Instructions to use XXXpilar/Fastfill-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use XXXpilar/Fastfill-test with PEFT:
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- Notebooks
- Google Colab
- Kaggle
Download code/fastfill/adapters/__init__.py from XXXpilar/Fastfill-test: direct link, hf CLI and curl.
- Browser
- Download file 2.03 kB
-
https://huggingface.co/XXXpilar/Fastfill-test/resolve/main/code/fastfill/adapters/__init__.py
- Command line
-
hf download hf://XXXpilar/Fastfill-test/code/fastfill/adapters/__init__.py
-
curl -L -o __init__.py https://huggingface.co/XXXpilar/Fastfill-test/resolve/main/code/fastfill/adapters/__init__.py
2.03 kB
| """Source adapters: exported dataset files -> IR rooms (see fastfill/scene.py). | |
| Each module in this package defines | |
| SOURCE = "<name>" # output file name <name>.jsonl | |
| def load(root) -> iterable # yields IR room dicts; root = download dir of fastfill.download | |
| python -m fastfill.adapters --root /Volumes/harddisk/3D_Room_Collections --out /Volumes/harddisk/fastfill_ir [--only IL3D] | |
| """ | |
| import argparse | |
| import importlib | |
| import json | |
| import os | |
| import pkgutil | |
| def registry(): | |
| mods = {} | |
| for m in pkgutil.iter_modules(__path__): | |
| if m.name.startswith("_") or m.name == "unified": | |
| continue | |
| mod = importlib.import_module(f"{__name__}.{m.name}") | |
| if hasattr(mod, "SOURCE") and hasattr(mod, "load"): | |
| mods[mod.SOURCE] = mod | |
| return mods | |
| def main(): | |
| ap = argparse.ArgumentParser() | |
| ap.add_argument("--root", required=True) | |
| ap.add_argument("--out", required=True) | |
| ap.add_argument("--only", nargs="*", default=None) | |
| a = ap.parse_args() | |
| os.makedirs(a.out, exist_ok=True) | |
| for name, mod in sorted(registry().items()): | |
| if a.only and name not in a.only: | |
| continue | |
| n = 0 | |
| tmp = f"{a.out}/{name}.jsonl.tmp" | |
| try: | |
| with open(tmp, "w") as f: | |
| for room in mod.load(a.root): | |
| f.write(json.dumps(room, ensure_ascii=False) + "\n") | |
| n += 1 | |
| except FileNotFoundError as e: # dataset not downloaded (or deleted): keep any existing IR file | |
| os.remove(tmp) | |
| print(f"{name}: skipped, input not found: {e.filename}", flush=True) | |
| continue | |
| if n == 0: # an empty input file must not wipe a good IR file | |
| os.remove(tmp) | |
| print(f"{name}: skipped, 0 rooms read; existing IR kept", flush=True) | |
| continue | |
| os.replace(tmp, f"{a.out}/{name}.jsonl") | |
| print(f"{name}: {n} rooms", flush=True) | |
| if __name__ == "__main__": | |
| main() | |