📦 deps(thirdparty): update snapshots
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# Platform Profile Schema
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Every `profiles/<platform>.md` describes ONE platform with the **same 8 sections in the same order**, so
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they are scannable and diffable. A profile owns all the *slow-changing, per-platform* substrate that the
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SKILL.md phases delegate to. It does **not** describe a specific job (that's the portable job request,
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below) and never repeats the universal gotchas (those live in `references/gotchas_universal.md` — link,
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don't restate).
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Design rule borrowed from SkyPilot / dstack / Ray: **hardware is a CONSTRAINT, not a SKU.** A job asks
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for `gpu: A100:8`; the profile owns how that maps to this platform's instance types. **Secrets are
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referenced by env-var NAME or file path only — never inline a key**.
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---
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## Required structure of `profiles/<platform>.md`
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Start each profile with a compact frontmatter block (the machine-readable facts), then the 8 prose
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sections.
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```yaml
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---
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platform: <name> # e.g. runpod
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kind: ssh-rental # ssh-rental | cloud-api | kubernetes | slurm
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meter_stop_verb: terminate # the action that STOPS billing (stop | terminate | destroy | release | 关机 | manual)
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meter_stop_irreversible: true
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detach_primitive: tmux # tmux | sbatch | k8s-job | nohup | kaggle-commit
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spot_available: true
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spot_grace: ~5s # SIGTERM→SIGKILL window, or n/a
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shared_fs: false # is there a cross-instance shared filesystem?
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inode_cap: none # ~200K | none | host-dependent
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free_egress: true # download/upload to the wire free?
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china_mirror_needed: false # does it sit behind the GFW?
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host_driver_cuda_max: "12.x"
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local_nvme: true
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---
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```
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### 1. LAUNCH
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Entry points (web console / CLI / REST API / SSH), the canonical create command, and the **env
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contract** — what IS the Python env (prebuilt base? a Docker image you choose? Lambda Stack?). State the
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rule "the image/base IS the env — do not `conda create` on a rental" if it applies.
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### 2. STORAGE MODEL *(the survival matrix — principle #4)*
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List every storage tier with its path, speed, and size/inode cap. Then a **survival matrix**:
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| Tier | Path | Survives STOP? | Survives DESTROY? | Cap |
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|---|---|---|---|---|
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State region/DC-lock for any shared/network volume. Name the mount checkpoints MUST go to for the
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teardown verb in §5.
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### 3. NETWORK
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Egress/proxy story, China-mirror relevance (link `references/china-network.md` if applicable), how
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ports/services are exposed (TB/Jupyter), and the **SSH flavor(s)** — note if proxied/basic SSH cannot
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`scp`/`rsync` (then direct-TCP is required) and whether ports change on restart.
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### 4. SPOT / INTERRUPTION + RESUME *(principle #7/#8)*
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The interruption model (spot bid? capacity? auto-shutdown clock? auto-release?), the **detection signal +
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grace window**, and the resume hook. Link `references/spot-resilience.md` for the cadence formula.
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### 5. TEARDOWN / BILLING *(principle #9 + the Iron Law)*
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Exactly **what stops the meter** (stop vs terminate vs destroy vs 关机), what each preserves, what is
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**irreversible**, and the cost trap (e.g. "stop still bills storage 2×"). This is the most error-prone
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section — be precise.
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### 6. DAEMON TOOL
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The detach primitive (`tmux` / `sbatch` / Job manifest / commit), whether it survives an instance restart
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(not just an SSH drop), and any native queue/scheduler. Note if `tmux` must be `apt install`-ed or is
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absent (use `nohup … </dev/null >log 2>&1 &`).
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### 7. TOP GOTCHAS (4–8, platform-pinned)
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Only the *platform-specific* ones, Symptom → Root cause → Fix. Universal gotchas are referenced, not
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repeated. Give each a stable local id (e.g. `RP1`, `VAST2`).
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### 8. SCRIPT OVERRIDES
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The exact values to parameterize the `scripts/` templates for this platform:
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`DATA_DIR=` (fast scratch) · `DURABLE_DIR=` (survives teardown) · `PROXY_HOOK=` · `CRED_FILE=` (file path; `""` if the key is an env var/secret) · `SCRATCH=` (what to prune) · `HF_HOME=` · `DETACH=`.
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The templates read exactly these env-var names. Two further knobs *derive* rather than being set per
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platform: `RUN_ONE` (the queue runner's path to `run_one.sh`) defaults to `$DURABLE_DIR/run_one.sh`, and
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`PROJECT_REPO_DIR` (where *this run's* code lives) is a per-run value — see "Portable job request" below;
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set either explicitly only if your layout differs.
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---
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## Portable job request (NOT in the profile — keep it per-run)
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A job is described separately so the *same* job runs against any profile. Document it in
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`references/parallel_ablation.md`; the shape:
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```yaml
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resources:
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gpu: {name: A100, count: 8, memory: 40GB+} # a CONSTRAINT (ranges ok), never a platform SKU
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disk: 200GB
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candidates: [autodl, china, runpod] # ordered fallback → "describe once, run anywhere"
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file_mounts: {/data: {source: ..., mode: MOUNT_CACHED}} # MOUNT | COPY | MOUNT_CACHED
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run: "bash run_queue.sh queue.txt"
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```
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The launcher resolves a job against a profile; the profile supplies paths/verbs, the job supplies
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the work. Keeping them separate is what makes a profile reusable across every job.
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