translation-runner / Jobs /submit.py
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Install exact Transformers runtime dependencies before translation
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"""Submit the reviewed translation Job without hard-coding a moving runner SHA.
This launcher is run by an operator with access to the ``hf-doc-build``
namespace. It resolves the current immutable commit of the public runner
dataset, then uses that same SHA for an in-Job snapshot download and the
``RUNNER_REVISION`` manifest field.
"""
from __future__ import annotations
import argparse
import json
import os
import re
from typing import Any
RUNNER_REPOSITORY = "hf-doc-build/translation-runner"
MODEL_REPOSITORY = "google/translategemma-27b-it"
MODEL_REVISION = "7d10f0b72f89a2d0f268cea30727d8b77c0d25c2"
DOC_BUILDER_REVISION = "e60a538eea9817ab312196d0d233604b01697265"
IMAGE = "huggingface/transformers-pytorch-gpu:latest"
NAMESPACE = "hf-doc-build"
RUNNER_LOCAL_DIR = "/tmp/translation-runner"
CONFIG_PATH = f"{RUNNER_LOCAL_DIR}/configs/transformers-ja-job.yml"
BOOTSTRAP = """\
import json
import os
from pathlib import Path
import subprocess
import sys
subprocess.run(
[
sys.executable,
"-m",
"pip",
"install",
"--disable-pip-version-check",
"--no-cache-dir",
"--upgrade",
"huggingface-hub==1.8.0",
"wheel>=0.38",
],
check=True,
)
from huggingface_hub import snapshot_download
revision = os.environ["RUNNER_REVISION"]
runner = Path(
snapshot_download(
repo_id="hf-doc-build/translation-runner",
repo_type="dataset",
revision=revision,
local_dir="/tmp/translation-runner",
cache_dir="/tmp/runner-download-cache",
force_download=True,
)
)
config_path = runner / "configs" / "transformers-ja-job.yml"
if not config_path.is_file():
raise RuntimeError(f"runner snapshot is incomplete: {config_path}")
runner_arguments = json.loads(os.environ["RUNNER_ARGUMENTS"])
if not isinstance(runner_arguments, list) or not all(isinstance(item, str) for item in runner_arguments):
raise RuntimeError("RUNNER_ARGUMENTS must be a JSON array of strings")
environment = os.environ.copy()
runner_src = str(runner / "src")
existing_pythonpath = environment.get("PYTHONPATH")
environment["PYTHONPATH"] = os.pathsep.join(
value for value in (runner_src, existing_pythonpath) if value
)
command = ["python3", "-m", "hf_doc_translation.sync", *runner_arguments]
os.execvpe(command[0], command, environment)
"""
def _runner_revision(api: Any) -> str:
revision = str(api.dataset_info(RUNNER_REPOSITORY).sha or "")
if not re.fullmatch(r"[0-9a-f]{40}", revision):
raise RuntimeError(f"Hub did not return an immutable runner revision: {revision!r}")
return revision
def _volumes(Volume: Any) -> list[Any]:
return [
Volume(type="model", source=MODEL_REPOSITORY, mount_path="/model", revision=MODEL_REVISION, read_only=True),
Volume(type="bucket", source="hf-doc-build/doc-translation-cache", mount_path="/translation-cache"),
Volume(
type="bucket",
source="hf-doc-build/doc-build-cache",
mount_path="/doc-build-cache",
read_only=True,
),
]
def _common_args() -> list[str]:
return [
"--config",
CONFIG_PATH,
"--repository",
"stevhliu/transformers",
"--base-ref",
"ja-translation",
"--environment",
"staging",
"--model-path",
"/model",
"--cache-dir",
"/translation-cache",
"--runner-revision",
"{runner_revision}",
]
def _command_arguments(mode: str, runner_revision: str) -> list[str]:
arguments = ["smoke-batching"] if mode == "smoke" else []
arguments.extend(value.format(runner_revision=runner_revision) for value in _common_args())
if mode == "backfill":
arguments.append("--force-backfill")
return arguments
def _github_secrets(mode: str) -> dict[str, str] | None:
"""Read the GitHub credential only from the submitter's environment."""
if mode not in {"backfill", "schedule"}:
return None
token = os.environ.get("GITHUB_TOKEN") or os.environ.get("GH_TOKEN")
if not token:
raise RuntimeError(
"publishing requires GITHUB_TOKEN or GH_TOKEN in the local environment; "
"the value is passed encrypted to the Job and is never read from the repository"
)
return {"GITHUB_TOKEN": token}
def _status_json(job: Any) -> dict[str, str | None] | None:
status = getattr(job, "status", None)
if status is None:
return None
stage = getattr(status, "stage", None)
return {
"stage": getattr(stage, "value", str(stage)) if stage is not None else None,
"message": getattr(status, "message", None),
}
def submit(mode: str, soak_complete: bool = False) -> dict[str, Any]:
from huggingface_hub import HfApi, Volume
if mode == "schedule" and not soak_complete:
raise RuntimeError("refusing to enable the daily schedule before the 30-day staging soak is complete")
api = HfApi()
runner_revision = _runner_revision(api)
command_mode = "backfill" if mode in {"backfill", "schedule"} else "smoke"
runner_arguments = _command_arguments(command_mode, runner_revision)
environment = {
"RUNNER_REVISION": runner_revision,
"RUNNER_ARGUMENTS": json.dumps(runner_arguments),
"TRANSLATEGEMMA_REVISION": MODEL_REVISION,
"DOC_BUILDER_REVISION": DOC_BUILDER_REVISION,
}
secrets = _github_secrets(mode)
kwargs = {
"image": IMAGE,
"command": ["python3", "-c", BOOTSTRAP],
"env": environment,
"secrets": secrets,
"flavor": "a100-large",
"timeout": "12h" if command_mode == "backfill" else "2h",
"labels": {"purpose": "transformers-ja-doc-sync", "environment": "staging"},
"volumes": _volumes(Volume),
"namespace": NAMESPACE,
}
job = api.create_scheduled_job(schedule="@daily", suspend=False, concurrency=False, **kwargs) if mode == "schedule" else api.run_job(**kwargs)
return {
"mode": mode,
"runner_revision": runner_revision,
"job_id": getattr(job, "id", None),
"job_url": getattr(job, "url", None),
"status": _status_json(job),
}
def main() -> int:
parser = argparse.ArgumentParser()
parser.add_argument("mode", choices=("smoke", "backfill", "schedule"))
parser.add_argument(
"--soak-complete",
action="store_true",
help="required safety acknowledgement before enabling the daily schedule",
)
args = parser.parse_args()
try:
result = submit(args.mode, soak_complete=args.soak_complete)
except RuntimeError as exc:
parser.error(str(exc))
print(json.dumps(result, indent=2, sort_keys=True))
return 0
if __name__ == "__main__":
raise SystemExit(main())