Files
foxhunt/scripts/argo-alpha-rl.sh
jgrusewski 1168f3ea83 feat(rl): R8 — alpha_rl_train CLI + Argo template + dispatcher
Closes the rebuild plan's R8 scope: production runner shape for the
integrated RL trainer. Three artifacts wired end-to-end:

  1. `crates/ml-alpha/examples/alpha_rl_train.rs` — clap CLI driving
     `IntegratedTrainer::step_with_lobsim` against MBP-10 windows
     loaded via `MultiHorizonLoader::next_sequence_pair` (R2) for
     true `(s_t, s_{t+1})` adjacency. Per `feedback_mbp10_mandatory`,
     `--mbp10-data-dir` is required — no synthetic-data fallback in
     the production path.
  2. `infra/k8s/argo/alpha-rl-template.yaml` — WorkflowTemplate
     mirroring alpha-perception's DAG (check-cache → ensure-binary →
     train; warmup-gpu parallel). Binary cache slot is
     `/data/bin/<sha>/alpha_rl_train` (distinct from `alpha_train`
     so the two binaries coexist at the same SHA).
  3. `scripts/argo-alpha-rl.sh` — dispatcher with three rebuild-plan
     guards baked in.

## Dispatcher guards (per the rebuild plan's feedback list)

`feedback_default_to_l40s_pool` (2026-05-09): default `--gpu-pool`
is `ci-training-l40s` (sm_89). H100 (sm_90) is opt-in for production
scale-up only. Cubins must match the device, so the dispatcher
derives `cuda-compute-cap` from the pool name and threads it into
the workflow params.

`feedback_argo_template_must_apply` (2026-05-21 canonical incident):
`argo submit --from=wftmpl/<name>` reads the cluster CRD, NOT the
on-disk YAML; unknown `-p` parameters silently no-op without a prior
`kubectl apply`. Dispatcher applies the local template BEFORE every
submission (overrideable via `--skip-template-apply` for the rare
case where you've already applied manually).

`feedback_push_before_deploy` (2026-05-20 canonical incident): the
in-cluster `ensure-binary` pod fetches source from `origin/<branch>`,
NOT the local working tree. Submitting before `git push` deploys the
last-pushed SHA, which can lag local diff by N commits. Dispatcher
verifies `git rev-parse HEAD == git rev-parse origin/<branch>` and
hard-errors with the explicit push command otherwise. Bypass via
`--skip-push-check` (only when intentionally deploying a previously-
pushed SHA via `--sha`).

## CLI: gate G8 (NaN abort)

Per `feedback_stop_on_anomaly` + `feedback_kill_runs_on_anomaly_quickly`,
the CLI checks every per-head loss (l_bce / l_q / l_pi / l_v / l_aux
/ l_total) for finiteness after each `step_with_lobsim` call.
Non-finite at any step → write summary with `nan_abort_step` set →
`process::exit(2)`. R9's cluster smoke tail-watcher kills the
workflow on the non-zero exit code, satisfying gate G8 from the
rebuild plan.

## CLI: knobs that ARE on the CLI

Structural / boundary parameters only (per
`pearl_controller_anchors_isv_driven`: every adaptive knob lives in
ISV, not CLI flags):
  * `--mbp10-data-dir / --predecoded-dir / --out` — I/O paths.
  * `--n-steps` — wall-budget control (1000 R9 smoke / 50k+ prod).
  * `--seq-len / --n-backtests / --per-capacity` — structural
    sizing. seq_len threads into the loader's multi-resolution
    `1:<seq_len>` config; n_backtests into both LobSimCuda and
    PerceptionTrainerConfig.n_batch.
  * `--seed` — reproducibility per
    `pearl_scoped_init_seed_for_reproducibility` (forks deterministic
    sub-seeds for dqn / ppo / per).
  * `--instrument-mode` — MBP-10 filter (all / front-month / id=N).
  * `--gpu-idx` — CUDA device selection.

What's NOT on the CLI: γ / τ / ε / entropy_coef / per_α / reward_scale
/ per-head LRs — all live in ISV[400..417] and are driven by R5's
controllers from EMA-tracked diagnostics. Per the rebuild plan
A1: "every adaptive bound is signal-driven, not tuned."

## Cluster smoke entry point

```bash
# R9 validation smoke (after pre-cluster local CUDA tests green).
./scripts/argo-alpha-rl.sh --n-steps 1000 --instrument-mode front-month

# Production scale-up (gated by R9's multi-fold pass).
./scripts/argo-alpha-rl.sh --n-steps 50000 --n-backtests 32 \
  --per-capacity 100000  # GPU sum-tree R-future when capacity > 4096
```

## What's NOT in this commit

The R9 cluster smoke run itself is out of band — this commit ships
the entry points. R9 will execute the pre-cluster validation
checklist + first 1000-step smoke + multi-fold walk-forward G8 gate
per the rebuild plan §"Cluster smoke discipline".

The summary JSON's schema is intentionally narrow (final-step losses
+ replay len + completion state + NaN abort marker). R-future may
add per-epoch breakdowns + per-ISV-slot snapshots once the cluster
smoke tells us which diagnostics are actually load-bearing for kill
decisions.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-05-23 13:30:10 +02:00

195 lines
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#!/usr/bin/env bash
# Submit the alpha-rl (integrated RL trainer) workflow.
#
# Drives `IntegratedTrainer::step_with_lobsim` (DQN + PPO on shared
# Mamba2 → CfC encoder, R7d off-policy replay) against MBP-10 from the
# training-data PVC, using LobSimCuda as the synthetic-book environment.
# Emits alpha_rl_train_summary.json to the feature-cache PVC.
#
# Guards (enforced by the rebuild plan A9 feedback list):
# * `feedback_default_to_l40s_pool` — defaults to ci-training-l40s;
# H100 (sm_90) is opt-in for scale-up sweeps only.
# * `feedback_push_before_deploy` — verifies local HEAD == origin
# HEAD before submission, refuses to submit otherwise.
# * `feedback_argo_template_must_apply` — kubectl-applies the local
# alpha-rl-template.yaml BEFORE `argo submit --from=wftmpl/alpha-rl`
# (the submit reads the cluster CRD, NOT the on-disk YAML, so
# unknown -p params silently no-op without the apply).
#
# Usage:
# ./scripts/argo-alpha-rl.sh # 1k step smoke on HEAD
# ./scripts/argo-alpha-rl.sh --branch main
# ./scripts/argo-alpha-rl.sh --n-steps 50000 --n-backtests 32 # production sweep
# ./scripts/argo-alpha-rl.sh --gpu-pool ci-training-h100 # opt into H100
# ./scripts/argo-alpha-rl.sh --watch
#
# Plan reference: docs/superpowers/plans/2026-05-23-integrated-rl-trainer-rebuild.md
set -euo pipefail
SHA=HEAD
BRANCH=$(git symbolic-ref --short HEAD 2>/dev/null || echo "ml-alpha-phase-a")
GPU_POOL=ci-training-l40s
N_STEPS=1000
SEQ_LEN=32
N_BACKTESTS=1
PER_CAPACITY=4096
SEED=16962
INSTRUMENT_MODE=front-month
WATCH=false
SKIP_PUSH_CHECK=false
SKIP_TEMPLATE_APPLY=false
usage() {
cat <<EOF
Usage: $0 [OPTIONS]
--sha <commit> Git SHA (default: HEAD on the current branch)
--branch <branch> Git branch (default: $BRANCH)
--gpu-pool <pool> GPU pool (default: $GPU_POOL).
Per feedback_default_to_l40s_pool: L40S is
the default. Opt into ci-training-h100 only
for scale-up runs that need sm_90 / 80GB.
--n-steps <n> step_with_lobsim count (default: $N_STEPS).
R9 smoke = 1000; production = 50000+.
--seq-len <n> Encoder sequence length (default: $SEQ_LEN).
--n-backtests <n> Parallel LobSim instances per step
(default: $N_BACKTESTS).
--per-capacity <n> PER buffer capacity (default: $PER_CAPACITY).
--seed <n> Random seed (default: $SEED).
--instrument-mode <m> all | front-month | id=<N> (default: $INSTRUMENT_MODE)
--watch Follow logs via argo watch
--skip-push-check Bypass the feedback_push_before_deploy guard
(rare; use only when submitting against a
previously-pushed SHA via --sha).
--skip-template-apply Bypass the feedback_argo_template_must_apply
guard (rare; only when you've manually
kubectl applied the template already).
-h, --help Show this help
EOF
}
while [[ $# -gt 0 ]]; do
case "$1" in
--sha) SHA="$2"; shift 2 ;;
--branch) BRANCH="$2"; shift 2 ;;
--gpu-pool) GPU_POOL="$2"; shift 2 ;;
--n-steps) N_STEPS="$2"; shift 2 ;;
--seq-len) SEQ_LEN="$2"; shift 2 ;;
--n-backtests) N_BACKTESTS="$2"; shift 2 ;;
--per-capacity) PER_CAPACITY="$2"; shift 2 ;;
--seed) SEED="$2"; shift 2 ;;
--instrument-mode) INSTRUMENT_MODE="$2"; shift 2 ;;
--watch) WATCH=true; shift ;;
--skip-push-check) SKIP_PUSH_CHECK=true; shift ;;
--skip-template-apply) SKIP_TEMPLATE_APPLY=true; shift ;;
-h|--help) usage; exit 0 ;;
*) echo "Unknown option: $1"; usage; exit 1 ;;
esac
done
# ── GPU pool → CUDA_COMPUTE_CAP ─────────────────────────────────────
# Per `feedback_default_to_l40s_pool` (2026-05-09): SP-chain training
# defaults to L40S (sm_89). H100 (sm_90) is opt-in for scale-up only.
# Cubins must match the device, so the dispatcher derives the cap from
# the pool name and threads it into the workflow params.
case "$GPU_POOL" in
ci-training-l40s|ci-training)
SM=89 ;;
ci-training-h100)
SM=90 ;;
*)
echo "ERROR: unknown gpu-pool: $GPU_POOL"
echo " Supported: ci-training-l40s, ci-training-h100"
exit 1 ;;
esac
# ── Guard 1: feedback_argo_template_must_apply ───────────────────────
# `argo submit --from=wftmpl/<name>` reads the cluster CRD, NOT the
# on-disk YAML. If the template has been edited locally but never
# `kubectl apply -f`'d, the submit silently uses the stale cluster
# version + drops any newly-added parameters. Pearl ref: 2026-05-21
# canonical incident.
TEMPLATE_FILE="infra/k8s/argo/alpha-rl-template.yaml"
if [[ ! -f "$TEMPLATE_FILE" ]]; then
echo "ERROR: template not found at $TEMPLATE_FILE (run from repo root)"
exit 1
fi
if [[ "$SKIP_TEMPLATE_APPLY" == "false" ]]; then
echo "Applying alpha-rl WorkflowTemplate to cluster..."
kubectl apply -n foxhunt -f "$TEMPLATE_FILE" >/dev/null
echo " applied: $TEMPLATE_FILE"
else
echo "WARNING: --skip-template-apply set — argo will use whatever's"
echo " already in the cluster CRD (may be stale)."
fi
# ── Guard 2: feedback_push_before_deploy ─────────────────────────────
# Per the 2026-05-20 incident: cluster pods pull source from origin
# `<BRANCH>`, NOT from the local working tree. Submitting before
# `git push` deploys whatever was last on origin, which can lag the
# local diff by N commits. Verify HEAD == origin/<branch> before
# submission unless explicitly bypassed.
if [[ "$SKIP_PUSH_CHECK" == "false" ]]; then
echo "Verifying local HEAD == origin/$BRANCH (feedback_push_before_deploy)..."
if ! git rev-parse --git-dir >/dev/null 2>&1; then
echo "ERROR: not in a git repo; cannot verify push state"
exit 1
fi
git fetch --quiet origin "$BRANCH" 2>/dev/null || true
LOCAL_HEAD=$(git rev-parse HEAD)
ORIGIN_HEAD=$(git rev-parse "origin/$BRANCH" 2>/dev/null || echo "MISSING")
if [[ "$ORIGIN_HEAD" == "MISSING" ]]; then
echo "ERROR: origin/$BRANCH does not exist — push the branch first:"
echo " git push -u origin $BRANCH"
exit 1
fi
if [[ "$LOCAL_HEAD" != "$ORIGIN_HEAD" ]]; then
echo "ERROR: local HEAD ($LOCAL_HEAD) != origin/$BRANCH ($ORIGIN_HEAD)"
echo " Push first:"
echo " git push origin $BRANCH"
echo " Or override with --skip-push-check if you're knowingly"
echo " deploying a previously-pushed SHA via --sha."
exit 1
fi
echo " HEAD verified: $LOCAL_HEAD == origin/$BRANCH"
fi
# Resolve SHA=HEAD to a concrete SHA before submission so the in-cluster
# check-cache pod doesn't need git access. Mirrors alpha-perception.
if [ "$SHA" = "HEAD" ]; then
SHA=$(git rev-parse "origin/$BRANCH" 2>/dev/null \
|| git rev-parse "$BRANCH" 2>/dev/null \
|| git rev-parse HEAD)
echo "Resolved HEAD → $SHA"
fi
echo ""
echo "Submitting alpha-rl workflow..."
echo " branch: $BRANCH"
echo " sha: $SHA"
echo " gpu-pool: $GPU_POOL (sm_$SM)"
echo " n-steps: $N_STEPS"
echo " seq-len: $SEQ_LEN"
echo " n-backtests: $N_BACKTESTS"
echo " per-capacity: $PER_CAPACITY"
echo " seed: $SEED"
echo " instrument: $INSTRUMENT_MODE"
WATCH_FLAG=""
if [[ "$WATCH" == "true" ]]; then
WATCH_FLAG="--watch"
fi
argo submit -n foxhunt --from=wftmpl/alpha-rl \
-p commit-sha="$SHA" \
-p git-branch="$BRANCH" \
-p cuda-compute-cap="$SM" \
-p gpu-pool="$GPU_POOL" \
-p n-steps="$N_STEPS" \
-p seq-len="$SEQ_LEN" \
-p n-backtests="$N_BACKTESTS" \
-p per-capacity="$PER_CAPACITY" \
-p seed="$SEED" \
-p instrument-mode="$INSTRUMENT_MODE" \
$WATCH_FLAG