File size: 11,650 Bytes
53c10a4 | 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 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 | from __future__ import annotations
import importlib.util
import json
import sys
from pathlib import Path
import pytest
RELEASE_ROOT = Path(__file__).resolve().parents[1]
SCRIPT_PATH = RELEASE_ROOT / "scripts" / "create_eval_source_manifest.py"
SPEC = importlib.util.spec_from_file_location("orarl_eval_source_discovery", SCRIPT_PATH)
assert SPEC is not None and SPEC.loader is not None
DISCOVERY = importlib.util.module_from_spec(SPEC)
sys.modules[SPEC.name] = DISCOVERY
SPEC.loader.exec_module(DISCOVERY)
def _write(path: Path, content: str = "[]\n") -> Path:
path.parent.mkdir(parents=True, exist_ok=True)
path.write_text(content, encoding="utf-8")
return path
def _fixture_roots(tmp_path: Path) -> tuple[Path, Path]:
data_root = tmp_path / "licensed-data"
runtime_root = tmp_path / "runtime"
valid_data = runtime_root / "eval" / "data" / "valid_data"
valid_data.mkdir(parents=True)
for folder in (
"Video-MME",
"Video-MME-v2",
"MVBench",
"MMVU",
"Video-Holmes",
"LongVideoBench",
"MLVU",
"VSI-Bench",
"MMSI-Bench",
"MindCube-Tiny",
"ReVSI",
"Spatial-Grounding",
"OneThinker-eval",
"TimeLens-Bench",
"preprocessed_videos",
"qvhighlights-videos",
):
(data_root / folder).mkdir(parents=True)
(data_root / "Video-MME" / "data").mkdir()
(data_root / "Video-MME" / "preprocessed_videos_384f_262k_total0").mkdir()
(data_root / "Video-MME-v2" / "preprocessed_videos_384f_262k_total0").mkdir()
(data_root / "MVBench" / "videos").mkdir()
(data_root / "OneThinker-eval" / "Refcoco").mkdir()
(data_root / "TimeLens-Bench" / "video_shards" / "charades").mkdir(parents=True)
(data_root / "TimeLens-Bench" / "video_shards" / "activitynet").mkdir()
(data_root / "TimeLens-Bench" / "video_shards" / "qvhighlights").mkdir()
for name in (
"videomme_preprocessed_384f_262k_total0.jsonl",
"videommev2_preprocessed_384f_262k_total0.jsonl",
"mvbench.json",
"mmvu_mc.jsonl",
"videoholmes.jsonl",
"longvideobench_val.jsonl",
"mlvu_mc.jsonl",
"vsibench_preprocessed_128f_16M.jsonl",
):
_write(valid_data / name, "{}\n" if name.endswith(".jsonl") else "[]\n")
_write(data_root / "MMSI-Bench" / "MMSI_bench.tsv", "id\tquestion\tanswer\timage\n")
_write(data_root / "MindCube-Tiny" / "combined-00000-of-00001.parquet", "")
_write(data_root / "ReVSI" / "all_frame" / "test-00000-of-00001.parquet", "")
for name in (
"refcoco_val.json",
"refcoco_testA.json",
"refcoco_testB.json",
"refcocop_val.json",
"refcocop_testA.json",
"refcocop_testB.json",
"refcocog_val.json",
"refcocog_test.json",
):
_write(
runtime_root
/ "eval"
/ "task"
/ "spatial_grounding"
/ "rec_jsons_processed"
/ name
)
for name in (
"eval_got10k.json",
"eval_stvg.json",
"eval_seg_refcoco.json",
"eval_seg_refcocop.json",
"eval_seg_refcocog.json",
"eval_seg_mevis.json",
"eval_seg_reasonvos.json",
):
_write(data_root / "OneThinker-eval" / name)
for name in (
"charades-timelens.json",
"activitynet-timelens.json",
"qvhighlights-timelens.json",
):
_write(data_root / "TimeLens-Bench" / name, "{}\n")
for excluded in ("VideoMMMU", "LVBench", "outputs", "training"):
directory = data_root / excluded
directory.mkdir()
_write(directory / "annotations.jsonl", "{}\n")
return data_root, runtime_root
def test_discovery_covers_only_paper_tasks_and_defaults_to_unauthorized(
tmp_path: Path,
) -> None:
data_root, runtime_root = _fixture_roots(tmp_path)
records = DISCOVERY.discover_eval_sources(data_root, runtime_root)
assert {record["eval_task"] for record in records} == set(DISCOVERY.PAPER_TASKS)
assert len({record["eval_task"] for record in records}) == 16
assert all(record["benchmark"] == record["eval_task"] for record in records)
assert all(record["redistribution_authorized"] is False for record in records)
assert all(str(record["split"]) == str(record["split"]).casefold() for record in records)
serialized = "\n".join(json.dumps(record, sort_keys=True) for record in records)
for excluded in ("VideoMMMU", "LVBench", "outputs", "training"):
assert excluded not in serialized
temporal = [
record for record in records if record["eval_task"] == "temporal_grounding"
]
assert {record["split"] for record in temporal} == {
"activitynet_timelens",
"charades_timelens",
"qvhighlights_timelens",
}
qvhighlights = next(
record for record in temporal if record["split"] == "qvhighlights_timelens"
)
assert qvhighlights["media_roots"]["videos"].endswith(
"TimeLens-Bench/video_shards/qvhighlights"
)
charades = next(record for record in temporal if record["split"] == "charades_timelens")
assert charades["preprocessing"]["fps"] == 4
for record in temporal:
assert record["preprocessing"] == {
"fps": 4,
"min_tokens": 1,
"max_frames": 2048,
"max_pixels": 409600,
"total_tokens": 128000,
}
assert record["legacy_environment"]["TIMELENS_NUM_WORKERS"] == 2
grounding = [
record for record in records if record["eval_task"] == "spatial_grounding"
]
assert all(
"/eval/task/spatial_grounding/rec_jsons_processed/"
in record["annotation_input"]
for record in grounding
)
assert {
record["split"] for record in grounding
} == {
"refcoco_val",
"refcoco_test_a",
"refcoco_test_b",
"refcocop_val",
"refcocop_test_a",
"refcocop_test_b",
"refcocog_val",
"refcocog_test",
}
assert {
record["legacy_environment"]["SPATIAL_GROUNDING_DATASETS"]
for record in grounding
} == {
(
"refcoco-val,refcoco-testA,refcoco-testB,"
"refcoco+-val,refcoco+-testA,refcoco+-testB,"
"refcocog-val,refcocog-test"
)
}
assert all(
record["media_roots"]["images"].endswith("OneThinker-eval/Refcoco")
for record in grounding
)
videomme = next(record for record in records if record["eval_task"] == "videomme")
assert videomme["media_roots"]["videos"].endswith("Video-MME/data")
mvbench = next(record for record in records if record["eval_task"] == "mvbench")
assert mvbench["media_roots"]["videos"].endswith("licensed-data/MVBench")
mindcube = next(record for record in records if record["eval_task"] == "mindcube")
assert mindcube["evaluation"] == {
"prompt_profile": "mindcube_official",
"parser_profile": "multiple_choice",
"metric_profile": "micro_accuracy",
"aggregation": "micro",
"expected_group_counts": {
"rotation": 200,
"among": 600,
"around": 250,
},
}
assert mindcube["source_url"].endswith(
"tree/7dd2725d9bd4149f2aad00a9843f72a3824da003"
)
revsi = next(record for record in records if record["eval_task"] == "revsi")
assert revsi["annotation_input"].endswith(
"ReVSI/all_frame/test-00000-of-00001.parquet"
)
assert revsi["media_roots"]["videos"].endswith("ReVSI/all_frame")
assert revsi["evaluation"]["frame_protocol"] == "native_all_frame"
assert revsi["legacy_environment"]["REVSI_SETTING"].startswith("native-all-f128")
assert revsi["legacy_environment"]["REVSI_EXACT_NFRAMES"] is True
assert revsi["legacy_environment"]["REVSI_EXPECTED_SAMPLES"] == 6808
tracking = next(
record for record in records if record["eval_task"] == "tracking"
)
assert tracking["split"] == "got10k"
assert tracking["legacy_environment"]["TRACKING_DATASETS"] == "eval_got10k"
assert tracking["media_roots"]["default"].endswith("OneThinker-eval")
stvg = next(record for record in records if record["eval_task"] == "stvg")
assert stvg["split"] == "stvg"
assert stvg["legacy_environment"]["STVG_DATASETS"] == "eval_stvg"
assert stvg["media_roots"]["default"].endswith("OneThinker-eval")
segmentation = [
record for record in records if record["eval_task"] == "segmentation"
]
assert {record["split"] for record in segmentation} == {
"refcoco",
"refcocop",
"refcocog",
"mevis",
"reasonvos",
}
assert {
record["split"]: record["expected_count"] for record in segmentation
} == {
"mevis": 424,
"reasonvos": 458,
"refcoco": 3811,
"refcocog": 2537,
"refcocop": 3805,
}
assert all(
record["legacy_environment"]["SEGMENTATION_BATCH_SIZE"] == 16
and record["legacy_environment"]["SEGMENTATION_MAX_PIXELS_IMAGE"] == 1048576
and record["legacy_environment"]["SEGMENTATION_VIDEO_READER"] == "decord"
and record["legacy_environment"]["SEGMENTATION_RUN_SAM2"] is False
and record["preprocessing"]["video_reader"] == "decord"
for record in segmentation
)
def test_authorization_requires_the_explicit_confirmation_flag(tmp_path: Path) -> None:
data_root, runtime_root = _fixture_roots(tmp_path)
output = tmp_path / "private" / "sources.jsonl"
assert (
DISCOVERY.main(
[
"--data-root",
str(data_root),
"--runtime-root",
str(runtime_root),
"--output",
str(output),
"--confirm-redistribution-authorized",
]
)
== 0
)
records = [json.loads(line) for line in output.read_text(encoding="utf-8").splitlines() if line]
assert records
assert all(record["redistribution_authorized"] is True for record in records)
def test_discovery_fails_on_ambiguous_required_annotation(tmp_path: Path) -> None:
data_root, runtime_root = _fixture_roots(tmp_path)
_write(data_root / "MMSI-Bench" / "duplicate" / "MMSI_bench.tsv", "id\n")
with pytest.raises(DISCOVERY.DiscoveryError, match="ambiguous mmsi annotation"):
DISCOVERY.discover_eval_sources(data_root, runtime_root)
def test_tsv_count_accepts_large_embedded_image_fields(tmp_path: Path) -> None:
annotation = _write(
tmp_path / "mmsi.tsv",
f"id\timage\nsample-1\t{'a' * 200_000}\n",
)
assert DISCOVERY._cheap_expected_count(annotation) == 1
def test_mindcube_discovery_accepts_one_verified_official_parquet(
tmp_path: Path,
monkeypatch: pytest.MonkeyPatch,
) -> None:
old_subset = _write(tmp_path / "data" / "test.parquet", "")
official = _write(tmp_path / "official.parquet", "")
counts = {old_subset: 120, official: 1050}
monkeypatch.setattr(DISCOVERY, "_cheap_expected_count", counts.__getitem__)
assert DISCOVERY._mindcube_annotation(tmp_path) == official.resolve()
def test_mindcube_discovery_rejects_only_reduced_parquet(
tmp_path: Path,
monkeypatch: pytest.MonkeyPatch,
) -> None:
reduced = _write(tmp_path / "data" / "test.parquet", "")
monkeypatch.setattr(DISCOVERY, "_cheap_expected_count", lambda _path: 120)
with pytest.raises(DISCOVERY.DiscoveryError, match="requires 1050 rows"):
DISCOVERY._mindcube_annotation(tmp_path)
assert reduced.is_file()
|