peacock-data-public-datasets-idc-llm_eval
/
env-llmeval
/lib
/python3.10
/site-packages
/scipy
/conftest.py
| # Pytest customization | |
| import json | |
| import os | |
| import warnings | |
| import tempfile | |
| import numpy as np | |
| import numpy.testing as npt | |
| import pytest | |
| import hypothesis | |
| from scipy._lib._fpumode import get_fpu_mode | |
| from scipy._lib._testutils import FPUModeChangeWarning | |
| from scipy._lib import _pep440 | |
| from scipy._lib._array_api import SCIPY_ARRAY_API, SCIPY_DEVICE | |
| def pytest_configure(config): | |
| config.addinivalue_line("markers", | |
| "slow: Tests that are very slow.") | |
| config.addinivalue_line("markers", | |
| "xslow: mark test as extremely slow (not run unless explicitly requested)") | |
| config.addinivalue_line("markers", | |
| "xfail_on_32bit: mark test as failing on 32-bit platforms") | |
| try: | |
| import pytest_timeout # noqa:F401 | |
| except Exception: | |
| config.addinivalue_line( | |
| "markers", 'timeout: mark a test for a non-default timeout') | |
| config.addinivalue_line("markers", | |
| "skip_if_array_api(*backends, reasons=None, np_only=False, cpu_only=False): " | |
| "mark the desired skip configuration for the `skip_if_array_api` fixture.") | |
| def _get_mark(item, name): | |
| if _pep440.parse(pytest.__version__) >= _pep440.Version("3.6.0"): | |
| mark = item.get_closest_marker(name) | |
| else: | |
| mark = item.get_marker(name) | |
| return mark | |
| def pytest_runtest_setup(item): | |
| mark = _get_mark(item, "xslow") | |
| if mark is not None: | |
| try: | |
| v = int(os.environ.get('SCIPY_XSLOW', '0')) | |
| except ValueError: | |
| v = False | |
| if not v: | |
| pytest.skip("very slow test; " | |
| "set environment variable SCIPY_XSLOW=1 to run it") | |
| mark = _get_mark(item, 'xfail_on_32bit') | |
| if mark is not None and np.intp(0).itemsize < 8: | |
| pytest.xfail(f'Fails on our 32-bit test platform(s): {mark.args[0]}') | |
| # Older versions of threadpoolctl have an issue that may lead to this | |
| # warning being emitted, see gh-14441 | |
| with npt.suppress_warnings() as sup: | |
| sup.filter(pytest.PytestUnraisableExceptionWarning) | |
| try: | |
| from threadpoolctl import threadpool_limits | |
| HAS_THREADPOOLCTL = True | |
| except Exception: # observed in gh-14441: (ImportError, AttributeError) | |
| # Optional dependency only. All exceptions are caught, for robustness | |
| HAS_THREADPOOLCTL = False | |
| if HAS_THREADPOOLCTL: | |
| # Set the number of openmp threads based on the number of workers | |
| # xdist is using to prevent oversubscription. Simplified version of what | |
| # sklearn does (it can rely on threadpoolctl and its builtin OpenMP helper | |
| # functions) | |
| try: | |
| xdist_worker_count = int(os.environ['PYTEST_XDIST_WORKER_COUNT']) | |
| except KeyError: | |
| # raises when pytest-xdist is not installed | |
| return | |
| if not os.getenv('OMP_NUM_THREADS'): | |
| max_openmp_threads = os.cpu_count() // 2 # use nr of physical cores | |
| threads_per_worker = max(max_openmp_threads // xdist_worker_count, 1) | |
| try: | |
| threadpool_limits(threads_per_worker, user_api='blas') | |
| except Exception: | |
| # May raise AttributeError for older versions of OpenBLAS. | |
| # Catch any error for robustness. | |
| return | |
| def check_fpu_mode(request): | |
| """ | |
| Check FPU mode was not changed during the test. | |
| """ | |
| old_mode = get_fpu_mode() | |
| yield | |
| new_mode = get_fpu_mode() | |
| if old_mode != new_mode: | |
| warnings.warn(f"FPU mode changed from {old_mode:#x} to {new_mode:#x} during " | |
| "the test", | |
| category=FPUModeChangeWarning, stacklevel=0) | |
| # Array API backend handling | |
| xp_available_backends = {'numpy': np} | |
| if SCIPY_ARRAY_API and isinstance(SCIPY_ARRAY_API, str): | |
| # fill the dict of backends with available libraries | |
| try: | |
| import array_api_strict | |
| xp_available_backends.update({'array_api_strict': array_api_strict}) | |
| except ImportError: | |
| pass | |
| try: | |
| import torch # type: ignore[import] | |
| xp_available_backends.update({'pytorch': torch}) | |
| # can use `mps` or `cpu` | |
| torch.set_default_device(SCIPY_DEVICE) | |
| except ImportError: | |
| pass | |
| try: | |
| import cupy # type: ignore[import] | |
| xp_available_backends.update({'cupy': cupy}) | |
| except ImportError: | |
| pass | |
| # by default, use all available backends | |
| if SCIPY_ARRAY_API.lower() not in ("1", "true"): | |
| SCIPY_ARRAY_API_ = json.loads(SCIPY_ARRAY_API) | |
| if 'all' in SCIPY_ARRAY_API_: | |
| pass # same as True | |
| else: | |
| # only select a subset of backend by filtering out the dict | |
| try: | |
| xp_available_backends = { | |
| backend: xp_available_backends[backend] | |
| for backend in SCIPY_ARRAY_API_ | |
| } | |
| except KeyError: | |
| msg = f"'--array-api-backend' must be in {xp_available_backends.keys()}" | |
| raise ValueError(msg) | |
| if 'cupy' in xp_available_backends: | |
| SCIPY_DEVICE = 'cuda' | |
| array_api_compatible = pytest.mark.parametrize("xp", xp_available_backends.values()) | |
| def skip_if_array_api(xp, request): | |
| """ | |
| Skip based on the ``skip_if_array_api`` marker. | |
| Parameters | |
| ---------- | |
| *backends : tuple | |
| Backends to skip, e.g. ``("array_api_strict", "torch")``. | |
| These are overriden when ``np_only`` is ``True``, and are not | |
| necessary to provide for non-CPU backends when ``cpu_only`` is ``True``. | |
| reasons : list, optional | |
| A list of reasons for each skip. When ``np_only`` is ``True``, | |
| this should be a singleton list. Otherwise, this should be a list | |
| of reasons, one for each corresponding backend in ``backends``. | |
| If unprovided, default reasons are used. Note that it is not possible | |
| to specify a custom reason with ``cpu_only``. Default: ``None``. | |
| np_only : bool, optional | |
| When ``True``, the test is skipped for all backends other | |
| than the default NumPy backend. There is no need to provide | |
| any ``backends`` in this case. To specify a reason, pass a | |
| singleton list to ``reasons``. Default: ``False``. | |
| cpu_only : bool, optional | |
| When ``True``, the test is skipped on non-CPU devices. | |
| There is no need to provide any ``backends`` in this case, | |
| but any ``backends`` will also be skipped on the CPU. | |
| Default: ``False``. | |
| """ | |
| if "skip_if_array_api" not in request.keywords: | |
| return | |
| backends = request.keywords["skip_if_array_api"].args | |
| kwargs = request.keywords["skip_if_array_api"].kwargs | |
| np_only = kwargs.get("np_only", False) | |
| cpu_only = kwargs.get("cpu_only", False) | |
| if np_only: | |
| reasons = kwargs.get("reasons", ["do not run with non-NumPy backends."]) | |
| reason = reasons[0] | |
| if xp.__name__ != 'numpy': | |
| pytest.skip(reason=reason) | |
| return | |
| if cpu_only: | |
| reason = "do not run with `SCIPY_ARRAY_API` set and not on CPU" | |
| if SCIPY_ARRAY_API and SCIPY_DEVICE != 'cpu': | |
| if xp.__name__ == 'cupy': | |
| pytest.skip(reason=reason) | |
| elif xp.__name__ == 'torch': | |
| if 'cpu' not in torch.empty(0).device.type: | |
| pytest.skip(reason=reason) | |
| if backends is not None: | |
| reasons = kwargs.get("reasons", False) | |
| for i, backend in enumerate(backends): | |
| if xp.__name__ == backend: | |
| if not reasons: | |
| reason = f"do not run with array API backend: {backend}" | |
| else: | |
| reason = reasons[i] | |
| pytest.skip(reason=reason) | |
| # Following the approach of NumPy's conftest.py... | |
| # Use a known and persistent tmpdir for hypothesis' caches, which | |
| # can be automatically cleared by the OS or user. | |
| hypothesis.configuration.set_hypothesis_home_dir( | |
| os.path.join(tempfile.gettempdir(), ".hypothesis") | |
| ) | |
| # We register two custom profiles for SciPy - for details see | |
| # https://hypothesis.readthedocs.io/en/latest/settings.html | |
| # The first is designed for our own CI runs; the latter also | |
| # forces determinism and is designed for use via scipy.test() | |
| hypothesis.settings.register_profile( | |
| name="nondeterministic", deadline=None, print_blob=True, | |
| ) | |
| hypothesis.settings.register_profile( | |
| name="deterministic", | |
| deadline=None, print_blob=True, database=None, derandomize=True, | |
| suppress_health_check=list(hypothesis.HealthCheck), | |
| ) | |
| # Profile is currently set by environment variable `SCIPY_HYPOTHESIS_PROFILE` | |
| # In the future, it would be good to work the choice into dev.py. | |
| SCIPY_HYPOTHESIS_PROFILE = os.environ.get("SCIPY_HYPOTHESIS_PROFILE", | |
| "deterministic") | |
| hypothesis.settings.load_profile(SCIPY_HYPOTHESIS_PROFILE) | |