Codecov Report

❌ Patch coverage is 80.00000% with 13 lines in your changes missing coverage. Please review.
✅ Project coverage is 90.50%. Comparing base (2b4c350) to head (49f824e).
⚠️ Report is 1 commits behind head on master.

@@            Coverage Diff             @@
##           master     #356      +/-   ##
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- Coverage   90.73%   90.50%   -0.24%     
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  Files          16       16              
  Lines        2300     2339      +39     
==========================================
+ Hits         2087     2117      +30     
- Misses        213      222       +9     

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So I built a draft implementation for Moreau.jl using this branch; it worked really well! Thank you.

A few issues that popped up:

• We need to decide whether to cache data for the backward pass when we solve the forward problem. There doesn't seem to be any way to know if we're being called from a DiffOpt context or not, so I ended up using the presence of the DiffOpt library as a proxy for whether to store backward gradients.
• We support differentiating the quadratic term in the objective, and it seemed to me DiffOpt only supported linear sensitivity of the obj? I wasn't sure.
• Converting from dobj (DiffOpt) to dx (Moreau interface) required us to cache a bunch of data structures like P, x, and q that we otherwise didn't need in the Julia interface.
• We ended up needing to cache the structure of A on the Julia side to dA and db into dconstraint

Overall, I think a bunch of this is just API differences, and probably can't be fixed at this point, but figured it was worth mentioning.

This looks good to merge, let me know if there are any comments