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Codecov ReportPatch coverage:
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## master #2720 +/- ##
============================================
+ Coverage 72.08% 72.13% +0.04%
- Complexity 5126 7107 +1981
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Files 473 706 +233
Lines 21970 31599 +9629
Branches 2351 3265 +914
============================================
+ Hits 15838 22795 +6957
- Misses 4925 7252 +2327
- Partials 1207 1552 +345
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This creates the Patch concept along with some start of usages. There is a more specialized ParamPatch for the standard parameter additive patches and a Scaled, Basic, and LoRA implementation. The patches can be created directly, by comparing models, and from gradients. This is an initial step. Following this, there are a few pieces of work that could be considered: 1. DJL Serving Python engine specific patch implementation 2. LoRA for full training 3. Make BasicParamPatch from Optimizer (including gradients, momentum, and lr) Additionally, I included some changes to the IntegrationTest. I ran into the dumb issue where I made the tests private which makes them unable to run from IntegrationTest. Worse, the exceptions had no cause and therefore they wouldn't print any message or run to give feedback through println or logger. It still runs fine in IntelliJ too, making this issue only show up through gradle. After this change, it would provide a clear exception message which makes this easy to debug in the future.
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This creates the Patch concept along with some start of usages. There is a more specialized ParamPatch for the standard parameter additive patches and a Scaled, Basic, and LoRA implementation. The patches can be created directly, by comparing models, and from gradients.
This is an initial step. Following this, there are a few pieces of work that could be considered:
Additionally, I included some changes to the IntegrationTest. I ran into the
dumb issue where I made the tests private which makes them unable to run from
IntegrationTest. Worse, the exceptions had no cause and therefore they wouldn't
print any message or run to give feedback through println or logger. It still
runs fine in IntelliJ too, making this issue only show up through gradle. After
this change, it would provide a clear exception message which makes this easy to
debug in the future.