Run an explicitly requested Zephyr control/treatment benchmark on the same pre-normalized sample and compare Finelog stage metrics.
日本語の概要は準備中です。原文の説明を表示しています。
Deploy a significant code change (backend, kernel, optimizer, data path) to the live hero run: relaunch it under a new run id from a permanent checkpoint, compare against the old run over a trial window, and roll back if the gate fails; use only when the user asks to deploy a change to the hero.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Use manage-hero-run for the run record, DRI, retention, and babysitting. This
checklist governs a code cutover and its trial. Single-rack validation does not
exercise cross-domain collectives or checkpoint recovery at production scale.
Record the following with the user before changing the live run:
step-N. Use the newest scheduled
permanent checkpoint (every 6000 steps, about 26 hours at the hero's pace), or
request one from the old run's training-control endpoint with the
request-permanent-checkpoint header value. Only a run whose code includes
that action can take the request; otherwise schedule the cutover shortly after
a scheduled permanent checkpoint. Do not hand off from a temporary checkpoint:
it expires three days after it is written.Land the code change and finalized trigger_hero.sh values on main before
cutover. Use a pristine checkout at the verified SHA. The launcher records the
new run, retained checkpoint, and W&B fork boundary; its commands and recovery
semantics are documented in the linked launcher procedure.
Inventory downstream reports and trackers that pin the run ID or affected metric keys. Update their selection as part of accepting the child.
Use small scripts whose queries fail closed on errors or unrecognized output. Dry-run every guard against the live cluster and obtain an independent review.
Verify:
metadata.json exists, records the expected step, and has the intended
retention. Confirm layout and checkpoint lineage.IRIS_USER=marin. Verify its intended resume
checkpoint first. Never create another W&B fork for rollback.hero-checkpoints
in US-EAST-08A (100 TiB quota); permanent checkpoints go to
marin-us-east-02a in US-EAST-02A, whose quota all Marin work shares. At
quota CoreWeave suspends writes for the whole zone, and the hero's next save
hangs without an error (#8506, 2026-09-23).
Require five checkpoints of free space in 08A (about 21 TB at 4.29 TB each):
the old run's newest temporary checkpoint, a restore-smoke copy, the child's
temporary checkpoint plus the next one being written (the older is pruned only
after the newer commits), and one spare. Require two checkpoints plus a day of
recent growth in 02A for the handoff and the child's next permanent
checkpoint. Read usage and quota from the Finelog storage.usage namespace;
the collector runs every few hours, so if the newest collected_at is more
than an hour old, get current values with
python -m scripts.ops.storage.coreweave_usage --dry-run.Distinguish a successful query with no matching jobs from a failed query. Parse
Iris CSV headers and CRLF correctly; do not interpret grep -c exit status as a
query result. Match pods by task identity because Kubernetes names are sanitized
and truncated. Confirm restore from Loading checkpoint from and entry into the
training loop.
IRIS_USER=marin.N (steps N through N+199), plus wider context. Include loss,
cross entropy, MFU, step time/tokens per second, drops, routing entropy, router
losses, gradient norm, and peak memory. Share the URL.The trial gate overrides manage-hero-run's ordinary retry policy. On a failed
gate, unexplained hang, or retry loop, cancel the child coordinator and roll back
without waiting for further attempts. Retries may restore either the handoff or
a newer child checkpoint; neither substitutes for a successful trial.
Go: leave the child running, publish the comparison and coverage gaps, update the
status issue and downstream reporting, and resume ordinary recovery policy.
The old run's leftover temporary checkpoints expire on their own within three
days, or 14 if its launcher predates the three-day TTL. Delete any restore-smoke
copy once it has served its purpose, deleting metadata.json first so a partial
directory never looks complete.
After rollback, compare the old run's first replayed steps with its earlier trajectory. This checks trajectory consistency, not bitwise determinism. Its W&B history may not advance until it passes the old counter, so verify progress in Finelog. Update the status issue and file the failure with supporting evidence.
For collective stalls, use silent-hang diagnostics.
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Run an explicitly requested Zephyr control/treatment benchmark on the same pre-normalized sample and compare Finelog stage metrics.
日本語の概要は準備中です。原文の説明を表示しています。
Register a named Hugging Face dataset for Marin by inspecting its schema and adding the appropriate experiments/datasets module.
日本語の概要は準備中です。原文の説明を表示しています。
Implement a fully specified request for a GCP IAM resource grant or Cloud Run IAP viewer in marin-iac.
日本語の概要は準備中です。原文の説明を表示しています。
Add or change a named Pallas/Mosaic kernel, including its reference implementation, correctness tests, wrapper, or requested tuning.
日本語の概要は準備中です。原文の説明を表示しています。
Archive explicitly named legacy experiment files by publishing a dated tag and canonical issue breadcrumbs.
日本語の概要は準備中です。原文の説明を表示しています。
Launch or continuously monitor a specified Zephyr pipeline on Iris only when asked to babysit it; restart only after explicit approval.
日本語の概要は準備中です。原文の説明を表示しています。