Release v0.7.0 · SeldonIO/alibi

v0.7.0 (2022-05-18)

This release introduces two new methods, a GradientSimilarity explainer and a ProtoSelect data summarisation algorithm.

New feature GradientSimilarity explainer for explaining predictions of gradient-based (PyTorch and TensorFlow) models by returning the most similar training data points from the point of view of the model (docs).
New feature We have introduced a new subpackage alibi.prototypes which contains the ProtoSelect algorithm for summarising datasets with a representative set of "prototypes" (docs).
ALE explainer now can take a custom grid-point per feature to evaluate the ALE on. This can help in certain situations when grid-points defined by quantiles might not be the best choice (docs).
Extended the IntegratedGradients method target selection to handle explaining any scalar dimension of tensors of any rank (previously only rank-1 and rank-2 were supported). See #635.
Python 3.10 support. Note that PyTorch at the time of writing doesn't support Python 3.10 on Windows.

Fixed a bug which incorrectly handled multi-dimensional scaling in CounterfactualProto (#646).
Fixed a bug in the example using CounterfactualRLTabular (#651).

tensorflow is now an optional dependency. To use methods that require tensorflow you can install alibi using pip install alibi[tensorflow] which will pull in a supported version. For full instructions for the recommended way of installing optional dependencies please refer to Installation docs.
Updated sklearn version bounds to scikit-learn>=0.22.0, <2.0.0.
Updated tensorflow maximum allowed version to 2.9.x.

This release introduces a way to manage the absence of optional dependencies. In short, the design is such that if an optional dependency is required for an algorithm but missing, at import time the corresponding public (or private in the case of the optional dependency being required for a subset of the functionality of a private class) algorithm class will be replaced by a MissingDependency object. For full details on developing alibi with optional dependencies see Contributing: Optional Dependencies.
The CONTRIBUTING.md has been updated with further instructions for managing optional dependencies (see point above) and more conventions around docstrings.
We have split the Explainer base class into Base and Explainer to facilitate reusability and better class hierarchy semantics with introducing methods that are not explainers (#649).
mypy has been updated to ~=0.900 which requires additional development dependencies for type stubs, currently only types-requests has been necessary to add to requirements/dev.txt.
Fron this release onwards we exclude the directories doc/ and examples/ from the source distribution (by adding prune directives in MANIFEST.in). This results in considerably smaller file sizes for the source distribution.