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[executorch][native] Record rms_norm op samples - #25094
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/25094
Note: Links to docs will display an error until the docs builds have been completed. ❌ 2 New FailuresAs of commit d3ef9e0 with merge base 925c1bd ( NEW FAILURES - The following jobs have failed:
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Stack from ghstack (oldest at bottom):
RMSNorm joins linear in the op samples, with a case module like linear's. The backend test suite has no RMSNorm test, so every case is new: LLM hidden norms at decode and prefill, one over a hidden size that is not a power of two, the query and key norms over the head dim of a 4-D
[batch, tokens, heads, 128]tensor, norms with and without a weight, rows whose mean square falls below an eps of 1e-8, down to an all-zero row, rows whose squares overflow float16, an outlier channel, a leading batch dim, an odd hidden size, and dynamic token and batch dims. RMSNorm has nonn.Linear, so it fits only the float scheme: one package of 13 cases in 3 dtypes, each method a singleaten.rms_norm.CMake globs the case modules and the CI workflow already covers the directory, so the existing ggml-CPU sample tests,
ggml_sample_test_act_quantandggml_sample_test_no_linear, pick up the new package with no CI change.Authored with Claude Code.
Differential Revision: D131119347
NOTE FOR REVIEWERS: This PR has internal Meta-specific changes or comments, please review them on Phabricator!