fineenvs_v1: validation run 2026-10-20-fineenvs_v1-36fc78e213a3

### Reproducibility and retries

| Stage | Mode | Tasks with expectation | Matched first attempt | Matched after 1 / 2 / 3+ retries | Archived as not robust | Not-run retried | Recovered | Unresolved |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 1 | classifier | 0 | 0 | 0 / 0 / 0 | 0 | 0 | 0 | 0 |
| 2 | classifier | 0 | 0 | 0 / 0 / 0 | 0 | 0 | 0 | 0 |
| 3 | classifier | 0 | 0 | 0 / 0 / 0 | 0 | 0 | 0 | 0 |

Expected outcomes come from an earlier audit of the same tasks (matched by task ID). A task whose result differs from that audit is rerun up to the retry limit; a task that never matches is archived as not robust. Without an expectation only tasks with no result (crash, node failure, missing reward or missing runner evidence) are rerun, and a task still without a result after the last attempt is archived as not robust. Stages 1, 2 and 3 are covered; the retries run after the whole pipeline.

## fineenvs_v1

Keeps **5,000 tasks** and archives **0** from [FineEnvs/SmolDataEnvs-harbor-train](https://huggingface.co/datasets/FineEnvs/SmolDataEnvs-harbor-train) at commit `4719635555de1666f374d847baebb500d368e493`.


Our patcher modified **5,000 of the original 5,000 tasks**.

Automatic fixes changed **4,576 unique tasks**.

Tasks can have multiple change labels, so category counts may overlap.

| Change label | Tasks affected | Explanation |
| --- | ---: | --- |
| gold-answer-solution | 5000 | Retain one shared upstream image pinned to docker.io/savatar101/env-data-agent-train@sha256:7b3f7e22780b431ce0d43717dcef6875cde84baeee824cc87e968374d62d3470; use its existing math-verify 0.9.0 and check installed dependency versions in tests/setup.sh instead of repeating a best-effort pip install. Move the original input initialization for BUCKET_PREFIX=4quant__soft-tissue-sarcoma and nonempty-input check into setup_files/setup.sh and remove the duplicate healthcheck hook. Preserve the upstream input basename mapping, environment variables, instructions, grading logic and reward.txt output format. Rename the JSON correctness score to reward, including empty/missing-answer zeros; preserve the score value and auxiliary metrics. Add solution/solve.sh, which writes the verifier's EXPECTED_ANSWER to /workdir/answer.txt, so the reference stage can check that the environment and grader accept it; it does not recompute the answer from the data. Package 3 input files (397355382 bytes) under setup_files/inputs with remote Xet identities and SHA-256 checksums in input-manifest.json. Remove the setup downloader invocation and copy the packaged files locally during setup, verifying their checksums with bounded-memory copying. No input download occurs at setup or image build time.<br>Retain one shared upstream image pinned to docker.io/savatar101/env-data-agent-train@sha256:7b3f7e22780b431ce0d43717dcef6875cde84baeee824cc87e968374d62d3470; use its existing math-verify 0.9.0 and check installed dependency versions in tests/setup.sh instead of repeating a best-effort pip install. Move the original input initialization for BUCKET_PREFIX=CooperUnion__anime-recommendations-database and nonempty-input check into setup_files/setup.sh and remove the duplicate healthcheck hook. Preserve the upstream input basename mapping, environment variables, instructions, grading logic and reward.json output format. Rename the JSON correctness score to reward, including empty/missing-answer zeros; preserve the score value and auxiliary metrics. Add solution/solve.sh, which writes the verifier's EXPECTED_ANSWER to /workdir/answer.txt, so the reference stage can check that the environment and grader accept it; it does not recompute the answer from the data. Package 2 input files (112341362 bytes) under setup_files/inputs with remote Xet identities and SHA-256 checksums in input-manifest.json. Remove the setup downloader invocation and copy the packaged files locally during setup, verifying their checksums with bounded-memory copying. No input download occurs at setup or image build time.<br>Retain one shared upstream image pinned to docker.io/savatar101/env-data-agent-train@sha256:7b3f7e22780b431ce0d43717dcef6875cde84baeee824cc87e968374d62d3470; use its existing math-verify 0.9.0 and check installed dependency versions in tests/setup.sh instead of repeating a best-effort pip install. Move the original input initialization for BUCKET_PREFIX=CooperUnion__anime-recommendations-database and nonempty-input check into setup_files/setup.sh and remove the duplicate healthcheck hook. Preserve the upstream input basename mapping, environment variables, instructions, grading logic and reward.txt output format. Rename the JSON correctness score to reward, including empty/missing-answer zeros; preserve the score value and auxiliary metrics. Add solution/solve.sh, which writes the verifier's EXPECTED_ANSWER to /workdir/answer.txt, so the reference stage can check that the environment and grader accept it; it does not recompute the answer from the data. Package 2 input files (112341362 bytes) under setup_files/inputs with remote Xet identities and SHA-256 checksums in input-manifest.json. Remove the setup downloader invocation and copy the packaged files locally during setup, verifying their checksums with bounded-memory copying. No input download occurs at setup or image build time.<br>Retain one shared upstream image pinned to docker.io/savatar101/env-data-agent-train@sha256:7b3f7e22780b431ce0d43717dcef6875cde84baeee824cc87e968374d62d3470; use its existing math-verify 0.9.0 and check installed dependency versions in tests/setup.sh instead of repeating a best-effort pip install. Move the original input initialization for BUCKET_PREFIX=CooperUnion__cardataset and nonempty-input check into setup_files/setup.sh and remove the duplicate healthcheck hook. Preserve the upstream input basename mapping, environment variables, instructions, grading logic and reward.json output format. Rename the JSON correctness score to reward, including empty/missing-answer zeros; preserve the score value and auxiliary metrics. Add solution/solve.sh, which writes the verifier's EXPECTED_ANSWER to /workdir/answer.txt, so the reference stage can check that the environment and grader accept it; it does not recompute the answer from the data. Package 1 input files (1475504 bytes) under setup_files/inputs with remote Xet identities and SHA-256 checksums in input-manifest.json. Remove the setup downloader invocation and copy the packaged files locally during setup, verifying their checksums with bounded-memory copying. No input download occurs at setup or image build time.<br>Retain one shared upstream image pinned to docker.io/savatar101/env-data-agent-train@sha256:7b3f7e22780b431ce0d43717dcef6875cde84baeee824cc87e968374d62d3470; use its existing math-verify 0.9.0 and check installed dependency versions in tests/setup.sh instead of repeating a best-effort pip install. Move the original input initialization for BUCKET_PREFIX=CooperUnion__cardataset and nonempty-input check into setup_files/setup.sh and remove the duplicate healthcheck hook. Preserve the upstream input basename mapping, environment variables, instructions, grading logic and reward.txt output format. Rename the JSON correctness score to reward, including empty/missing-answer zeros; preserve the score value and auxiliary metrics. Add solution/solve.sh, which writes the verifier's EXPECTED_ANSWER to /workdir/answer.txt, so the reference stage can check that the environment and grader accept it; it does not recompute the answer from the data. Package 1 input files (1475504 bytes) under setup_files/inputs with remote Xet identities and SHA-256 checksums in input-manifest.json. Remove the setup downloader invocation and copy the packaged files locally during setup, verifying their checksums with bounded-memory copying. No input download occurs at setup or image build time.<br>Retain one shared upstream image pinned to docker.io/savatar101/env-data-agent-train@sha256:7b3f7e22780b431ce0d43717dcef6875cde84baeee824cc87e968374d62d3470; use its existing math-verify 0.9.0 and check installed dependency versions in tests/setup.sh instead of repeating a best-effort pip install. Move the original input initialization for BUCKET_PREFIX=Cornell-University__movie-dialog-corpus and nonempty-input check into setup_files/setup.sh and remove the duplicate healthcheck hook. Preserve the upstream input basename mapping, environment variables, instructions, grading logic and reward.json output format. Rename the JSON correctness score to reward, including empty/missing-answer zeros; preserve the score value and auxiliary metrics. Add solution/solve.sh, which writes the verifier's EXPECTED_ANSWER to /workdir/answer.txt, so the reference stage can check that the environment and grader accept it; it does not recompute the answer from the data. Package 6 input files (30116727 bytes) under setup_files/inputs with remote Xet identities and SHA-256 checksums in input-manifest.json. Remove the setup downloader invocation and copy the packaged files locally during setup, verifying their checksums with bounded-memory copying. No input download occurs at setup or image build time.<br>Retain one shared upstream image pinned to docker.io/savatar101/env-data-agent-train@sha256:7b3f7e22780b431ce0d43717dcef6875cde84baeee824cc87e968374d62d3470; use its existing math-verify 0.9.0 and check installed dependency versions in tests/setup.sh instead of repeating a best-effort pip install. Move the original input initialization for BUCKET_PREFIX=PromptCloudHQ__amazon-reviews-unlocked-mobile-phones and nonempty-input check into setup_files/setup.sh and remove the duplicate healthcheck hook. Preserve the upstream input basename mapping, environment variables, instructions, grading logic and reward.txt output format. Rename the JSON correctness score to reward, including empty/missing-answer zeros; preserve the score value and auxiliary metrics. Add solution/solve.sh, which writes the verifier's EXPECTED_ANSWER to /workdir/answer.txt, so the reference stage can check that the environment and grader accept it; it does not recompute the answer from th

fineenvs_v1/archive.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c40d87d7120d98b899773345bad4d1501f4d4cab98e2bd22e4b2fb6724a66e1d
+size 3798215

fineenvs_v1/patch.py

@@ -0,0 +1,437 @@
+"""Expose FineEnvs preparation while retaining one inspected upstream image.
+
+First run data/utils/fineenvs/prepare_inputs.py on the pinned source. Then run this patcher with
+--source PINNED.parquet --inputs-cache SNAPSHOT --output NEW_DIRECTORY.
+Every retained task includes its input bytes under setup_files/inputs. This
+patcher does not access the network, build images, or execute task verifiers.
+"""
+import argparse
+import copy
+import gzip
+import hashlib
+import io
+import json
+from pathlib import Path
+import re
+import shlex
+import sys
+import tarfile
+import tomllib
+from concurrent.futures import ProcessPoolExecutor
+from multiprocessing import get_context
+
+sys.path.insert(0, str(Path(__file__).resolve().parents[2]))
+from data.utils.patch_reporting import write_patch_report
+from data.utils.task_archive import read_members
+
+SOURCE = {
+    "dataset": "FineEnvs/SmolDataEnvs-harbor-train",
+    "url": "https://huggingface.co/datasets/FineEnvs/SmolDataEnvs-harbor-train",
+    "revision": "4719635555de1666f374d847baebb500d368e493",
+}
+ORIGINAL_DOCKERFILE = b"FROM docker.io/savatar101/env-data-agent-train:base\nWORKDIR /workdir\n"
+PIP_PREPARATION = b"pip install --quiet math-verify >/dev/null 2>&1 || true\n"
+HEALTHCHECK = 'python3 /opt/pull_bucket.py && [ -n "$(ls /home/user/input)" ]'
+TASK_SETUP = b'''#!/usr/bin/env bash
+set -euo pipefail
+python3 /setup_files/pull_bucket.py
+[ -n "$(ls /home/user/input)" ]
+'''
+# All source tasks passed validation with packaged inputs.
+EXCLUDED = {}
+SUPPORT_DIR = Path(__file__).resolve().parents[1] / "utils" / "fineenvs"
+if Path(__file__).with_name("preparation.json").is_file():
+    SUPPORT_DIR = Path(__file__).resolve().parent
+LOCK_PATH = SUPPORT_DIR / "preparation.json"
+SNAPSHOT_PATH = SUPPORT_DIR / "input-snapshot.json"
+SNAPSHOT_ROOT = "/opt/fineenvs-inputs"
+# Only the measured slow prefix receives an additional shared image. Build-time
+# downloads must match both the recorded remote identities and actual bytes.
+BUILD_SNAPSHOT = b'''import hashlib
+import json
+from pathlib import Path
+from huggingface_hub import download_bucket_files, list_bucket_tree
+
+root = Path("/opt/fineenvs-inputs")
+snapshot = json.loads((root / "manifest.json").read_text())
+observed = {f.path: f for f in list_bucket_tree(
+    snapshot["bucket"], prefix=snapshot["prefix"] + "/", recursive=True,
+    token=False) if getattr(f, "type", None) == "file"}
+assert set(observed) == {f["path"] for f in snapshot["files"]}, "input inventory changed"
+targets = []
+for f in snapshot["files"]:
+    actual = observed[f["path"]]
+    assert (actual.size, actual.xet_hash) == (f["size"], f["xet_hash"]), "remote input changed"
+    targets.append((actual, root / "files" / Path(f["path"]).name))
+(root / "files").mkdir(parents=True, exist_ok=True)
+download_bucket_files(snapshot["bucket"], files=targets, token=False)
+for f in snapshot["files"]:
+    path = root / "files" / Path(f["path"]).name
+    assert path.stat().st_size == f["size"], "input size mismatch"
+    with path.open("rb") as stream:
+        assert hashlib.file_digest(stream, "sha256").hexdigest() == f["sha256"], "input hash mismatch"
+'''
+STAGE_SNAPSHOT = b'''import hashlib
+import json
+import os
+from pathlib import Path
+import time
+
+
+def copy_input(source, target, expected):
+    # Avoid the opaque sendfile fast path used by shutil.copyfile. Keep dirty
+    # destination pages bounded for the upstream 1 GiB task memory limit.
+    started = time.monotonic()
+    digest = hashlib.sha256()
+    total = pending = 0
+    with source.open("rb") as reader, target.open("wb", buffering=0) as writer:
+        while chunk := reader.read(1024 * 1024):
+            view = memoryview(chunk)
+            while view:
+                written = writer.write(view)
+                if not written:
+                    raise OSError("input copy made no progress")
+                view = view[written:]
+            digest.update(chunk)
+            total += len(chunk)
+            pending += len(chunk)
+            if pending >= 32 * 1024 * 1024:
+                os.fdatasync(writer.fileno())
+                os.posix_fadvise(writer.fileno(), total - pending, pending, os.POSIX_FADV_DONTNEED)
+                pending = 0
+        os.fdatasync(writer.fileno())
+        os.posix_fadvise(writer.fileno(), 0, 0, os.POSIX_FADV_DONTNEED)
+    if total != expected["size"] or digest.hexdigest() != expected["sha256"]:
+        raise RuntimeError(f"input copy mismatch: {source.name}")
+    print(f"[pull_bucket] copied {source.name}: {total} bytes in {time.monotonic() - started:.3f}s", flush=True)
+
+
+root = Path("/opt/fineenvs-inputs")
+snapshot = json.loads((root / "manifest.json").read_text())
+assert os.environ["BUCKET_PREFIX"].rstrip("/") == snapshot["prefix"]
+assert (os.environ.get("HF_BUCKET") or "AdithyaSK/jupyter-agent-kaggle-all") == snapshot["bucket"]
+dest = Path("/home/user/input")
+dest.mkdir(parents=True, exist_ok=True)
+# Match the original downloader's existing-file guard and basename mapping.
+existing = [p for p in dest.iterdir() if p.is_file()]
+if existing:
+    print(f"[pull_bucket] {dest}/ already has {len(existing)} file(s); skipping", flush=True)
+else:
+    for f in snapshot["files"]:
+        source = root / "files" / Path(f["path"]).name
+        assert source.stat().st_size == f["size"], "baked input size mismatch"
+        print(f"[pull_bucket] copying {source.name}: {f['size']} bytes", flush=True)
+        copy_input(source, dest / source.name, f)
+    print(f"[pull_bucket] staged {len(snapshot['files'])} file(s) from baked snapshot", flush=True)
+'''
+
+
+def verifier_setup(lock):
+    versions = repr(lock["verifier_distributions"])
+    return ("#!/usr/bin/env bash\nset -euo pipefail\npython3 - <<'PY'\n"
+            "from importlib.metadata import version\n"
+            f"expected = {versions}\n"
+            "for name, wanted in expected.items():\n"
+            "    actual = version(name)\n"
+            "    if actual != wanted:\n"
+            "        raise RuntimeError(f'{name}: expected {wanted}, found {actual}')\n"
+            "from math_verify import parse, verify\n"
+            "import antlr4, latex2sympy2_extended, mpmath, sympy\n"
+            "PY\n").encode()
+
+
+def gold_solution(config):
+    """Reference solution: write the answer the grader expects, exactly as the agent must.
+
+    It proves the environment starts, the answer path is writable and the grader
+    accepts the expected value; it does not recompute the answer from the data.
+    The grader compares against verifier.env EXPECTED_ANSWER, which differs from the
+    notebook's metadata.gold_answer in 41 upstream tasks.
+    """
+    expected = config["verifier"]["env"]["EXPECTED_ANSWER"]
+    return ("#!/bin/bash\nset -euo pipefail\nmkdir -p /workdir\n"
+            f"printf '%s' {shlex.quote(expected)} > /workdir/answer.txt\n").encode()
+
+
+def normalize_rewards(script, grader):
+    """Rename the JSON score, including the missing-answer branch, without regrading."""
+    if grader.count(b'"correctness":') != 2:
+        raise ValueError("unexpected upstream JSON grader score fields")
+    if b"reward.json" in script:
+        if script.count(b'"correctness":') != 1:
+            raise ValueError("unexpected upstream missing-answer JSON score")
+        script = script.replace(b'"correctness":', b'"reward":')
+        script = script.replace(b"#   correctness      ", b"#   reward           ")
+    elif b"reward.txt" not in script:
+        raise ValueError("unknown upstream reward format")
+    return script, grader.replace(b'"correctness":', b'"reward":')
+
+
+def transform(blob, lock, snapshot=None, packaged=None):
+    files = read_members(blob)
+    config = tomllib.loads(files["task.toml"].decode())
+    if files["environment/Dockerfile"] != ORIGINAL_DOCKERFILE:
+        raise ValueError("unexpected upstream Dockerfile")
+    if hashlib.sha256(files["environment/pull_bucket.py"]).hexdigest() != lock["pull_bucket_sha256"]:
+        raise ValueError("unexpected upstream input downloader")
+    if config["environment"]["healthcheck"]["command"] != HEALTHCHECK:
+        raise ValueError("unexpected upstream healthcheck")
+    if files["tests/test.sh"].count(PIP_PREPARATION) != 1:
+        raise ValueError("unexpected upstream verifier preparation")
+    if any(name.startswith(("setup_files/", "solution/")) or name == "tests/setup.sh" for name in files):
+        raise ValueError("unexpected existing setup or solution")
+    # Remove only the obsolete lifecycle declaration and its explanatory comment.
+    # Preserve other TOML bytes, including variables, answers and resources.
+    toml, count = re.subn(
+        r"# Pre-agent hook: Harbor runs the command AFTER container start and BEFORE the\n"
+        r"# agent setup begins\. We use it to pull this task's bucket prefix into\n"
+        r"# /home/user/input/\. See environment/pull_bucket\.py\.\n"
+        r"\[environment\.healthcheck\]\n.*?(?=\[environment\.env\])",
+        "", files["task.toml"].decode(), count=1, flags=re.S)
+    if count != 1:
+        raise ValueError("unexpected upstream lifecycle declaration")
+    before = copy.deepcopy(config)
+    del before["environment"]["healthcheck"]
+    if tomllib.loads(toml) != before:
+        raise ValueError("configuration changed beyond the healthcheck removal")
+    verifier_script, grader = normalize_rewards(
+        files["tests/test.sh"].replace(PIP_PREPARATION, b""), files["tests/grader.py"])
+    replacements = {
+        "environment/Dockerfile": (f'FROM {lock["image"]}\nWORKDIR /workdir\n').encode(),
+        "task.toml": toml.encode(),
+        "tests/test.sh": verifier_script,
+        "tests/grader.py": grader,
+    }
+    additions = {
+        "setup_files/setup.sh": (TASK_SETUP, 0o755),
+        "setup_files/pull_bucket.py": (files["environment/pull_bucket.py"], 0o644),
+        "tests/setup.sh": (verifier_setup(lock), 0o755),
+        "solution/solve.sh": (gold_solution(config), 0o755),
+    }
+    prebuilt = packaged is None and snapshot is not None and config["environment"]["env"]["BUCKET_PREFIX"].rstrip("/") == snapshot["prefix"]
+    if prebuilt:
+        if config["environment"]["env"]["HF_BUCKET"] != snapshot["bucket"]:
+            raise ValueError("snapshot bucket does not match task")
+        names = [Path(f["path"]).name for f in snapshot["files"]]
+        if not names or len(set(names)) != len(names):
+            raise ValueError("snapshot has missing or colliding basenames")
+        additions.update({
+            "environment/input-snapshot.json": ((json.dumps(snapshot, sort_keys=True, indent=2) + "\n").encode(), 0o644),
+            "environment/build_snapshot.py": (BUILD_SNAPSHOT, 0o644),
+            "setup_files/stage_inputs.py": (STAGE_SNAPSHOT, 0o644),
+        })
+        replacements["environment/Dockerfile"] += (
+            f"COPY input-snapshot.json {SNAPSHOT_ROOT}/manifest.json\n"
+            f"COPY build_snapshot.py {SNAPSHOT_ROOT}/build_snapshot.py\n"
+            f"RUN python3 {SNAPSHOT_ROOT}/build_snapshot.py\n").encode()
+        additions["setup_files/setup.sh"] = (TASK_SETUP.replace(b"pull_bucket.py", b"stage_inputs.py"), 0o755)
+    if packaged is not None:
+        manifest, directory = packaged
+        env = config['environment']['env']
+        if (manifest['bucket'], manifest['prefix']) != (env['HF_BUCKET'], env['BUCKET_PREFIX'].rstrip('/')):
+            raise ValueError('packaged input family does not match task')
+        names = [f['name'] for f in manifest['files']]
+        if not names or len(names) != len(set(names)) or any(
+                not n or Path(n).is_absolute() or '..' in Path(n).parts or Path(n).as_posix() != n or n == '.' for n in names):
+            raise ValueError('invalid or colliding input paths')
+        del additions['setup_files/pull_bucket.py']
+        additions.update({
+            'setup_files/setup.sh': (TASK_SETUP.replace(b'pull_bucket.py', b'stage_inputs.py'), 0o755),
+            'setup_files/stage_inputs.py': ((SUPPORT_DIR / 'stage_inputs.py').read_bytes(), 0o644),
+            'setup_files/input-manifest.json': ((json.dumps(manifest, sort_keys=True, indent=2) + '\n').encode(), 0o644),
+        })
+        for item in manifest['files']:
+            additions['setup_files/inputs/' + item['name']] = (directory / 'files' / item['name'], 0o644)
+        if any('/' in name for name in names):
+            instruction = files['instruction.md'].decode()
+            instruction = instruction.replace('Files (in /home/user/input, no subfolders):',
+                'Files (in /home/user/input; additional source variants retain their subfolders):')
+            for name in names:
+                if '/' not in name:
+                    instruction = re.sub(r'(?m)^- ' + re.escape(name) + r'$',
+                                         lambda match: '- /home/user/input/' + name, instruction)
+            replacements['instruction.md'] = instruction.encode()
+    # Preserve original modes, links and metadata. Fix gzip time and new-member
+    # metadata so repeated patching produces identical bytes.
+    output = io.BytesIO()
+    with gzip.GzipFile(fileobj=output, mode="wb", filename="", mtime=0,
+                       compresslevel=1 if packaged is not None else 9) as compressed:
+        with tarfile.open(fileobj=io.BytesIO(blob), mode="r:*") as original:
+            with tarfile.open(fileobj=compressed, mode="w") as patched:
+                for member in original:
+                    content = original.extractfile(member).read() if member.isfile() else None
+                    info = copy.copy(member)
+                    if member.name in replacements:
+                        content = replacements[member.name]
+                        info.size = len(content)
+                    patched.addfile(info, io.BytesIO(content) if content is not None else None)
+                for name, (content, mode) in sorted(additions.items()):
+                    info = tarfile.TarInfo(name)
+                    info.mode = mode
+                    if isinstance(content, Path):
+                        info.size = content.stat().st_size
+                        with content.open('rb') as stream:
+                            patched.addfile(info, stream)
+                    else:
+                        info.size = len(content)
+                        patched.addfile(info, io.BytesIO(content))
+    variant = "reward.json" if b"reward.json" in files["tests/test.sh"] else "reward.txt"
+    reason = (
+        f"Retain one shared upstream image pinned to {lock['image']}; use its existing "
+        "math-verify 0.9.0 and check installed dependency versions in tests/setup.sh "
+        "instead of repeating a best-effort pip install. Move the original input "
+        f"initialization for BUCKET_PREFIX={config['environment']['env']['BUCKET_PREFIX']} "
+        "and nonempty-input check into setup_files/setup.sh and remove the duplicate "
+        "healthcheck hook. Preserve the upstream downloader bytes and basename mapping, "
+        f"environment variables, instructions, grading logic and {variant} output format. "
+        "Rename the JSON correctness score to reward, including empty/missing-answer zeros; "
+        "preserve the score value and auxiliary metrics. "
+        "Add solution/solve.sh, which writes the verifier's EXPECTED_ANSWER to "
+        "/workdir/answer.txt, so the reference stage can check that the environment and grader "
+        "accept it; it does not recompute the answer from the data."
+    )
+    if config["metadata"]["gold_answer"] != config["verifier"]["env"]["EXPECTED_ANSWER"]:
+        reason += (f" Upstream records two answers: notebook gold_answer "
+                   f"{config['metadata']['gold_answer']!r} and graded EXPECTED_ANSWER "
+                   f"{config['verifier']['env']['EXPECTED_ANSWER']!r}; the solution uses the graded one.")
+    if prebuilt:
+        reason += (
+            f" Bake all {len(snapshot['files'])} original input files ({sum(f['size'] for f in snapshot['files'])} bytes) "
+            "into one image shared by this bucket family, with remote Xet identity and SHA-256 checks at build time. "
+            "Copy the same basenames and bytes locally during setup, preserving the existing-file guard. "
+            "The pilot task 0060_333_60333012_qa_4 timed out in all five fresh preparations at 60.001 seconds; "
+            f"evidence: {snapshot['evidence']['report']}; archive member: {snapshot['evidence']['archive_member']}. "
+            "A later public download succeeded, so this is a preparation reliability repair, not an exclusion. "
+            "Generation 1 built this snapshot image successfully, but local copy preparation still "
+            "hit 60 seconds in two of five runs (others 9.047, 8.949 and 8.615 seconds). "
+            "Replace shutil.copyfile/sendfile with a 1 MiB buffered copy, flush and release only "
+            "destination cache pages every 32 MiB, and verify SHA-256 during the copy. "
+            "This addresses possible dirty-page pressure from 943755800 input bytes under the "
+            "unchanged 1024 MiB memory limit; logs do not establish the kernel stall cause. "
+            "Per-file progress and elapsed-time logs expose any remaining stall. "
+            "Evidence: generation-0001/stage3-10/results/submissions/e437d78d5ed6/report/"
+            "stage-3-a8956d95a28f.json; archive image-build-logs/fd623c862442.build.log and "
+            "results/stage_3_build_validation/a8956d95a28f/00004-0060_333_60333012_qa_4/"
+            "preparation-review.json (retry-1 through retry-4). "
+            "Verifier timeout remains 120 seconds; successful verifier preparations met its "
+            "6-second allowance. Fresh stage-3 setup review is required; this is not a claimed pass."
+        )
+    if packaged is not None:
+        reason = reason.replace('Preserve the upstream downloader bytes and basename mapping, ',
+                                'Preserve the upstream input basename mapping, ')
+        reason += (f" Package {len(manifest['files'])} input files ({sum(f['size'] for f in manifest['files'])} bytes) "
+                   "under setup_files/inputs with remote Xet identities and SHA-256 checksums in input-manifest.json. "
+                   "Remove the setup downloader invocation and copy the packaged files locally during setup, verifying "
+                   "their checksums with bounded-memory copying. No input download occurs at setup or image build time.")
+        if any('/' in f['name'] for f in manifest['files']):
+            reason += (' Preserve content-pinned input variants under distinct source-relative paths instead of '
+                       'the upstream downloader overwriting equal basenames nondeterministically. '
+                       'Keep task-declared root files at their original root locations and make those instruction '
+                       'paths explicit; disclose the additional source subfolders. Question and graded answer are unchanged.')
+    return output.getvalue(), reason
+
+
+def packaged_inputs(cache, source):
+    """Verify a complete prepared snapshot once before reusing its families."""
+    def digest(path):
+        with path.open('rb') as stream:
+            return hashlib.file_digest(stream, 'sha256').hexdigest()
+    index = json.loads((cache / 'index.json').read_text())
+    if not index.get('complete') or index['source'] != SOURCE or index['source_parquet_sha256'] != digest(source):
+        raise ValueError('input snapshot is incomplete or belongs to a different source')
+    result = {}
+    for family in index['families']:
+        path = (cache / family['manifest']).resolve()
+        if not path.is_relative_to(cache.resolve()) or digest(path) != family['manifest_sha256']:
+            raise ValueError('input manifest path or checksum mismatch')
+        manifest = json.loads(path.read_text())
+        key = (manifest['bucket'], manifest['prefix'])
+        if key in result or key != (family['bucket'], family['prefix']):
+            raise ValueError('duplicate or mismatched input family')
+        names = [f['name'] for f in manifest['files']]
+        if not names or len(set(names)) != len(names) or any(
+                not n or Path(n).is_absolute() or '..' in Path(n).parts or Path(n).as_posix() != n or n == '.' for n in names):
+            raise ValueError('invalid input manifest filenames')
+        for item in manifest['files']:
+            f = path.parent / 'files' / item['name']
+            if f.is_symlink() or f.stat().st_size != item['size'] or digest(f) != item['sha256']:
+                raise ValueError('packaged input checksum mismatch: ' + str(f))
+        result[key] = (manifest, path.parent)
+    return index, result
+
+
+def main():
+    parser = argparse.ArgumentParser(description=__doc__)
+    parser.add_argument("--source", type=Path, required=True)
+    parser.add_argument("--output", type=Path, required=True)
+    parser.add_argument('--inputs-cache', type=Path, required=True,
+                        help='complete checksum-verified snapshot produced by prepare_inputs.py')
+    parser.add_argument('--workers', type=int, default=4, help='bounded parallel task compression workers')
+    parser.add_argument('--include-archived', action='store_true',
+                        help='include any explicitly excluded tasks for revalidation')
+    args = parser.parse_args()
+    if not 1 <= args.workers <= 8:
+        parser.error('--workers must be between 1 and 8')
+    import pyarrow as pa
+    import pyarrow.parquet as pq
+    source = args.source
+    if source.is_dir():
+        sources = sorted(source.glob("*.parquet"))
+        if len(sources) != 1:
+            raise ValueError("expected one pinned source Parquet")
+        source = sources[0]
+    destination = args.output / source.name
+    reporting_paths = [destination, destination.with_suffix('.archive.parquet'),
+                       destination.with_suffix('.manifest.json'),
+                       destination.with_suffix('.manifest.patch.py'),
+                       args.output / 'preparation.json']
+    reporting_paths.append(args.output / 'input-snapshot.json')
+    if destination.resolve() == source.resolve() or any(p.exists() for p in reporting_paths):
+        raise ValueError("use a new output directory distinct from the immutable source")
+    lock = json.loads(LOCK_PATH.read_text())
+    input_index, inputs = packaged_inputs(args.inputs_cache, source)
+    parquet = pq.ParquetFile(source)
+    args.output.mkdir(parents=True, exist_ok=True)
+    labels, reasons = {}, {}
+    excluded = {} if args.include_archived else EXCLUDED
+    with ProcessPoolExecutor(max_workers=args.workers, mp_context=get_context('spawn')) as pool, \
+            pq.ParquetWriter(destination, parquet.schema_arrow) as writer:
+        for batch in parquet.iter_batches(batch_size=args.workers * 2):
+            rows = [row for row in batch.to_pylist() if row["path"] not in excluded]
+            pending = []
+            for row in rows:
+                config = tomllib.loads(read_members(row['task_binary'])['task.toml'].decode())
+                env = config['environment']['env']
+                family = inputs[(env['HF_BUCKET'], env['BUCKET_PREFIX'].rstrip('/'))]
+                pending.append(pool.submit(transform, row['task_binary'], lock, None, family))
+            for row, future in zip(rows, pending):
+                name = row["path"]
+                if name in labels:
+                    raise ValueError(f"duplicate source task ID: {name}")
+                row["task_binary"], reasons[name] = future.result()
+                labels[name] = ["runtime-preparation", "gold-answer-solution", "reward-key-normalization"]
+                labels[name].append('packaged-task-inputs')
+            writer.write_table(pa.Table.from_pylist(rows, schema=parquet.schema_arrow))
+            if len(labels) and len(labels) % 100 < len(rows):
+                print(f'Packaged {len(labels)} tasks', flush=True)
+    report = write_patch_report(
+        source, destination, source=SOURCE,
+        dropped={name: {"category": "resource-limit", "reason": reason} for name, reason in excluded.items()},
+        change_labels=labels,
+        change_reasons=reasons, patches=[{"label": "runtime-preparation", **lock},
+                                        {"label": "packaged-task-inputs", **input_index},
+                                        {"label": "reward-key-normalization", "reason": "Rename JSON correctness to reward without changing grading."},
+                                        {"label": "gold-answer-solution", "reason": "solution/solve.sh "
+                                         "writes the graded EXPECTED_ANSWER to /workdir/answer.txt."}],
+        patcher=__file__)
+    (args.output / 'preparation.json').write_bytes(LOCK_PATH.read_bytes())
+    (args.output / 'input-snapshot.json').write_text(json.dumps(input_index, indent=2) + '\n')
+    for helper in ('stage_inputs.py', 'prepare_inputs.py', 'reviewed-input-conflicts.json'):
+        (args.output / helper).write_bytes((SUPPORT_DIR / helper).read_bytes())
+    print(json.dumps({"tasks": len(report["tasks"]), "changed": len(labels),
+                      "excluded": len(excluded), "output": str(destination),
+                      "requires_review_setup": True}))
+
+
+if __name__ == "__main__":
+    main()

fineenvs_v1/tasks.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9ff268d168d9f63d271e0f4ed3633efeb297de0ea8ca8548a6f962efe4af850c
+size 35925854146