Passing GSoC Midterms

Hey everyone! Weeks 7 and 8 are done, and the biggest news first: I passed the midterm evaluation🎉. Half of GSoC is behind me now. These two weeks were less about writing new classes and more about going back and making the ones I already had a lot stricter. Here is what happened. PR #1920: The RatioEstimatorBuilder This PR adds the builder for the NRE family, so NRE_A , NRE_B , NRE_C and BNRE all get the same typed interface that NPE and NLE already had. The builder itself was honestly the easy part. By now the pattern is well established, so it was mostly mirroring what already worked, with linear , mlp and resnet as the classifier options. The interesting part was what my mentor Jan Teusen suggested we bundle into the same PR. Some improvements to the base class PR #1920 was the first PR that proved the shared base class serves a third family. My Mentor, Jan pointed out that this was exactly the right moment to fix the validation gaps in that base, because then the NRE builder and the vector field builder that was coming next would inherit the fixes for free, instead of me retrofitting four builders later. So we folded a hardening bundle into the same PR: Invalid Literal values now raise at construction. This was the real gap. If you typed a wrong field name , Python already raised a TypeError for you. But if you typed a wrong value on a correctly named field, like z_score_input="idependent" , nothing happened until you called .train() and it blew up much later. Now it fails immediately. Model-incompatible kwargs now raise too. Passing num_blocks to a linear classifier used to be silently dropped, and the same argument on mlp crashed late. Both are caught at construction now by inspecting the target build function's signature. frozen=True on the config dataclasses. Configs are now immutable. If you want a different setting, you make a new object instead of mutating the old one. This sounds like a small thing but it removes a whole class of " I changed the config