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add VectorizedN support for welford_vec_reduce_all and add float<->bf16/fp16 conversion specialization for VectorizedN #126500

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pytorch-bot bot commented May 17, 2024

🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/126500

Note: Links to docs will display an error until the docs builds have been completed.

✅ You can merge normally! (7 Unrelated Failures)

As of commit 3b23540 with merge base ab07867 (image):

FLAKY - The following job failed but was likely due to flakiness present on trunk:

BROKEN TRUNK - The following jobs failed but was present on the merge base:

👉 Rebase onto the `viable/strict` branch to avoid these failures

UNSTABLE - The following jobs failed but were likely due to flakiness present on trunk and has been marked as unstable:

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@pytorch-bot pytorch-bot bot added ciflow/inductor module: cpu CPU specific problem (e.g., perf, algorithm) module: inductor labels May 17, 2024
@CaoE CaoE marked this pull request as draft May 17, 2024 02:08
@CaoE CaoE added the ciflow/trunk Trigger trunk jobs on your pull request label May 17, 2024
Comment on lines +219 to +221
auto result0 = welford_vec_reduce_all(Welford0);
auto result1 = welford_vec_reduce_all(Welford1);
return welford_combine(result0, result1);
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Suggested change
auto result0 = welford_vec_reduce_all(Welford0);
auto result1 = welford_vec_reduce_all(Welford1);
return welford_combine(result0, result1);
return welford_vec_reduce_all(welford_combine(Welford0, Welford1));

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