File size: 1,415 Bytes
1ca0407 dbd06d6 1ca0407 dbd06d6 1ca0407 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 | """Grade an answer for a row of the flat dataset, with no Docker and no LLM.
from grade import grade
reward, details = grade(row, answer_dict)
`row` is a dataset row (needs `family` and `instance`); `answer_dict` is the parsed JSON answer.
Construct tasks return 1.0 for any valid witness, else 0.0. Optimize tasks return 0 if invalid,
otherwise 0.1 + 0.9 * progress from a trivial baseline to the best known value (see graders/run.py).
Requires python>=3.10 with numpy, scipy, sympy, networkx.
"""
import importlib.util
import json
import os
import sys
from pathlib import Path
_HERE = Path(os.path.abspath(__file__)).parent / "graders" # abspath, not resolve(): HF cache files are symlinks
_cache = {}
def _load(name, path):
spec = importlib.util.spec_from_file_location(name, path)
mod = importlib.util.module_from_spec(spec)
sys.modules[name] = mod
spec.loader.exec_module(mod)
return mod
def _check_fn(family):
if family not in _cache:
if "run" not in sys.modules:
_load("run", _HERE / "run.py")
_cache[family] = _load(f"check_{family}", _HERE / family / "check.py").check
return _cache[family]
def grade(row, answer):
inst = row["instance"]
if isinstance(inst, str):
inst = json.loads(inst)
run = sys.modules.get("run") or _load("run", _HERE / "run.py")
return run.grade(inst, answer, _check_fn(row["family"]))
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