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jgrusewski fcf76701f4 plan5(task5-B): pivot multi-seed Argo from N×K (seed,fold) to N seed-only fanout
The first L40S deploy attempt (workflow `train-multi-seed-z2llf`, terminated)
failed at startup with `error: unexpected argument '--fold' found` on every
job: `train_baseline_rl` is a multi-fold walk-forward executor that accepts
`--max-folds K`, NOT `--fold N`. The original P5T1 harness assumed the
opposite and fanned out N seeds × K folds = N*K jobs, each invoking the
binary with `--seed N --fold K`.

User chose Path B: pivot to one job per seed (each runs all K folds via the
existing `--max-folds` mechanism). Per-job runtime is K× longer, but fanout
drops from N*K=30 → N=5 (matches L40S pool capacity better) and the binary
contract becomes the one the binary actually has.

4 surface changes:

1. crates/ml/examples/train_baseline_rl.rs — add `--seed N` CLI arg
   (default 42 — historic implicit value). Sets `FOXHUNT_SEED` env var at
   startup BEFORE any CUDA module spins up. Logs the seed value at the
   training start banner.

2. crates/ml/src/cuda_pipeline/mod.rs — add `global_seed()` (reads
   `FOXHUNT_SEED`, default 42) + `mix_seed(base)` (SplitMix64 avalanche
   so adjacent global seeds produce uncorrelated module seeds). Six call
   sites updated to mix the global seed into their previously-hardcoded
   constants:
   - trainer/action.rs: GpuActionSelector seed (0xDEAD_BEEF_CAFE) + the
     epsilon-greedy fallback StdRng (0xAC7_DEF0).
   - cuda_pipeline/gpu_iqn_head.rs: IQN Xavier-init RNG (0x1CA_1234).
   - cuda_pipeline/gpu_iql_trainer.rs: V(s) Xavier-init RNG (0x1C1_9ABC).
   - cuda_pipeline/gpu_her.rs: random-donor RNG (0x4E4_5678).
   - cuda_pipeline/gpu_ppo_collector.rs: rng_seeds Vec for PPO
     experience-collector init + reset (0xAA0_5EED).
   - trainer/training_loop.rs: per-epoch regime_dropout_seed.

3. infra/k8s/argo/train-multi-seed-template.yaml — drop `fold` parameter
   from `train-single` template; binary invoked as `--seed "$SEED"
   --max-folds {{workflow.parameters.folds}}` so the walk-forward sweep
   happens inside the single training process. Drop `FOLD` env var. Update
   the nsys-rep upload filename to drop the fold suffix. Update banners /
   doc comments to reflect "one-job-per-seed" semantics.

4. scripts/argo-train.sh — matrix generator drops the inner fold loop.
   Each emitted task carries only `seed=${s}` and depends on the same
   ensure-fxcache + gpu-warmup. The dry-run synthetic marker switches from
   `seed=${s} fold=${f}` to `seed=${s} max_folds=${FOLDS}` so test harnesses
   count the new shape correctly.

5. scripts/tests/test_multi_seed_harness.sh — assertions updated:
   - `--multi-seed 3 --folds 2` produces 3 tasks (was 6).
   - Rendered binary command must include `--max-folds
     {{workflow.parameters.folds}}` placeholder.
   - Rendered template must declare `folds` workflow parameter (so
     `argo submit -p folds=K` overrides the default).
   - Rendered binary command must NOT contain any per-fold flag — this
     catches the failure mode that broke the first L40S deploy.
   - Backward-compat: `--multi-seed 1 --folds 1` preserves the existing
     single-template path (no DAG matrix tasks emitted).

6. docs/dqn-wire-up-audit.md — adds 1 Wired row documenting the pivot,
   the new `--seed`/`mix_seed` plumbing, all 6 RNG call sites, and the
   end-to-end seed-variation verification result.

Validation:

  cargo check --workspace clean at 11 warnings (workspace baseline preserved).

  cargo build --release --example train_baseline_rl succeeds; --help shows
  the new --seed flag with documented default 42.

  Seed-variation end-to-end test on RTX 3050 Ti (1 fold × 2 epochs each):
    --seed 42  → F0 best Sharpe = -9.7831, best_val_metric = 1.957244,
                 epoch-2 train Sharpe = -16.12, val_Sharpe = +1.11.
    --seed 999 → F0 best Sharpe = +92.9341, best_val_metric = 2.161012,
                 epoch-2 train Sharpe = +92.93, val_Sharpe = -0.25.
  Different best Sharpe / best_val_metric / epoch-2 train + val Sharpe
  across seeds proves the seed actually propagates through the RNG init
  paths and is not just accepted-and-ignored. The seed=42 numbers match
  the prompt's "deterministic baseline" expectation (F0 = -9.7831 was
  bit-identical pre-pivot because no global-seed plumbing existed).

  ./scripts/argo-train.sh dqn --multi-seed 5 --folds 6 --dry-run produces
  exactly 5 WorkflowTask markers (train-s0..train-s4), each with
  `--max-folds {{workflow.parameters.folds}}` in the binary invocation.

  All 3 harness tests PASS:
    - test_multi_seed_harness.sh: 5 PASS lines, exit 0.
    - test_nsys_harness.sh: 4 PASS lines + ALL PASS, exit 0.
    - test_tier_checks.sh: PASS overall (good-fixture passes, bad-fixture
      surfaces expected check rejections), exit 0.

Backward compat: existing single-job `argo-train.sh` callers (no
`--multi-seed`, no `--folds`) route to the original `train-template.yaml`
unchanged. `--seed 42` is a no-op offset for the SplitMix64 mix at the call
sites — the trajectory shifts only when the user passes `--seed` explicitly,
matching the prompt's "default 42 (historic implicit value)" requirement.

L40S pool: argo-train.sh defaults `--gpu-pool ci-training-h100`; user passes
`--gpu-pool ci-training-l40s` at deploy time. No script default change
(per constraint 5).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-26 14:11:32 +02:00
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