AntonioJun/workspace
Spatial Code VSI-Bench Workspace This workspace evaluates VSI-Bench question answering with several input regimes: raw video frames, perceived spatial codes from SAM3 + Depth Anything 3 caches, ground-truth spatial codes from dataset annotations, and a deterministic symbolic solver. The code is organized so important outputs are reproducible from fixed inputs, fixed packages, fixed model checkpoints, and fixed SAM3/DA3 caches. The repository intentionally separates three… See the full description on the dataset page: https://huggingface.co/datasets/AntonioJun/workspace.
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1"""Load a complete geometric hypothesis from a filename containing spaces."""2 3from __future__ import annotations4 5import importlib.util6from pathlib import Path7import re8from types import ModuleType9 10from experiments import config11 12REQUIRED_CALLABLES = ("build_spatial_code", "dump_spatial_code")13 14 15def load_hypothesis(name: str) -> ModuleType:16 path = config.hypothesis_path(name)17 if not path.is_file():18 raise FileNotFoundError(f"hypothesis does not exist: {path}")19 safe_name = re.sub(r"\W+", "_", path.stem).strip("_")20 spec = importlib.util.spec_from_file_location(21 f"experiments.hypotheses.{safe_name}", path22 )23 if spec is None or spec.loader is None:24 raise ImportError(f"cannot load hypothesis: {path}")25 module = importlib.util.module_from_spec(spec)26 spec.loader.exec_module(module)27 missing = [28 name for name in REQUIRED_CALLABLES if not callable(getattr(module, name, None))29 ]30 if missing:31 raise AttributeError(32 f"{path.name} is missing callable(s): {', '.join(missing)}"33 )34 return module35 36 37def list_hypotheses() -> list[str]:38 return sorted(39 path.stem40 for path in config.HYPOTHESES_ROOT.glob("*.py")41 if path.name != "__init__.py"42 )43