Merge a8a36f2c74e68fbd9da20e2db85031b39df76064 into 553741557a57df44a46fb3ab72b6aafeaf945337

deepinfer/environ.py

@@ -7,10 +7,17 @@ from datetime import timedelta
 from typing import Any
 
 DEFAULT_PREFILL_MAX_SUM_SEQLEN_K = 2**30
+_FALSE = {"0", "", "false"}
+_TRUE = {"1", "true"}
 
 
 def _bool(v: str | None, default: str = "0") -> bool:
-    return (v if v is not None else default) not in ("0", "", "false", "False")
+    value = (v if v is not None else default).lower()
+    if value in _FALSE:
+        return False
+    if value in _TRUE:
+        return True
+    raise ValueError("expected one of '0', '1', 'false', 'true' (case-insensitive)")
 
 
 def _int(v: str | None, default: int = 0) -> int:

eval/score.py

@@ -129,7 +129,9 @@ def score_run(
     n_sample = int(meta.get("n_sample", max((row["sample_idx"] for row in results), default=0) + 1))
     missing = sorted(set(by_id) - seen)
     expected_rollouts = len(records) * n_sample
-    coverage_complete = not missing and len(results) == expected_rollouts
+    # load_raw deduplicates (task_id, sample_idx), but stale out-of-range samples
+    # can still compensate for missing samples in the total rollout count.
+    coverage_complete = not missing and len(results) == expected_rollouts and all(0 <= row["sample_idx"] < n_sample for row in results)
     if not coverage_complete:
         print(
             f"[warn] incomplete coverage: {len(seen)}/{len(records)} tasks, {len(results)}/{expected_rollouts} "

tests/eval/test_score_coverage.py

@@ -0,0 +1,47 @@
+from __future__ import annotations
+
+import json
+from pathlib import Path
+
+import pytest
+
+from eval.score import score_run
+
+pytestmark = [pytest.mark.ci, pytest.mark.ci_npu]
+
+
+@pytest.mark.parametrize(
+    ("sample_indices", "complete"),
+    [
+        pytest.param([[0, 1], [0, 1]], True, id="complete"),
+        pytest.param([[1, 0], [1, 0]], True, id="out-of-order"),
+        pytest.param([[0], [0, 1, 2]], False, id="extra-sample-hides-missing-sample"),
+        pytest.param([[1, 2], [0, 1]], False, id="shifted-sample-indices"),
+        pytest.param([[-1, 0], [0, 1]], False, id="negative-sample-index"),
+        pytest.param([[0], [0, 1]], False, id="missing-sample"),
+        pytest.param([[], [0, 1, 2, 3]], False, id="missing-task"),
+        pytest.param([[0, 1, 2], [0, 1]], False, id="extra-sample"),
+    ],
+)
+def test_score_run_sample_coverage(
+    tmp_path: Path, capsys: pytest.CaptureFixture[str], sample_indices: list[list[int]], complete: bool
+) -> None:
+    data_file = tmp_path / "data.jsonl"
+    data_file.write_text(
+        "".join(json.dumps({"task_id": str(i), "question": "What is 1 + 1?", "answer": "2"}) + "\n" for i in range(2)),
+        encoding="utf-8",
+    )
+    (tmp_path / "meta.json").write_text(json.dumps({"bench": "aime", "data_file": str(data_file), "n_sample": 2}), encoding="utf-8")
+    for task_id, indices in enumerate(sample_indices):
+        (tmp_path / f"raw_rank{task_id:03d}.jsonl").write_text(
+            "".join(json.dumps({"task_id": str(task_id), "sample_idx": index, "raw_text": r"\boxed{2}"}) + "\n" for index in indices),
+            encoding="utf-8",
+        )
+
+    assert score_run(str(tmp_path), judge="rule", verbose=False) == 0
+
+    summary = json.loads((tmp_path / "summary.json").read_text(encoding="utf-8"))
+    assert summary["coverage_complete"] is complete
+    assert summary["expected_rollouts"] == 4
+    assert summary["num_rollouts"] == sum(map(len, sample_indices))
+    assert ("[warn] incomplete coverage" in capsys.readouterr().out) is (not complete)