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run-ferries

marin-community/marin/.agents/skills/run-ferries/SKILL.md

Launch, monitor, or seal a Marin canary or daily ferry only when explicitly requested.

Skill3.9k starsChanged 25 days ago

What's in it

  1. Ferries
  2. Inputs Before Proposing (Daily Only)
  3. Operating Policy
  4. General
  5. Canary
  6. Daily
  7. Workflows
  8. Daily lane (proposal + run)
  9. Canary lane (steady-state run)
  10. Promotion rule
  11. Validation Checklist
---
name: run-ferries
description: Launch, monitor, or seal a Marin canary or daily ferry only when explicitly requested.
---

# Ferries

- `experiments/ferries/canary_ferry.py` (MoE canary, TPU and GPU via `CANARY_ACCELERATOR`)
- `experiments/ferries/daily.py`

Canary is the stable, low-cost health check. Daily exercises a larger envelope
with one or two explicit changes.

Shared baseline:
- data: shared `nemotron_mix` baseline
- default cluster: `us-central1` (zone `us-central1-a`)
- run log: `docs/experiments/daily-ferry-log.md`

Daily defaults to `llama_150m`, sequence length 4096, batch size 512, and about
1e19 FLOPs unless its configuration says otherwise.

## Inputs Before Proposing (Daily Only)
Canary runs normally do not require a proposal cycle or PR. For daily, collect:
1. Last ferry references: issue URL, PR/commit URL, W&B run URL and Iris job ID
2. Human objective for this interval: standard integration pass, or explicit regression investigation
3. Interval boundary: use "since last ferry run", not fixed wall-clock day boundaries

If objective is ambiguous, ask before editing.

## Operating Policy
### General
- Hard launch gate: get explicit requester approval before launching any ferry job. Only exception: the requester explicitly says to launch without asking.
- Follow the `use-iris` skill's job-monitoring workflow until the run reaches a terminal state (`SUCCEEDED`/`FAILED`/`STOPPED`); do not stop early. Full ferry monitoring often takes 4-5 hours.
- Never restart/recreate/mutate cluster without explicit human consent in-thread. Keep cluster mutation guardrails aligned with the Iris monitoring workflow, including the **debug** exception path.
- Use major-event updates (not spam): launch, first eval, major incident, terminal state.
- Seal each completed daily run with a pushed git tag pointing to the exact launch commit.
- Canonical run-closure PR labels: `ferry`, `ferry-daily`, `ferry-log-only`, `ferry-sealed`.
- Canonical seal-tag format (daily): `ferry/daily/YYYYMMDD/<run_slug>`

### Canary
- Keep canary stable; only change it for explicit reliability fixes, and only when diagnosing/fixing a concrete failure mode.
- Canary launches usually do not require a PR if the script/config is unchanged.
- If canary fails, treat as urgent infrastructure/training-health triage.
- Canary is run-only by default (W&B + issue updates); no sealing tag or run-closure PR in the normal path.

### Daily
- Use daily for bounded evolution, usually 1-2 knobs.
- If daily fails, debug with one bounded fix attempt, then escalate.
- Run-closure PR scope is log-only: update `docs/experiments/daily-ferry-log.md`, keep detailed debug/run narrative in the issue.

## Workflows

### Daily lane (proposal + run)

#### 1) Build context since last ferry
Check the latest entries in `docs/experiments/daily-ferry-log.md`.

```bash
LAST_FERRY_SHA=<last_ferry_commit_sha>
LAST_FERRY_DATE=<YYYY-MM-DD>

git log --oneline "${LAST_FERRY_SHA}..HEAD" -- experiments/ lib/ scripts/

gh issue list \
  --label experiment \
  --search "updated:>=${LAST_FERRY_DATE}" \
  --limit 100
```

Treat GitHub-tagged ferry PRs/issues as source of truth. Use "since last ferry run" rather than fixed wall-clock boundaries.

#### 2) Edit `experiments/ferries/daily.py`
- Keep edits bounded (typically 1-2 knobs); propose at least one intentional modification each interval.
- If no obvious change emerges from recent commits/issues/ferry history, pick a low-risk tweak (e.g. data-mix adjustment or hyperparameter change) that may improve loss at the same FLOPs budget.
- Pattern-match from the previous daily ferry; avoid high-churn rewrites.
- Update run naming for this interval (e.g. via `FERRY_DATE` in launch env: `daily-125m-YYYY-MM-DD` style).

#### 3) Record proposal in issue and push launch commit
In the run issue, record:
- last ferry links (issue + commit + W&B/job link),
- exact config delta and rationale,
- risk level (`low`/`medium`/`high`),
- relaunch fallback note,
- why this run is not literally identical to the previous daily run,
- launch checklist (explicit requester approval or explicit waiver + monitoring started).

Then push the launch commit (no proposal PR by default).

#### 4) Launch
Confirm requester approval in-thread unless they already gave explicit "launch without asking" permission.

```bash
uv run iris --cluster=marin job run --no-wait --cpu=1 --memory=2G --extra=cpu \
  -- python -m experiments.ferries.daily
```

After launch, capture and post to the issue:
- Iris job id (printed by `iris job run`, form `/<user>/iris-run-job-YYYYMMDD-HHMMSS`)
- cluster
- launch timestamp
- W&B link(s) when available

Optional deterministic daily rerun name:
```bash
uv run iris --cluster=marin job run --no-wait --cpu=1 --memory=2G --extra=cpu \
  -e FERRY_DATE "$(date +%Y%m%d-%H%M%S)-daily-ferry" \
  -- python -m experiments.ferries.daily
```

#### 5) Monitor to terminal state
Follow the `use-iris` skill's job-monitoring workflow with `job_id`, `cluster`, `experiment=<ferry script path>`.
- Keep the monitoring loop active until terminal status; ferry runs commonly take 4-5 hours.
- Follow monitoring-loop restart policy for recoverable failures.
- Escalate non-trivial failures to humans.

#### 6) Close the loop
Post in the ferry issue: final status, key metrics/regressions, Iris job ID and W&B link(s), recommendation for next ferry. Optional: post a manual Discord update for major run state changes.

For daily-log metric fields, extract canonical final keys with:

```bash
uv run python scripts/ferries/daily_analysis.py \
  --run <wandb_run_url_or_path> \
  --format markdown
```

Use this terminal issue comment shape:

```markdown
Final status: <SUCCEEDED|FAILED|STOPPED>
Iris job id: <job_id>
W&B link: <url>
Final eval summary: <key metrics>
Experiment link: <experiment JSON/browser link>
Recommendation / victory decision: <next action>
```

#### 7) Seal and open log-only PR
- Create and push a sealing tag for the exact launch commit (the commit containing the `experiments/ferries/daily.py` used for the run).
- Open a PR that updates only `docs/experiments/daily-ferry-log.md`, following
  `.agents/skills/commit/SKILL.md` for commit, PR text, and monitoring.
- Keep all detailed launch/retry/debug narrative in the run issue, not in the PR.
- Apply canonical labels: `ferry`, `ferry-daily`, `ferry-log-only`, `ferry-sealed`.

### Canary lane (steady-state run)
Default mode: launch the existing canary script as-is and monitor. Do not run the daily proposal/PR loop unless intentionally changing canary. Even for unchanged runs, ask the requester before launch unless they explicitly waived that requirement.

Launch (TPU):
```bash
uv run iris --config=lib/iris/config/marin.yaml \
  job run --memory=16G --disk=16G --cpu=1 --extra=tpu \
  -- python -m experiments.ferries.canary_ferry
```

Launch (GPU / CoreWeave):
```bash
uv run iris --cluster=cw-us-east-02a \
  job run --memory=16G --disk=16G --cpu=1 --extra=cpu \
  -e MARIN_PREFIX s3://marin-na/marin \
  -e CANARY_ACCELERATOR gpu \
  -- python -m experiments.ferries.canary_ferry
```

If canary fails: triage and identify root cause, only then open a focused PR if a canary script/config change is necessary, relaunch and monitor to terminal state.

#### Canary profiling triage
- The full `profile_summary.json` is in the workflow logs (default params: `--warmup-steps 5`, `--breakdown-mode exclusive_per_track`, `--hot-op-limit 25`). The step summary has pointers to the raw trace artifact and W&B run.
- The log summary is ephemeral and not published. To re-analyze with different parameters, fetch the raw trace via `--run-target` — see `.agents/skills/profile-training/SKILL.md`.
- If the canary failed early, the profile may only cover warmup steps — check `step_time.all_steps.count` before drawing conclusions from steady-state stats.
- `exclusive_per_track` (the default) can hide device stalls that overlap across tracks. Use `exclusive_global` when investigating stall-heavy profiles.

## Promotion rule

Promote a daily variant only when eval losses and aggregate LM metrics improve
without a reliability regression. Open a follow-up PR for the recipe and this
skill with a before/after metrics table.

## Validation Checklist
- Diff is intentional and bounded for the selected lane.
- If daily was edited, launch commit is pushed and referenced in the run issue.
- Run-closure PR only updates `docs/experiments/daily-ferry-log.md`.
- Ferry issue has updated launch metadata.
- Monitoring loop ran until terminal state.

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