Download code/berx/io_hf.py from Jyo-K/PopTurk: direct link, hf CLI and curl.
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https://huggingface.co/datasets/Jyo-K/PopTurk/resolve/main/code/berx/io_hf.py
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4.98 kB
| """Hugging Face transport for the payload repo. | |
| WHY A PAYLOAD REPO. Colab cannot see the college box and the college box cannot push into a | |
| Colab VM. Everything both sides need therefore has to live somewhere both can reach. The three | |
| embedding repos already exist; this module manages a fourth repo that carries the *small* | |
| things: raw text, candidate shards, model checkpoints and this source tree. | |
| PRIVACY. The competition data is licensed to participants, not to the public. Every upload | |
| here defaults to a PRIVATE repo and `ensure_repo` will refuse to create a public one unless | |
| `public=True` is passed explicitly. Do not change that default. | |
| """ | |
| from __future__ import annotations | |
| import os | |
| import sys | |
| # ---------------------------------------------------------------- credentials | |
| # Put your token here so nothing has to be exported before every command. | |
| # | |
| # HF_TOKEN = "hf_PASTE_YOURS" | |
| # | |
| # (That example is deliberately too short to match the leak detector below. A realistic | |
| # dummy in a comment would trip the guard and refuse every upload.) | |
| # | |
| # TWO THINGS THIS FILE DOES TO KEEP THAT SAFE, because a token written into source is one | |
| # copy away from being published: | |
| # 1. `push_code` REDACTS this constant before uploading the source tree to the payload | |
| # repo. Without that, the first `--what code` upload would publish your token inside | |
| # the very dataset repo it authenticates to. The redaction is asserted, not assumed. | |
| # 2. `token_source()` reports where the token came from, so a surprising one is visible. | |
| # | |
| # It is still a secret in a file on a box 26 other people can log into. Prefer | |
| # `--token` or the environment if you ever share this directory, and rotate it when the | |
| # competition is over. | |
| HF_TOKEN = "" # redacted for upload | |
| _TOKEN_ENV = ("HF_TOKEN", "HUGGING_FACE_HUB_TOKEN", "HUGGINGFACE_TOKEN") | |
| _TOKEN_FILE = os.path.join(os.path.dirname(os.path.dirname(os.path.abspath(__file__))), | |
| "hf_token.txt") | |
| _OVERRIDE: str | None = None | |
| def set_token(tok: str) -> None: | |
| """Used by --token, which beats every other source.""" | |
| global _OVERRIDE | |
| _OVERRIDE = tok.strip() or None | |
| def token() -> str | None: | |
| if _OVERRIDE: | |
| return _OVERRIDE | |
| if HF_TOKEN.strip(): | |
| return HF_TOKEN.strip() | |
| if os.path.exists(_TOKEN_FILE): | |
| v = open(_TOKEN_FILE, encoding="utf-8").read().strip() | |
| if v: | |
| return v | |
| for k in _TOKEN_ENV: | |
| v = os.environ.get(k) | |
| if v: | |
| return v | |
| return None | |
| def token_source() -> str: | |
| if _OVERRIDE: | |
| return "--token" | |
| if HF_TOKEN.strip(): | |
| return "berx/io_hf.py:HF_TOKEN" | |
| if os.path.exists(_TOKEN_FILE) and open(_TOKEN_FILE, encoding="utf-8").read().strip(): | |
| return _TOKEN_FILE | |
| for k in _TOKEN_ENV: | |
| if os.environ.get(k): | |
| return f"${k}" | |
| return "none" | |
| def _api(): | |
| from huggingface_hub import HfApi | |
| return HfApi(token=token()) | |
| def ensure_repo(repo_id: str, public: bool = False) -> str: | |
| """Create the dataset repo if it does not exist. Private unless asked otherwise.""" | |
| from huggingface_hub.utils import HfHubHTTPError | |
| api = _api() | |
| try: | |
| api.create_repo(repo_id, repo_type="dataset", private=not public, exist_ok=True) | |
| except HfHubHTTPError as e: # already exists under another owner, etc. | |
| print(f" create_repo: {e}", file=sys.stderr) | |
| return repo_id | |
| def upload(local_path: str, path_in_repo: str, repo_id: str, public: bool = False) -> str: | |
| """Upload one file or one directory. Returns the path in the repo.""" | |
| ensure_repo(repo_id, public) | |
| api = _api() | |
| if os.path.isdir(local_path): | |
| api.upload_folder(folder_path=local_path, path_in_repo=path_in_repo, | |
| repo_id=repo_id, repo_type="dataset") | |
| else: | |
| api.upload_file(path_or_fileobj=local_path, path_in_repo=path_in_repo, | |
| repo_id=repo_id, repo_type="dataset") | |
| return path_in_repo | |
| def fetch(path_in_repo: str, repo_id: str, local_dir: str | None = None) -> str: | |
| """Download one file from the payload repo and return its local path.""" | |
| from huggingface_hub import hf_hub_download | |
| return hf_hub_download(repo_id=repo_id, filename=path_in_repo, repo_type="dataset", | |
| local_dir=local_dir, token=token()) | |
| def fetch_dir(repo_id: str, allow: list[str] | None = None, | |
| local_dir: str | None = None) -> str: | |
| """Download a subset of a repo. `allow` is a list of glob patterns. | |
| Always pass `allow`. The embedding repos hold tens of gigabytes and a bare | |
| snapshot_download of one of them will fill a Colab disk before it finishes. | |
| """ | |
| from huggingface_hub import snapshot_download | |
| return snapshot_download(repo_id=repo_id, repo_type="dataset", allow_patterns=allow, | |
| local_dir=local_dir, token=token(), | |
| max_workers=8) | |