Captum v0.4.1 Release
The Captum v0.4.1 release includes three new tutorials, a few code improvements and bug fixes.
New Tutorials
Robustness tutorial:
- Applying robustness attacks and metrics to CIFAR model and dataset
Concept tutorials:
- TCAV for image classification for googlenet model
- TCAV for NLP sentiment analysis model
Improvements
- Reduced unnecessary reliance on
Numpy
across the codebase by replacing such usages withPyTorch
equivalents when possible (PR #714 #755 #760) - Enhanced the error message for missing modules rules in LRP (PR #727)
- Switched linter to
ufmt
from previousblack
+isort
and reformatted the code accordingly (PR #739) - Generalized implementation of
captum._utils.av
for TCAV to use and refactored TCAV to simplify the creation of datasets used to train concept models (PR #747)
Bug Fixes
- Fixed the device error when using TCAV on cuda (Issue #719 #720 #721 , PR #725)
- Captum Insight now cache a subset of batches from dataset for recycle to fix the issue of not showing data after iterating all batches (PR #728)
- Corrected the loading of reference word embedding in tutorial “Interpreting Bert Part 1” (PR #743)
- Renamed the util
save_div
’s argumentdefault_value
todefault_denom
and unified its behaviors for different denominator types (Issue #654 , PR #751)