Datasets:
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5618ed1 | 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 | #!/usr/bin/env python3
"""Merge sharded Cosmos3-Super task-15 interaction-text predictions."""
from __future__ import annotations
import argparse
import json
from pathlib import Path
from typing import Any
from eval_cosmos3_super_interaction_text_task import TASK_ID, score_rows, write_outputs
def parse_args() -> argparse.Namespace:
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument("--run-id", required=True)
parser.add_argument("--output-dir", type=Path, required=True)
parser.add_argument("--shard-dir", type=Path, nargs="+", required=True)
parser.add_argument("--caption-manifest", type=Path, required=True)
parser.add_argument("--dataset-jsonl", type=Path, required=True)
parser.add_argument("--caption-jsonl", type=Path, required=True)
parser.add_argument("--model", required=True)
parser.add_argument("--base-url", default="http://127.0.0.1:8000/v1")
parser.add_argument("--eval-split", default="test")
parser.add_argument("--candidate-count", type=int, default=4)
return parser.parse_args()
def read_json(path: Path) -> dict[str, Any]:
return json.loads(path.read_text(encoding="utf-8")) if path.exists() else {}
def read_jsonl(path: Path) -> list[dict[str, Any]]:
rows = []
with path.open("r", encoding="utf-8") as handle:
for line in handle:
line = line.strip()
if line:
rows.append(json.loads(line))
return rows
def main() -> int:
args = parse_args()
merged: dict[str, dict[str, Any]] = {}
for shard_dir in args.shard_dir:
path = shard_dir / TASK_ID / "predictions.jsonl"
if not path.exists():
raise FileNotFoundError(f"missing shard predictions: {path}")
for row in read_jsonl(path):
pred_id = row.get("prediction_id")
if not pred_id:
raise ValueError(f"prediction row missing prediction_id in {path}")
if pred_id in merged:
raise ValueError(f"duplicate prediction_id across shards: {pred_id}")
merged[str(pred_id)] = row
rows = sorted(merged.values(), key=lambda row: (str(row.get("episode_id")), int(row.get("start_frame", 0)), str(row.get("id"))))
manifest = read_json(args.caption_manifest)
score_args = argparse.Namespace(
run_id=args.run_id,
output_dir=args.output_dir,
model=args.model,
base_url=args.base_url,
dataset_jsonl=args.dataset_jsonl,
caption_jsonl=args.caption_jsonl,
caption_manifest=args.caption_manifest,
eval_split=args.eval_split,
candidate_count=args.candidate_count,
sample_offset=0,
sample_stride=len(args.shard_dir),
)
metrics, _per_class, _confusion = score_rows(rows, score_args, manifest)
write_outputs(rows, score_args, manifest)
(args.output_dir / "summary.json").write_text(
json.dumps(
{
"title": "Cosmos3-Super Reasoner Interaction Text Task-15 Probe",
"status": "pass",
"run_id": args.run_id,
"shard_dirs": [str(path) for path in args.shard_dir],
"task_metrics": {TASK_ID: metrics},
"output_dir": str(args.output_dir),
},
indent=2,
sort_keys=True,
)
+ "\n",
encoding="utf-8",
)
return 0
if __name__ == "__main__":
raise SystemExit(main())
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