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Releases: bethgelab/foolbox

Version 3.0.3

03 Jul 13:48
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Fixes a bug in the BrendelBethgeAttack and updated Numba to silence warnings.

Version 3.0.2

23 May 14:35
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Fixes a bug in the BrendelBethgeAttack (thanks @AidanKelley)

Version 3.0.1

23 May 07:49
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Bug fixes

  • type annotations are now correctly exposed using py.typed (file was missing in MANIFEST)
  • TransformBoundsWrapper now correctly handles data_format (thanks @zimmerrol)

Version 3.0.0

22 Mar 21:22
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New Features

Foolbox 3 aka Foolbox Native has been rewritten from scratch with performance in mind. All code is running natively in PyTorch, TensorFlow and JAX, and all attacks have been rewritten with real batch support.

Version 3.0.0b1

16 Feb 23:26
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Version 3.0.0b1 Pre-release
Pre-release

New Features

  • added foolbox.gradient_estimators
  • improved attack hyperparameter documentation

Version 3.0.0b0

15 Feb 15:26
28f06a4
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Version 3.0.0b0 Pre-release
Pre-release

Foolbox 3 aka Foolbox Native has been rewritten from scratch with performance in mind. All code is running natively in PyTorch, TensorFlow and JAX, and all attacks have been rewritten with real batch support.

Warning: This is a pre-release beta version. Expect breaking changes.

Version 2.4.0

07 Feb 14:38
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New Features

  • fixed PyTorch model gradients (fixes DeepFool with batch size > 1)
  • added support for TensorFlow 2.0 and newer (Graph and Eager mode)
  • refactored the tests
  • support for the latest randomgen version

Version 2.3.0

04 Nov 22:07
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New Features

  • new EnsembleAveragedModel (thanks to @zimmerrol)
  • new foolbox.utils.flatten
  • new foolbox.utils.atleast_kd
  • new foolbox.utils.accuracy
  • PyTorchModel now always warns if model is in train mode, not just once
  • batch support for ModelWithEstimatedGradients

Bug fixes

  • fixed dtype when using Adam PGD with a PyTorch model
  • fixed CW attack hyperparameters

Version 2.2.0

28 Oct 15:56
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New Features

  • support for Foolbox extensions using the foolbox.ext namespace

Version 2.1.0

27 Oct 09:18
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New Features

  • New foolbox.models.JAXModel class to support JAX models (https://github.com/google/jax)
  • The preprocessing argument of models now supports a flip_axis key to support common preprocessing operations like RGB to BGR in a nice way. This builds on the ability to pass dicts to preprocessing introduced in Foolbox 2.0.

Bug fixes and improvements

  • Fixed a serious bug in the LocalSearchAttack (thanks to @duoergun0729)
  • foolbox.utils.samples now warns if samples are repeated
  • foolbox.utils.sampels now uses PNGs instead of JPGs (except for ImageNet)
  • Other bug fixes
  • Improved docstrings
  • Improved docs