- Support TensorFlow 2.14 (#322)
- Add way to strip arbitrary output activations (#310)
- Fix
is_layer_at_idx
for LRP (#308) - Support Python 3.11 and TensorFlow 2.12 (#313)
- Update CI workflows and dev-dependencies (#313)
- Fix
Perturbate
on RGB images (#306) - Fix documentation
- Support TensorFlow 2.11 (#300)
- Update CI workflows and dev-dependencies (#301)
- Remove dead
analyzer.fit
code left from PatternNet and PatternAttribution (#289) - Fixes to README and documentation
iNNvestigate for TensorFlow 2. This is a major version release and therefore breaking backward compatibility.
Breaking changes:
- update lower dependency bounds to Python 3.8 and TensorFlow 2.6
- use TensorFlow's Keras instead of deprecated stand-alone Keras
- manual disabling of eager execution is required via
tf.compat.v1.disable_eager_execution()
(#277) - temporarily remove
PatternNet
,PatternAttribution
,LRPZIgnoreBias
andLRPEpsilonIgnoreBias
(#277) - remove DeepLIFT (#257)
Changes for developers:
- switch setup to Poetry (#257)
- adopt
src
andtests
layout (#257) - adopt Black code style (#247)
- add linters to dev dependencies (#257)
- added type annotations (#263, #266, #277)
- added reference tests & CI to guarantee identical attributions compared to
v1.0.9
(#258, #277) - refactor backend (#263, #277)
- refactor analyzers: explicit class attributes, fixes for serialization (#266, #277)
- bug fixes (#263)
- BatchNormalization Layer compatible with LRP
- EmbeddingLayer support
- new Alpha-Beta-LRP-rules
Additionally various PR were merged and bugs fixed, for details see PR #222
Bugfixes, increased code coverage, CI.
Add Python 2 compatibility again.
Bugfixes.
- Add beta version of DeepLIFT (as in Ancona et.al.) and wrapper for DeepLIFT package.
- Updating readme and bugfixes.
Treat IntegratedGradients as attribution method and bugfixes.
Added the following functionality:
- Additional notebooks.
- Analyzers: Input*Gradient
- Added parameter to choose between plain, abs, square gradient in Gradient analyzer.
- New interface via register-methods in analyzer base code.
- Many fixes.
- Support for read-the-docs documentation.
Includes the following functionality:
- Analyzers: Gradient, SmoothGrad, IntegratedGradients, PatternNet, PatternAttribution, LRP, DeepTaylor, Input, Random.
- Pattern computer.