Datasets:
benchflow
/
frontierphysics-pr32-evidence

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test_outputs.py:1425: in staged_submitted_execution
assert_regular_file(
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
path = PosixPath('/root/analyze_protein_strain.py')
description = 'reusable /root/analyze_protein_strain.py'
def assert_regular_file(path: Path, description: str) -> os.stat_result:
> assert path.exists(), f"Missing {description}: {path}"
E AssertionError: Missing reusable /root/analyze_protein_strain.py: /root/analyze_protein_strain.py
E assert False
E + where False = exists()
E + where exists = PosixPath('/root/analyze_protein_strain.py').exists
test_outputs.py:147: AssertionError
________ test_submitted_executable_handles_compact_full_rank_transition ________
def test_submitted_executable_handles_compact_full_rank_transition() -> None:
fixture, metadata = compact_full_rank_fixture()
public = input_data()
assert int(metadata["residue_count"]) == 80
assert int(metadata["residue_count"]) != np.asarray(public["residue_key"]).size
assert {str(value) for value in fixture["residue_key"]}.isdisjoint(str(value) for value in public["residue_key"])
assert {str(value) for value in fixture["segment_key"]}.isdisjoint(str(value) for value in public["segment_key"])
LOGS.mkdir(parents=True, exist_ok=True)
(LOGS / "compact-full-rank-fixture.json").write_text(
json.dumps(metadata, indent=2, sort_keys=True) + "\n",
encoding="utf-8",
)
> artifacts, hidden_reference, hidden_nonaffine = run_submitted_executable(
fixture,
COMPACT_FULL_RANK_RADIUS,
"compact-full-rank",
)
test_outputs.py:1881:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
test_outputs.py:1546: in run_submitted_executable
with staged_submitted_execution(
/usr/local/lib/python3.11/contextlib.py:137: in __enter__
return next(self.gen)
^^^^^^^^^^^^^^
test_outputs.py:1425: in staged_submitted_execution
assert_regular_file(
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
path = PosixPath('/root/analyze_protein_strain.py')
description = 'reusable /root/analyze_protein_strain.py'
def assert_regular_file(path: Path, description: str) -> os.stat_result:
> assert path.exists(), f"Missing {description}: {path}"
E AssertionError: Missing reusable /root/analyze_protein_strain.py: /root/analyze_protein_strain.py
E assert False
E + where False = exists()
E + where exists = PosixPath('/root/analyze_protein_strain.py').exists
test_outputs.py:147: AssertionError
______________ test_public_shape_and_key_special_case_is_rejected ______________
def test_public_shape_and_key_special_case_is_rejected() -> None:
fixture, _ = compact_full_rank_fixture()
> attack_source, public_count, public_key_digest = public_only_special_case_solver_source()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
test_outputs.py:1911:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
test_outputs.py:1604: in public_only_special_case_solver_source
submitted_source = SCRIPT_PATH.read_text(encoding="utf-8")
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
/usr/local/lib/python3.11/pathlib.py:1058: in read_text
with self.open(mode='r', encoding=encoding, errors=errors) as f:
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = PosixPath('/root/analyze_protein_strain.py'), mode = 'r', buffering = -1
encoding = 'utf-8', errors = None, newline = None
def open(self, mode='r', buffering=-1, encoding=None,
errors=None, newline=None):
"""
Open the file pointed by this path and return a file object, as
the built-in open() function does.
"""
if "b" not in mode:
encoding = io.text_encoding(encoding)
> return io.open(self, mode, buffering, encoding, errors, newline)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
E FileNotFoundError: [Errno 2] No such file or directory: '/root/analyze_protein_strain.py'
/usr/local/lib/python3.11/pathlib.py:1044: FileNotFoundError
____________ test_submitted_executable_rejects_rank_deficient_input ____________
def test_submitted_executable_rejects_rank_deficient_input() -> None:
state_a = np.asarray(
[
[0.0, 0.0, 0.0],
[1.0, 0.0, 0.0],
[0.0, 1.0, 0.0],
[1.0, 1.0, 0.0],