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benchflow
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frontierphysics-pr15-evidence

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fp = <zipfile.ZipExtFile name='feature_names.npy' mode='r'>
allow_pickle = False, pickle_kwargs = {'encoding': 'ASCII', 'fix_imports': True}
def read_array(fp, allow_pickle=False, pickle_kwargs=None, *,
max_header_size=_MAX_HEADER_SIZE):
"""
Read an array from an NPY file.
Parameters
----------
fp : file_like object
If this is not a real file object, then this may take extra memory
and time.
allow_pickle : bool, optional
Whether to allow writing pickled data. Default: False
.. versionchanged:: 1.16.3
Made default False in response to CVE-2019-6446.
pickle_kwargs : dict
Additional keyword arguments to pass to pickle.load. These are only
useful when loading object arrays saved on Python 2 when using
Python 3.
max_header_size : int, optional
Maximum allowed size of the header. Large headers may not be safe
to load securely and thus require explicitly passing a larger value.
See :py:func:`ast.literal_eval()` for details.
This option is ignored when `allow_pickle` is passed. In that case
the file is by definition trusted and the limit is unnecessary.
Returns
-------
array : ndarray
The array from the data on disk.
Raises
------
ValueError
If the data is invalid, or allow_pickle=False and the file contains
an object array.
"""
if allow_pickle:
# Effectively ignore max_header_size, since `allow_pickle` indicates
# that the input is fully trusted.
max_header_size = 2**64
version = read_magic(fp)
_check_version(version)
shape, fortran_order, dtype = _read_array_header(
fp, version, max_header_size=max_header_size)
if len(shape) == 0:
count = 1
else:
count = numpy.multiply.reduce(shape, dtype=numpy.int64)
# Now read the actual data.
if dtype.hasobject:
# The array contained Python objects. We need to unpickle the data.
if not allow_pickle:
> raise ValueError("Object arrays cannot be loaded when "
"allow_pickle=False")
E ValueError: Object arrays cannot be loaded when allow_pickle=False
/usr/local/lib/python3.12/site-packages/numpy/lib/format.py:795: ValueError
==================================== PASSES ====================================
=========================== short test summary info ============================
PASSED ../root::test_prediction_alignment_and_persistence
PASSED ../root::test_forecast_matches_independent_svd_ridge
PASSED ../root::test_serialized_model_is_correct_and_reproduces_predictions
PASSED ../root::test_forecast_report_metrics_are_recomputed_correctly
FAILED ../root::test_artifact_schema_and_source_protocol - ValueError: Object...
FAILED ../root::test_information_tensor_matches_independent_knn_recomputation
FAILED ../root::test_peak_arrays_rankings_and_memory_metrics - ValueError: Ob...
FAILED ../root::test_hidden_adversarial_lag_and_overlap_probes - ValueError: ...
=================== 4 failed, 4 passed in 204.67s (0:03:24) ====================
ANTI_TAMPER: verifier integrity preflight passed
============================= test session starts ==============================
platform linux -- Python 3.12.13, pytest-8.4.2, pluggy-1.6.0 -- /usr/local/bin/python3
rootdir: /root
configfile: ../dev/null
plugins: json-ctrf-0.3.5
collecting ... collected 8 items
../root::test_artifact_schema_and_source_protocol PASSED [ 12%]
../root::test_prediction_alignment_and_persistence PASSED [ 25%]
../root::test_forecast_matches_independent_svd_ridge PASSED [ 37%]
../root::test_serialized_model_is_correct_and_reproduces_predictions PASSED [ 50%]
../root::test_forecast_report_metrics_are_recomputed_correctly PASSED [ 62%]
../root::test_information_tensor_matches_independent_knn_recomputation PASSED [ 75%]
../root::test_peak_arrays_rankings_and_memory_metrics PASSED [ 87%]
../root::test_hidden_adversarial_lag_and_overlap_probes PASSED [100%]
==================================== PASSES ====================================
=========================== short test summary info ============================
PASSED ../root::test_artifact_schema_and_source_protocol
PASSED ../root::test_prediction_alignment_and_persistence
PASSED ../root::test_forecast_matches_independent_svd_ridge
PASSED ../root::test_serialized_model_is_correct_and_reproduces_predictions