NAVA learner: drive the LR schedule off the syncer global_step - #3
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The NAVA learner's WarmupCosineAnnealingLR was stepped once per local optimizer step, so its phase was a function of this process's inner-step count since launch. On a Spot preemption the relaunched learner reset that count to zero: it re-ran warmup and the full cosine from the top, and the two learners drifted onto independent schedules. Re-base the schedule onto the syncer's global_step — the outer-step clock that is broadcast and re-acquired on every (re)connect, is durable on the on-demand head, and is identical across learners. A relaunched learner now resumes its LR at the correct phase; both learners always share one schedule. - learner: add --total-steps (outer-step horizon T); parameterize the cosine over global_step in [0, T]; replace per-step sched.step() with set_lr_from_clock() at each sync boundary (and a seed before the loop). --syncer none falls back to the local-step clock. Log the current lr. - backend: pass --total-steps through to the learner command. warmup_steps and the cosine horizon are now in global/outer-step units. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
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The NAVA learner's WarmupCosineAnnealingLR was stepped once per local optimizer step, so its phase was a function of this process's inner-step count since launch. On a Spot preemption the relaunched learner reset that count to zero: it re-ran warmup and the full cosine from the top, and the two learners drifted onto independent schedules.
Re-base the schedule onto the syncer's global_step — the outer-step clock that is broadcast and re-acquired on every (re)connect, is durable on the on-demand head, and is identical across learners. A relaunched learner now resumes its LR at the correct phase; both learners always share one schedule.
warmup_steps and the cosine horizon are now in global/outer-step units.