perf(optim): replay CUDA update preparation

[JESUSROYETH]

The opt-in flag --model.capture_updates true cuts complete nano detection fit time by 10.01% on the small-batch CUDA workload I measured it on. Five paired ten-epoch runs on public COCO (256 training images, 32 disjoint validation images, 640 px, batch 4, BF16) take 120.850 (120.542–122.793) s native and 108.750 (108.123–110.967) s with replay.

MuSGD records its existing update preparation once, momentum included, and replays it on each new gradient, copied into owned inputs. I kept the learning-rate reads and the parameter writes outside the capture. The update layouts match, so the final foreach write avoids individual add_ calls. Both benchmark arms already had the merged orthogonalization replay, decoded-image caching and device HSV on, and the timing covers the whole fit: setup, loading, augmentation, backward, optimizer, EMA, validation, checkpoints. Measured on an NVIDIA L4, driver 580.178.04, PyTorch 2.9.1+cu129, Lightning 2.6.6.

Model, learned optimizer state, scheduler, EMA, loss and metric byte hashes all match. Peak allocated memory does go up though, from 877.8 to 924.6 MiB, so the default stays off. Unsupported inputs fall back to the native path, warmup restores the state correctly, and reload clears the recordings. Scalar keys keep their native types, and the floating-point bits stay untouched.

Focused coverage passes on PyTorch 2.4.0 and 2.9.1 — inference, reload, AMP and scalar-setting regressions, plus three mutation checks, strict mypy and the full precommit run. I did not run the full make gate or the accelerator goldens. One batch-32 screen showed no benefit, so there's no performance claim for other workloads or for long-run accuracy.

Clean-room acknowledged: only unchanged repository expressions, our own L4 profiles and the registered PyTorch CUDA API went into this — no external optimizer implementation consulted.

WP: 197
Provenance: R42 is the CUDA API contract; unchanged update expressions come from this repository
Assumptions: none
Gate: tests/optim/test_update_replay.py; tests/ptl/test_cli.py::test_capture_updates_flag_reaches_optimizer

[kilo-code-bot]

Code Review Summary

Status: 3 Issues Found | Recommendation: Address before merge

Overview

Severity	Count
CRITICAL	0
WARNING	3
SUGGESTION	0

Issue Details (click to expand)

WARNING

File	Line	Issue
src/lucid_yolo/optim/update_replay.py	239	The warmup pass in _PreparedGroup._record (line 133, inside with torch.cuda.stream(self.stream)) is not wrapped in the restore try/finally that the capture pass (line 137) has. A failure during warmup leaves gradients and momentum mutated, contradicting the CHANGELOG and docstring promise that "a failure while recording raises (gradients and momentum are restored first)".
docs/work_packages/wp-197c.md	29	The "byte-identical between e5d7a85 and 623edc0" claim is stale: commits 1b8e9fe and 42bfdb9 after 623edc0 rewrite musgd.py, replay.py and update_replay.py, so the CUDA evidence no longer covers the tree at HEAD. The "169 focused checks" figure also predates the new test files.
docs/PROVENANCE.md	148	A second usage-log row for R40 (first at line 142) contradicts the table's own preamble, which says it is a first-use log where each source appears once. The pre-existing R42 row at line 148 has the same shape.

Files Reviewed (19 files)

• CHANGELOG.md
• docs/DECISIONS.md
• docs/PROVENANCE.md
• docs/ROADMAP.md
• docs/TRAINING.md
• docs/engineering/phase-17-pose-objective-parity.md
• docs/work_packages/wp-197b.md
• docs/work_packages/wp-197c.md
• docs/work_packages/wp-198.md
• scripts/_tests/test_check_commit_trailers.py
• scripts/lint/check_commit_trailers.py
• src/lucid_yolo/optim/musgd.py
• src/lucid_yolo/optim/replay.py
• src/lucid_yolo/optim/update_replay.py
• src/lucid_yolo/ptl/module.py
• tests/optim/test_musgd_update_copies.py
• tests/optim/test_replay_state.py
• tests/optim/test_update_replay.py
• tests/optim/test_update_replay_guards.py
• tests/ptl/test_cli.py

Fix these issues in Kilo Cloud

Previous Review Summary (commit e5d7a85)

Current summary above is authoritative. Previous snapshots are kept for context only.

Previous review (commit e5d7a85)

Status: No Issues Found | Recommendation: Merge

Files Reviewed (13 files)

• CHANGELOG.md
• docs/DECISIONS.md
• docs/PROVENANCE.md
• docs/ROADMAP.md
• docs/TRAINING.md
• docs/engineering/phase-17-pose-objective-parity.md
• docs/work_packages/wp-197b.md
• docs/work_packages/wp-197c.md
• src/lucid_yolo/optim/musgd.py
• src/lucid_yolo/optim/update_replay.py
• src/lucid_yolo/ptl/module.py
• tests/optim/test_update_replay.py
• tests/ptl/test_cli.py

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_{Reviewed by free · Input: 599.2K · Output: 74.1K · Cached: 4.4M}

[Copilot]

🔵 Needs a closer look

Capturing live optimizer momentum needs human confirmation of accelerator validation, with the full gate and accelerator goldens not yet run.

No open issues 🎉

What changed in this PR

Adds opt-in CUDA replay of MuSGD update preparation to reduce optimizer overhead while keeping learning-rate application and parameter writes outside capture.

Changes:

• Adds group-level replay with state restoration, compatibility guards and reload invalidation.
• Exposes capture_updates through the training module and adds regression coverage.
• Documents measured performance, memory costs and validation limits.

No actionable findings remain. Full gate and accelerator-golden validation remain outstanding.

File	Description
tests/​ptl/​test_cli.py	Tests flag forwarding to the optimizer.
tests/​optim/​test_update_replay.py	Tests replay parity, fallbacks and state handling.
src/​lucid_yolo/​ptl/​module.py	Exposes and forwards the replay option.
src/​lucid_yolo/​optim/​update_replay.py	Implements guarded capture and replay.
src/​lucid_yolo/​optim/​musgd.py	Integrates replay and extracts native update preparation.
docs/​work_packages/​wp-197c.md	Records design, measurements and validation limits.
docs/​work_packages/​wp-197b.md	Links the follow-up work package.
docs/​TRAINING.md	Documents the opt-in training flag.
docs/​ROADMAP.md	Tracks the open replay work package.
docs/​PROVENANCE.md	Records update-replay API provenance.
docs/​engineering/​phase-17-pose-objective-parity.md	Includes the new work-package record.
docs/​DECISIONS.md	Extends the CUDA replay decision.
CHANGELOG.md	Announces optional update-preparation replay.

_{Review effort: Balanced}

[kilo-code-bot]

WARNING: The CHANGELOG and docstring both promise that "a failure while recording raises (gradients and momentum are restored first)". _record_group (lines 238-248) calls _PreparedGroup(...) and entry.run(...) outside any try/finally, and _PreparedGroup._record restores gradients and momentum only in its own finally (lines 142-150). So a failure during the second recording pass (the torch.cuda.graph block at line 137) does restore gradients and momentum, but a failure during the first warmup pass (line 133, inside with torch.cuda.stream(self.stream)) restores nothing, because that block is not wrapped. The CHANGELOG line 11 and the capture_updates docstring overstate the guarantee. Either the warmup pass needs the same restore, or the prose needs qualifying.

[kilo-code-bot]

WARNING: The claim "Optimizer sources are byte-identical between e5d7a85 and 623edc0, so a CUDA run recorded against either commit covers both" is stale. Commits after 623edc0 in this range — 1b8e9fe (fix(optim): re-record replay after lasting change) and 42bfdb9 — rewrite src/lucid_yolo/optim/{musgd,replay,update_replay}.py (206 insertions / 58 deletions over 623edc0..HEAD), so neither named commit matches the tree at HEAD and the CUDA evidence this sentence is meant to transfer no longer covers the current optimizer. The "169 focused CPU/CUDA/doctest checks" figure likewise predates the new test files added after 623edc0 (tests/optim/test_update_replay_guards.py, tests/optim/test_replay_state.py).

[kilo-code-bot]

WARNING: This is a second usage-log row for R40 (the first is at line 142, dated 2026-10-16), but the table's own preamble (line 120) states it is a first-use log where "a source appears once, on the day it was first read, and every later use of it is traced through the Provenance: trailers ... rather than by another line here." Either the preamble rule or this row must go. Note the pre-existing 2026-10-18 R42 row (line 148) has the same shape, so the rule and the practice need reconciling once.