File size: 3,226 Bytes
4949db9 | 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 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 | import hashlib
import json
import sys
from pathlib import Path
sys.path.insert(0, str(Path(__file__).resolve().parent.parent.parent))
from human_eval.config import COMPARISON_MODELS, STATUS_SKIPPED
GENERAL_KEYS = ["SA", "PTV", "persistence"]
def compute_import_hash(video_data_dir: Path) -> str:
"""Global hash across all datasets (used by initial import guard)."""
paths = sorted(str(p.relative_to(video_data_dir)) for p in video_data_dir.rglob("*.mp4"))
return hashlib.md5("\n".join(paths).encode()).hexdigest()
def compute_dataset_hash(dataset_dir: Path) -> str:
"""Per-dataset hash — only includes mp4 filenames within one dataset."""
paths = sorted(p.name for p in dataset_dir.glob("*.mp4"))
return hashlib.md5("\n".join(paths).encode()).hexdigest()
def compute_difficulty_score(gemini_scores: dict, qwen_scores: dict) -> float | None:
diffs = []
for key in GENERAL_KEYS:
g, q = gemini_scores.get(key), qwen_scores.get(key)
if g is None or q is None:
return None
diffs.append(abs(g - q))
return sum(diffs) / len(diffs) if diffs else None
def _load_latest_eval(dataset_dir: Path, prefix: str) -> dict | None:
files = sorted(dataset_dir.glob(f"eval_{prefix}_*.json"))
if not files:
return None
with open(files[-1]) as f:
return json.load(f)
def _build_scores_lookup(eval_data: dict | None) -> dict:
if not eval_data or "results" not in eval_data:
return {}
lookup = {}
for r in eval_data["results"]:
scores = {k: r[k] for k in GENERAL_KEYS if k in r}
lookup[r["video"]] = scores
return lookup
_DATASET_SUFFIXES = ("openvid", "video_phy_2", "physics_iq", "wmb")
def _ds_suffix(db_dataset: str) -> str:
"""Extract source dataset suffix from DB dataset name, e.g. 'veo-3.1-video_phy_2' -> 'video_phy_2'."""
for suffix in _DATASET_SUFFIXES:
if db_dataset.endswith(suffix):
return suffix
return db_dataset
class _EvalLookupCache:
"""Caches per-dataset eval score lookups and dataset hashes."""
def __init__(self):
self._eval: dict[str, tuple[dict, dict]] = {}
self._hash: dict[str, str] = {}
def get_scores(self, ds_name: str, ds_dir: Path) -> tuple[dict, dict]:
if ds_name not in self._eval:
self._eval[ds_name] = (
_build_scores_lookup(_load_latest_eval(ds_dir, "gemini")),
_build_scores_lookup(_load_latest_eval(ds_dir, "qwen")),
)
return self._eval[ds_name]
def get_hash(self, ds_name: str, ds_dir: Path) -> str:
if ds_name not in self._hash:
self._hash[ds_name] = compute_dataset_hash(ds_dir) if ds_dir.exists() else ""
return self._hash[ds_name]
def import_videos(conn, video_data_dir: Path):
"""Import videos into the human-eval DB.
This release omits the prompt-selection JSON consumed by the original
importer, so the importer entry point is intentionally disabled.
"""
raise RuntimeError(
"import_videos is not included in this release because the prompt-selection "
"JSON is omitted. Use the companion dataset metadata to build a DB import."
)
|