Download code/scripts/01_upload_hf.py from Jyo-K/PopTurk: direct link, hf CLI and curl.
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7.73 kB
| """Upload the payload the Colab lanes need, to Jyo-K/PopTurk. | |
| export HF_TOKEN=hf_... | |
| python scripts/01_upload_hf.py --what code shards models --split test | |
| WHAT GOES UP, AND WHAT DELIBERATELY DOES NOT | |
| code this source tree (~120 KB). The notebook imports berx from it, so there is exactly | |
| one copy of the scoring logic and a fix on the box reaches Colab on the next push. | |
| shards the self-contained cross-encoder work units from 04_make_shards.py. Text included, | |
| so a lane needs nothing else. | |
| models the fine-tuned cross-encoder checkpoints. Weights ONLY - the optimiser state is | |
| 4.5 GB of AdamW moments that inference never reads. | |
| geo the mined administrative-equivalence tables (a few MB). | |
| NOT the embeddings. They are already in the three channel repos and they are 42 GB; a Colab | |
| lane does cross-encoder scoring, which needs no embeddings at all. Anything that pulls them | |
| into a Colab VM has misunderstood the split of work. | |
| NOT the raw dataset in full. The shards already carry the text they need. | |
| PRIVACY. Every repo is created PRIVATE. The competition data is licensed to participants, not | |
| to the public, and a public dataset repo is a redistribution. Passing --public is an explicit | |
| decision to publish; think before you do. | |
| """ | |
| from __future__ import annotations | |
| import argparse | |
| import glob | |
| import os | |
| import re | |
| import shutil | |
| import sys | |
| import tempfile | |
| sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__)))) | |
| from berx import io_hf # noqa: E402 | |
| from berx import paths as P # noqa: E402 | |
| ROOT = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) | |
| # Matches the assignment `HF_TOKEN = "hf_..."` so it can be blanked, and any bare hf_ token | |
| # anywhere else as a backstop. | |
| TOKEN_RE = re.compile(r'^(HF_TOKEN\s*=\s*).*$', re.M) | |
| LEAK_RE = re.compile(r'hf_[A-Za-z0-9]{20,}') | |
| # Backreference to group 1 (the `HF_TOKEN = ` prefix) plus an EMPTY STRING LITERAL. The empty | |
| # literal is not decoration: dropping it leaves `HF_TOKEN =` with no value, which is a | |
| # SyntaxError, and the published code/ tree would fail to import on every Colab lane. | |
| REDACTED = r'\1"" # redacted for upload' | |
| # Inference reads none of these; they are the bulk of a checkpoint directory. | |
| SKIP_IN_MODEL = {"opt.pt", "optimizer.pt", "scheduler.pt", "rng_state.pth", | |
| "trainer_state.json", "training_args.bin"} | |
| def push_code(repo: str, public: bool): | |
| """Upload the source tree, with the embedded token REDACTED. | |
| The token now lives in berx/io_hf.py so it does not have to be exported. That makes this | |
| function the one place it could leak: uploading the tree verbatim would publish the | |
| token inside the very repo it authenticates to. The redaction below is asserted, and the | |
| upload is refused outright if any token-shaped string survives it - a silent failure here | |
| means a live credential in a dataset repo. | |
| """ | |
| tmp = tempfile.mkdtemp() | |
| dst = os.path.join(tmp, "code") | |
| shutil.copytree(os.path.join(ROOT, "berx"), os.path.join(dst, "berx"), | |
| ignore=shutil.ignore_patterns("__pycache__", "*.pyc")) | |
| shutil.copytree(os.path.join(ROOT, "scripts"), os.path.join(dst, "scripts"), | |
| ignore=shutil.ignore_patterns("__pycache__", "*.pyc")) | |
| for f in ("hf_token.txt",): # never ships, whatever else happens | |
| q = os.path.join(dst, f) | |
| if os.path.exists(q): | |
| os.remove(q) | |
| redacted = 0 | |
| for root, _, files in os.walk(dst): | |
| for fn in files: | |
| if not fn.endswith((".py", ".sh", ".md", ".txt", ".json", ".ipynb")): | |
| continue | |
| fp = os.path.join(root, fn) | |
| try: | |
| txt = open(fp, encoding="utf-8").read() | |
| except (UnicodeDecodeError, OSError): | |
| continue | |
| new_txt = TOKEN_RE.sub(REDACTED, txt) | |
| if new_txt != txt: | |
| open(fp, "w", encoding="utf-8").write(new_txt) | |
| redacted += 1 | |
| leak = LEAK_RE.search(new_txt) | |
| assert not leak, ( | |
| f"REFUSING TO UPLOAD: {fp} still contains something token-shaped " | |
| f"({leak.group(0)[:12]}...). Fix the redaction before publishing.") | |
| io_hf.upload(dst, "code", repo, public) | |
| shutil.rmtree(tmp, ignore_errors=True) | |
| print(f" code/ uploaded (token redacted in {redacted} file(s))") | |
| def push_shards(repo: str, split: str, public: bool): | |
| files = sorted(glob.glob(P.work("shards", f"{split}_shard*.parquet"))) | |
| files += glob.glob(P.work("shards", f"{split}_manifest.json")) | |
| assert files, "no shards found - run 04_make_shards.py first" | |
| total = 0 | |
| for f in files: | |
| mb = os.path.getsize(f) / 2 ** 20 | |
| total += mb | |
| io_hf.upload(f, f"shards/{os.path.basename(f)}", repo, public) | |
| print(f" shards/{os.path.basename(f)} {mb:.1f} MB") | |
| print(f" {total:.1f} MB total") | |
| def push_model(repo: str, local: str, name: str, public: bool): | |
| assert os.path.isdir(local), f"not a directory: {local}" | |
| tmp = tempfile.mkdtemp() | |
| dst = os.path.join(tmp, name) | |
| os.makedirs(dst) | |
| kept = 0 | |
| for f in os.listdir(local): | |
| if f in SKIP_IN_MODEL or f == "ckpt": | |
| continue | |
| src = os.path.join(local, f) | |
| if os.path.isfile(src): | |
| shutil.copy2(src, os.path.join(dst, f)) | |
| kept += os.path.getsize(src) | |
| io_hf.upload(dst, f"models/{name}", repo, public) | |
| shutil.rmtree(tmp, ignore_errors=True) | |
| print(f" models/{name} {kept/2**30:.2f} GiB (optimiser state excluded)") | |
| def push_geo(repo: str, public: bool): | |
| for f in glob.glob(P.work("geo", "*.json")): | |
| io_hf.upload(f, f"geo/{os.path.basename(f)}", repo, public) | |
| print(f" geo/{os.path.basename(f)}") | |
| def main(): | |
| ap = argparse.ArgumentParser() | |
| ap.add_argument("--what", nargs="+", required=True, | |
| choices=["code", "shards", "models", "geo", "all"]) | |
| ap.add_argument("--split", default="test") | |
| ap.add_argument("--repo", default=P.PAYLOAD_REPO) | |
| ap.add_argument("--model-dirs", nargs="*", default=[], | |
| help="LOCAL_DIR:NAME pairs, e.g. work/ce_model_A:bge_reranker_ft") | |
| ap.add_argument("--token", default="", help="overrides every other token source") | |
| ap.add_argument("--public", action="store_true", | |
| help="publish instead of keeping the repo private - think first") | |
| a = ap.parse_args() | |
| if a.token: | |
| io_hf.set_token(a.token) | |
| if not io_hf.token(): | |
| sys.exit("No token. Set HF_TOKEN in berx/io_hf.py, or pass --token, or put it in " | |
| "hf_token.txt, or export HF_TOKEN.") | |
| print(f"token from {io_hf.token_source()}") | |
| what = set(a.what) | |
| if "all" in what: | |
| what = {"code", "shards", "models", "geo"} | |
| io_hf.ensure_repo(a.repo, a.public) | |
| print(f"repo {a.repo} ({'PUBLIC' if a.public else 'private'})") | |
| if "code" in what: | |
| push_code(a.repo, a.public) | |
| if "shards" in what: | |
| push_shards(a.repo, a.split, a.public) | |
| if "geo" in what: | |
| push_geo(a.repo, a.public) | |
| if "models" in what: | |
| if not a.model_dirs: | |
| print(" --model-dirs not given; skipping models") | |
| for spec in a.model_dirs: | |
| local, _, name = spec.partition(":") | |
| push_model(a.repo, local, name or os.path.basename(local.rstrip("/")), a.public) | |
| print(f"\nhttps://huggingface.co/datasets/{a.repo}") | |
| if __name__ == "__main__": | |
| main() | |