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[Feature] Add a new parameter init_attr_cache_in
#21
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Reviewer's guide (collapsed on small PRs)Reviewer's GuideIntroduced a new optional Sequence diagram for the new
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| Change | Details | Files |
|---|---|---|
Extend attribution constructors to accept init_attr_cache_in and propagate it. |
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src/tdhook/attribution/gradient_helpers/common.pysrc/tdhook/attribution/grad_cam.pysrc/tdhook/attribution/guided_backpropagation.pysrc/tdhook/attribution/integrated_gradients.pysrc/tdhook/attribution/lrp.pysrc/tdhook/attribution/saliency.py |
Integrate and validate init_attr_cache_in in the attributor function. |
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src/tdhook/attribution/gradient_helpers/common.py |
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Codecov Report❌ Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## main #21 +/- ##
==========================================
- Coverage 96.42% 96.28% -0.15%
==========================================
Files 30 30
Lines 1904 1909 +5
==========================================
+ Hits 1836 1838 +2
- Misses 68 71 +3 ☔ View full report in Codecov by Sentry. |
What does this PR do?
Key insights about the PR.
Linked Issues
Summary by Sourcery
Add support for a new optional callback
init_attr_cache_inacross attribution methods to enable custom initialization of input cache before attribution.New Features:
init_attr_cache_inparameter in the base attribution helper and all concrete methods to allow users to provide custom cache-initialization logic.Enhancements:
init_attr_cache_inin the attribution function to preprocess the input cache and enforce that it returns a valid TensorDict.