to check should be specified as attack_params.<param_name> as an input argument for the constructor of CSecEval.
  • #839 Experimental support of Windows operating system (version 7 or later).

Requirements (1 change)

  • #768 Removed temporary pin of Pillow to v6 which used to break torch and torchvision packages.

Added (4 changes)

  • #100007 Added new experimental package ml.scalers with a different implementation of ml.features.normalization classes directly based Scikit-Learn's scalers. Included classes are: CScalerMinMax, CScalerStd, CScalerNorm.
  • #770 Added new methods to convert a CArray to specific scipy.sparse array formats: tocoo, tocsc, todia, todok, tolil.
  • #812 CAttackPoisoning now exposes: x0, xc, yc, objective_function and objective_function_gradient.
  • #776 n_jobs is now a init parameter of CModule and subclasses and not passed via fit anymore.

Improved (12 changes)

  • #817 Added CClassifierSVM native support to OVA multiclass scheme, without replicating the kernel in each one-vs-all classifier.
  • #574 Added _clear_cache mechanism to CModule and classes that require caching data in the forward pass before backward (e.g., exponential kernels do that to avoid re-computing the kernel matrix in the backward pass).
  • #820 Add parallel execution of forward method for CClassifierMulticlassOVA and CClassifierMulticlassOVO.
  • #815 Simplified CAttack interface (now only requires implementing run as required by CSecEval).
  • #574 Modified kernel and classifier interfaces to allow their use as preprocessing modules.
  • #775 Improved efficiency in gradient computation of SVMs, by back-propagating the alpha values to the kernel.
  • #773 Improved efficiency in the computation of gradients of evasion attacks (CAttackEvasionPGDLS). Now gradient is called once rather than twice to compute the gradient of the objective function.
  • #801 CSecEval will now check that the param_name input argument can be found in the attack class used in the evaluation.
  • #695 COptimizerPGD now exits optimization if constraint radius is 0. COptimizerPGD , COptimizerPGDLS and COptimizerPGDExp will now raise a warning if the 0-radius constraint is defined outside the given bounds.
  • #828 CClassifierSVM now uses n_jobs parameter for parallel execution of training in case of multiclass datasets.
  • #767 Using scipy.sparse .hstack and .vstack instead of a custom implementation in CSparse.concatenate.
  • #772 Using scipy.sparse .argmin and .argmax instead of a custom implementation in CSparse.argmin and CSparse.argmax.

Changed (6 changes)

  • #817 Kernel is now used as preprocess in CClassifierSVM.
  • #817 Removed store_dual_vars and kernel.setter from CClassifierSVM. Now a linear SVM is trained in the primal (w,b) if kernel=None, otherwise it is trained in the dual (alpha and b), on the precomputed training kernel matrix.
  • #765 Unified fit interface from fit(ds) to fit(x,y) to be consistent across normalizers and classifiers.
  • #574 Removed redundant definitions of gradient(x, w) from CKernelRBF, CKernelLaplacian, CKernelEuclidean, CClassifierDNN, CNormalizerUnitNorm. The protected property grad_requires_forward now specifies if gradient has to compute an explicit forward pass or only propagate the input x through the pre-processing chain before calling backward.
  • #823 Removed surrogate_data parameter from CAttackPoisoning and renamed it to double_init_ds in CAttackEvasion subclasses.
  • #829 CClassifierRejectThreshold now returns wrapped classifier classes plus the reject class (-1).

Fixed (10 changes)

  • #816 Fixed stop condition of COptimizerPGD which was missing index i.
  • #825 Infer the number of attacked classifier classes directly from it (instead of inferring it from surrogate data) in CAttackEvasionPGDLS to fix a crash when the class index of data points is greater or equal than the number of alternative data points.
  • #810 Fixed CClassifierPyTorch.backward not working properly due to a miscalculation of the number of input features of the model when a CNormalizeDNN is used as preprocessor.
  • #803 Fixed checks on the inner classifier in CClassifierRejectThreshold which can be bypassed by using the clf attribute setter, now removed.
  • #818 Fixed CCreator.set not allowing to set writable attributes of level-0 readable-only attributes.
  • #819 Fixed CCreator.get_params not returning level-0 not-writable attributes having one or more writable attributes.
  • #785 Fixed constant override of matplotlib backend in CFigure on Windows systems.
  • #783 Fixed model_zoo.load_model improperly building download urls depending on the system default url separator.
  • #771 Fixed the following methods of CSparse to ensure they properly work independently from the sparse array format: save, load, __pow__, round, nan_to_num, logical_and, unique, bincount, prod, all, any, min, max.
  • #769 CArray.tocsr() now always returns a scipy.sparse.csr_matrix array as expected.

Removed & Deprecated (2 changes)

  • #540 Removed discrete and surrogate_classifier parameter from CAttack.
  • #777 Deprecated attribute kernel is now removed from CClassifierSGD, CClassifierRidge and CClassifierLogistic classifiers.

Documentation (10 changes)

  • #839 Windows is now displayed as a supported Operating System in README and setup.
  • #806 Documented pytorch extra component installation requirements under Windows.
  • #834 Temporarily pinned numpydoc to < 1.1 to avoid compatibility issues of the newest version.
  • #807 Documentation is now built using Sphinx https://readthedocs.org/ theme v0.5 or higher.
  • #830 Fixed links to repository pages by adding a dash after project name.
  • #758 Added a direct link to the gitlab.com repository in README.
  • #788 Notebooks now include a warning about the required extra components (if any).
  • #787 Fixed argmin -> argmax typo in docstring of CClassifierRejectThreshold.predict method.
  • #789 Fixed notebook 4 not correctly generating a separate dataset for training the target classifiers.
  • #791 Fixed random_state not set for CClassifierDecisionTree in notebook 4.
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