pytorch

b4799736 - autograd: fix non-deterministic output in codegen comments (#84695)

autograd: fix non-deterministic output in codegen comments (#84695) Summary: Like it says in the title. Currently, this will return output like this: In Buck1, that's OK because Buck1's caching doesn't really care too much about However, in Buck2, this is a disaster, because caching is based exclusively on inputs and outputs and The diff here proposes making the path relative to the codegen script itself, which should carry about as much info, but avoid cache misses. Concretely, this: ``` // generated from /dev/shm/uid-34135/cfbc5712-seed-nspid4026533424_cgpid2794673-ns-4026533443/tools/autograd/templates/python_functions.h ``` Becomes, this: ``` // generated from ../tools/autograd/templates/python_functions.h ``` So, we keep the useful part, and we get caching. This matters because those headers are used in actions like: ``` fbcode//deeplearning/fbgemm/fbgemm_gpu/codegen:embedding_ops -- action (cxx_compile gen_embedding_backward_adam_split_unweighted_cuda.cu (pic)) ``` Those actions take upwards of 5 minutes to finish, so by allowing a cache hit, we are a) saving our users a lot of time and b) saving some RE capacity as well. This actually matters a lot because right now those targets are produced by `//caffe2:generate-code`, which itself doesn't get cache hits from RE because `generate_code.par` is non-deterministic (this is, unfortunately, true of PARs in general), so that rule introduces non-determinism that the codegen propagates and we get zero caching. This diff doesn't fix `//caffe2:generate-code`'s inputs being non-deterministic, but it does fix its *outputs* being non-deterministic, which means the non-determinism stops there, and we get back to cache hits. Test Plan: - CI ``` buck2 build fbcode//caffe2:generate-code buck2 build fbcode//deeplearning/fbgemm/fbgemm_gpu/codegen:embedding_ops ``` Reviewed By: ndmitchell Differential Revision: D39348565 Pull Request resolved: https://github.com/pytorch/pytorch/pull/84695 Approved by: https://github.com/soulitzer