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AutoResearchExam v1.1: run on Harbor main with any agent harness (part 2)
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import json
import os
import shutil
import stat
import subprocess
import sys
import tempfile
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
import grader_core
TESTS_DIR = os.path.dirname(os.path.abspath(__file__))
DELIVERABLE = "/app/output"
ENTRY_POINT = "executor.py"
LOG_DIR = "/logs/verifier"
CORE_MODULES = ("worker.py", "graph_spec.py", "reference_executor.py")
SPLIT = os.environ.get("GRADE_SPLIT", "final")
PRIVATE = SPLIT == "final"
PREFLIGHT_TIMEOUT_SEC = 120.0
_RESULT = {}
def _sealed_seeds():
path = os.path.join(TESTS_DIR, "hidden_data", SPLIT, "seeds.json")
with open(path) as fh:
return [int(s) for s in json.load(fh)["seeds"]]
def _privilege_drop():
"""Run candidate code as uid 1001, never as root.
Returns (argv prefix, extra Popen kwargs). `runuser` is the normal path; the
Popen user=/group= form is a binary-free fallback so that a base image without
util-linux cannot silently turn every rollout into a zero.
"""
runuser = shutil.which("runuser")
if runuser:
return [runuser, "-u", "agent", "--"], {}
setpriv = shutil.which("setpriv")
if setpriv:
return [setpriv, "--reuid=1001", "--regid=1001", "--clear-groups", "--"], {}
return [], {"user": 1001, "group": 1001}
def _reject_links(root):
"""Refuse a submission tree containing anything but plain files and directories.
A symlink or a hard link inside the deliverable would let a privileged copy
materialise a file from outside the deliverable into the directory the score is
computed from.
"""
if os.path.islink(root):
raise RuntimeError("%s is a symlink" % root)
for dirpath, dirnames, filenames in os.walk(root, followlinks=False):
for name in dirnames + filenames:
path = os.path.join(dirpath, name)
st = os.lstat(path)
if stat.S_ISLNK(st.st_mode):
raise RuntimeError("symlink in the deliverable: %s" % path)
if stat.S_ISREG(st.st_mode) and st.st_nlink > 1:
raise RuntimeError("hard link in the deliverable: %s" % path)
if not (stat.S_ISREG(st.st_mode) or stat.S_ISDIR(st.st_mode)):
raise RuntimeError("not a regular file or directory: %s" % path)
def _stage():
"""Copy the verifier's own modules and the submission into a root-owned run dir."""
run = tempfile.mkdtemp(prefix="grade_", dir="/tmp")
for name in CORE_MODULES:
shutil.copy2(os.path.join(TESTS_DIR, name), os.path.join(run, name))
dst = os.path.join(run, "submission")
_reject_links(DELIVERABLE)
shutil.copytree(DELIVERABLE, dst, symlinks=True)
for dirpath, dirnames, filenames in os.walk(run):
os.chown(dirpath, 0, 0)
os.chmod(dirpath, 0o755)
for name in filenames:
path = os.path.join(dirpath, name)
os.chown(path, 0, 0)
os.chmod(path, 0o644)
os.chmod(run, 0o755)
return run
def _preflight(run, prefix, popen_kwargs):
"""Import the entry point in a throwaway unprivileged process, for a clear message."""
code = ("import sys; sys.path.insert(0, %r); sys.path.insert(0, %r); "
"import executor; assert callable(executor.build_executor)"
% (run, os.path.join(run, "submission")))
proc = subprocess.run(prefix + [sys.executable, "-I", "-B", "-c", code],
capture_output=True, text=True, cwd=run,
timeout=PREFLIGHT_TIMEOUT_SEC, check=False,
start_new_session=True, **popen_kwargs)
return proc.returncode, (proc.stderr or "")[-2000:]
def _grade():
if _RESULT:
return _RESULT
record = {
"metric_name": "geometric_mean_speedup",
"metric": 0.0,
"valid": False,
"failure": None,
"split": SPLIT,
"per_instance": [],
"n_instances": 0,
"n_equivalent": 0,
"preflight_rc": None,
"preflight_stderr": "",
}
run = None
try:
entry = os.path.join(DELIVERABLE, ENTRY_POINT)
if not os.path.isfile(entry):
raise RuntimeError("no entry point at %s" % entry)
prefix, popen_kwargs = _privilege_drop()
run = _stage()
rc, err = _preflight(run, prefix, popen_kwargs)
record["preflight_rc"] = rc
record["preflight_stderr"] = err
if rc != 0:
raise RuntimeError("executor.py could not be imported (rc=%s)" % rc)
measured = grader_core.measure(_sealed_seeds(), run, python=sys.executable,
launch_prefix=prefix,
popen_kwargs=popen_kwargs)
record.update({k: measured[k] for k in
("metric", "valid", "failure", "per_instance",
"n_instances", "n_equivalent")})
record["stderr_tail"] = measured.get("stderr_tail", "")
except Exception as exc:
record["metric"] = 0.0
record["valid"] = False
record["failure"] = "%s: %s" % (type(exc).__name__, exc)
finally:
if run:
shutil.rmtree(run, ignore_errors=True)
os.makedirs(LOG_DIR, exist_ok=True)
with open(os.path.join(LOG_DIR, "metric.json"), "w") as fh:
json.dump(record, fh, indent=2, sort_keys=True)
_RESULT.update(record)
return record
def test_deliverable_is_present_and_importable():
"""The graded deliverable exists at the declared path and imports cleanly."""
record = _grade()
assert record["preflight_rc"] == 0, (
"executor.py missing or not importable: %s\n%s"
% (record["failure"], record.get("preflight_stderr", "")))
def test_output_matches_the_reference_on_every_sealed_instance():
"""Every sealed instance is executed and its output matches the reference."""
record = _grade()
assert record["n_instances"] > 0, "no instance completed: %s" % record["failure"]
bad = [i for i, r in enumerate(record["per_instance"]) if not r["equivalent"]]
assert not bad, (
"outputs differ from the reference on instance(s) %s of %d (tolerances: "
"max abs <= %g, relative Frobenius <= %g)"
% (bad, record["n_instances"], grader_core.ABS_TOL, grader_core.REL_TOL))
assert record["valid"], "measurement did not complete: %s" % record["failure"]
def test_speedup_metric_is_recorded():
"""The geometric-mean speedup is measured and written to metric.json."""
record = _grade()
assert os.path.isfile(os.path.join(LOG_DIR, "metric.json"))
print("instances=%d equivalent=%d geometric-mean speedup=%.4f"
% (record["n_instances"], record["n_equivalent"], record["metric"]))
ratios = sorted(r["ratio"] for r in record["per_instance"])
if ratios:
print("per-instance speedup: min %.4f median %.4f max %.4f"
% (ratios[0], ratios[len(ratios) // 2], ratios[-1]))
if PRIVATE:
for r in record["per_instance"]:
print(" seed %6d T=%-4d d=%-5d L=%-3d ref %8.2f ms sub %8.2f ms ratio %.4f"
% (r["seed"], r["shape"]["T"], r["shape"]["d_model"],
r["shape"]["n_layers"], r["ref_best_s"] * 1e3,
r["sub_best_s"] * 1e3, r["ratio"]))
assert record["metric"] >= 0.0