| """Push the locally-prepared data inputs (sentences + voices + phoneme LM + CMUdict cache) |
| to a HuggingFace dataset repo so the Colab notebook can `snapshot_download` them in Cell 2. |
| |
| Default target: akshan-main/glossolalia-inputs (override via --repo). |
| """ |
|
|
| import argparse |
| import sys |
| from pathlib import Path |
|
|
|
|
| def main(): |
| p = argparse.ArgumentParser() |
| p.add_argument("--src", default="data", help="local dir with sentences.txt, voices/, phoneme_lm.npz, cmudict.dict") |
| p.add_argument("--repo", default="akshan-main/glossolalia-inputs") |
| p.add_argument("--private", action="store_true") |
| args = p.parse_args() |
|
|
| src = Path(args.src) |
| required = ["sentences.txt", "phoneme_lm.npz", "voices"] |
| missing = [r for r in required if not (src / r).exists()] |
| if missing: |
| print(f"ERROR: missing in {src}: {missing}", file=sys.stderr); sys.exit(1) |
|
|
| from huggingface_hub import HfApi |
| api = HfApi() |
| api.create_repo(args.repo, repo_type="dataset", private=args.private, exist_ok=True) |
| print(f"uploading {src} -> dataset {args.repo} (private={args.private})", file=sys.stderr) |
| api.upload_folder( |
| folder_path=str(src), |
| repo_id=args.repo, |
| repo_type="dataset", |
| allow_patterns=["sentences.txt", "phoneme_lm.npz", "cmudict.dict", |
| "voices/*.wav", "voices/*.txt"], |
| ) |
| print(f"DONE: https://huggingface.co/datasets/{args.repo}") |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|
