This minor release adds evaluation metrics to the package and bumps PyTorch to version 2.0
Note: TorchCAM 0.4.0 requires PyTorch 2.0.0 or higher.
Highlights
Evaluation metrics
This release comes with a standard way to evaluate interpretability methods. This allows users to better evaluate models' robustness:
from functools import partial
from torchcam.metrics import ClassificationMetric
metric = ClassificationMetric(cam_extractor, partial(torch.softmax, dim=-1))
metric.update(input_tensor)
metric.summary()What's Changed
New Features 🚀
- feat: Added CAM evaluation metric by @frgfm in #172
- ci: Added FUNDING button by @frgfm in #182
- feat: Added new TV models to demo by @frgfm in #184
- ci: Added precommits, bandit & autoflake by @frgfm in #192
- feat: Removes model hooks when the context manager exits by @frgfm in #198
Bug Fixes 🐛
- chore: Applied post-release modifications by @frgfm in #180
- fix: Fixed division by zero during normalization by @frgfm in #185
- fix: Fixed zero division for weight computation in gradient based methods by @frgfm in #187
- docs: Fixes README badges by @frgfm in #194
- ci: Fixes issue templates by @frgfm in #196
- fix: Fixes SmoothGradCAMpp by @frgfm in #204
Improvements
- docs: Improved documentation build script by @frgfm in #183
- docs: Updates README & CONTRIBUTING by @frgfm in #193
- feat: Removed param grad computation in scripts by @frgfm in #201
- style: Updates precommit hooks and mypy config by @frgfm in #203
- refactor: Replaces flake8 by ruff and updates python version by @frgfm in #211
- style: Bumps ruff & black, removes isort & pydocstyle by @frgfm in #216
- style: Bumps ruff and updates torch & torchvision version specifiers by @frgfm in #219
- docs: Updates CONTRIBUTING & README by @frgfm in #220
- test: Speeds up test suite using plugins by @frgfm in #222
- ci: Adds multiple build CI jobs by @frgfm in #223
- feat: Removes warnings for torchvision and matplotlib by @frgfm in #224
Full Changelog: v0.3.2...v0.4.0
Contributors
frgfm