Comments (14)
WarrenWeckesser
commented on July 20, 2024
1
The issue for the failure of TestOnenormest.test_onenormest_table_6_t_1 is gh-17385.
from scipy.
mdhaber
commented on July 20, 2024
For slow, I get the same failures as above except FAILED scipy/linalg/tests/test_matfuncs.py::TestExpM::test_gh18086 - no new ones. It seems that test_gh18086 is flaky.
However, I had to skip scipy\scipy\sparse\linalg\tests\test_propack.py due to an access violation in test_svdp
from scipy.
mdhaber
commented on July 20, 2024
With SCIPY_XSLOW=1 I get one new failure from sparse/linalg:
_________________ TestOnenormest.test_onenormest_table_6_t_1 __________________
self = <scipy.sparse.linalg.tests.test_onenormest.TestOnenormest object at 0x000001C791846510>
@pytest.mark.xslow
def test_onenormest_table_6_t_1(self):
#TODO this test seems to give estimates that match the table,
#TODO even though no attempt has been made to deal with
#TODO complex numbers in the one-norm estimation.
# This will take multiple seconds if your computer is slow like mine.
# It is stochastic, so the tolerance could be too strict.
np.random.seed(1234)
t = 1
n = 100
itmax = 5
nsamples = 5000
observed = []
expected = []
nmult_list = []
nresample_list = []
for i in range(nsamples):
A_inv = np.random.rand(n, n) + 1j * np.random.rand(n, n)
A = scipy.linalg.inv(A_inv)
est, v, w, nmults, nresamples = _onenormest_core(A, A.T, t, itmax)
observed.append(est)
expected.append(scipy.linalg.norm(A, 1))
nmult_list.append(nmults)
nresample_list.append(nresamples)
observed = np.array(observed, dtype=float)
expected = np.array(expected, dtype=float)
relative_errors = np.abs(observed - expected) / expected
# check the mean underestimation ratio
underestimation_ratio = observed / expected
underestimation_ratio_mean = np.mean(underestimation_ratio)
assert_(0.90 < underestimation_ratio_mean < 0.99)
# check the required column resamples
max_nresamples = np.max(nresample_list)
assert_equal(max_nresamples, 0)
# check the proportion of norms computed exactly correctly
nexact = np.count_nonzero(relative_errors < 1e-14)
proportion_exact = nexact / float(nsamples)
> assert_(0.7 < proportion_exact < 0.8)
E AssertionError
A = array([[ 1.0543604 +0.03847635j, -0.33208373-0.22861055j,
0.40431944+0.0792976j , ..., -0.05681823-0.97139639... -0.72327521+0.42464523j, ..., 0.86198444+1.35242015j,
-1.4396941 -0.77624368j, -0.03960976-0.01487513j]])
A_inv = array([[0.29119074+0.65104849j, 0.58305885+0.67128938j,
0.06722355+0.93823077j, ..., 0.6889593 +0.84052724j,
...
0.45835081+0.39487713j, ..., 0.39236538+0.22490301j,
0.37966209+0.48231849j, 0.52764845+0.90868658j]])
est = 286.67179442494756
expected = array([ 71.97806709, 70.56821698, 42.24911326, ..., 42.74919002,
71.59204191, 287.08535285])
i = 4999
itmax = 5
max_nresamples = 0
n = 100
nexact = 2781
nmult_list = [5, 7, 4, 6, 7, 4, ...]
nmults = 4
nresample_list = [0, 0, 0, 0, 0, 0, ...]
nresamples = 0
nsamples = 5000
observed = array([ 71.97806709, 70.56821698, 35.59762277, ..., 42.74919002,
63.85697738, 286.67179442])
proportion_exact = 0.5562
relative_errors = array([0.00000000e+00, 2.01377551e-16, 1.57435032e-01, ...,
0.00000000e+00, 1.08043636e-01, 1.44054171e-03])
self = <scipy.sparse.linalg.tests.test_onenormest.TestOnenormest object at 0x000001C791846510>
t = 1
underestimation_ratio = array([1. , 1. , 0.84256497, ..., 1. , 0.89195636,
0.99855946])
underestimation_ratio_mean = 0.9414421444954721
v = array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 0., 0., 0., 0., 0., 0., 0., ...0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.])
w = array([ 1.93101609+4.88613457e-02j, 0.95209743+2.99680743e-01j,
3.85029705-1.27986728e+00j, 1.89775519+4.326...578313 -9.43259458e-01j, 1.87828784-6.22941868e+00j,
0.80356713+1.08910034e+00j, -2.96027481+1.61222120e+00j])
scipy\sparse\linalg\tests\test_onenormest.py:183: AssertionError
And 150 more from scipy.stats.sampling of the form:
_________________ TestNumericalInversePolynomial.test_cdf[x6] _________________
self = <scipy.stats.tests.test_sampling.TestNumericalInversePolynomial object at 0x000001C79A2B0710>
x = [[nan, 0.5, 0.1], [0.2, 0.4, inf], [-inf, 3, 4]]
@pytest.mark.parametrize("x", x)
def test_cdf(self, x):
dist = StandardNormal()
> rng = NumericalInversePolynomial(dist, u_resolution=1e-14)
dist = <scipy.stats.tests.test_sampling.StandardNormal object at 0x000001C92F41E010>
self = <scipy.stats.tests.test_sampling.TestNumericalInversePolynomial object at 0x000001C79A2B0710>
x = [[nan, 0.5, 0.1], [0.2, 0.4, inf], [-inf, 3, 4]]
scipy\stats\tests\test_sampling.py:915:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
unuran_wrapper.pyx:1414: in scipy.stats._unuran.unuran_wrapper.NumericalInversePolynomial.__cinit__
???
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
> ???
E OSError: Failed to open file b'C:\\Users\\matth\\AppData\\Local\\Temp\\scipy-1iyihy7o'
messagestream.pyx:43: OSError
During handling of the above exception, another exception occurred:
cls = <class '_pytest.runner.CallInfo'>
func = <function call_and_report.<locals>.<lambda> at 0x000001C92F3F0680>
when = 'call'
reraise = (<class '_pytest.outcomes.Exit'>, <class 'KeyboardInterrupt'>)
@classmethod
def from_call(
cls,
func: Callable[[], TResult],
when: Literal["collect", "setup", "call", "teardown"],
reraise: Optional[
Union[Type[BaseException], Tuple[Type[BaseException], ...]]
] = None,
) -> "CallInfo[TResult]":
"""Call func, wrapping the result in a CallInfo.
:param func:
The function to call. Called without arguments.
:param when:
The phase in which the function is called.
:param reraise:
Exception or exceptions that shall propagate if raised by the
function, instead of being wrapped in the CallInfo.
"""
excinfo = None
start = timing.time()
precise_start = timing.perf_counter()
try:
> result: Optional[TResult] = func()
cls = <class '_pytest.runner.CallInfo'>
duration = 0.0035343000199645758
excinfo = <ExceptionInfo PytestUnraisableExceptionWarning('Exception ignored in: \'scipy._lib.messagestream.MessageStream.__deal...m cannot find the file specified: b\'C:\\\\Users\\\\matth\\\\AppData\\\\Local\\\\Temp\\\\scipy-1iyihy7o\'\n') tblen=12>
func = <function call_and_report.<locals>.<lambda> at 0x000001C92F3F0680>
precise_start = 528360.9868457
precise_stop = 528360.99038
reraise = (<class '_pytest.outcomes.Exit'>, <class 'KeyboardInterrupt'>)
result = None
start = 1716820806.2819302
stop = 1716820806.2849226
when = 'call'
..\miniforge3\envs\scipy-dev\Lib\site-packages\_pytest\runner.py:341:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
..\miniforge3\envs\scipy-dev\Lib\site-packages\_pytest\runner.py:241: in <lambda>
lambda: runtest_hook(item=item, **kwds), when=when, reraise=reraise
item = <Function test_cdf[x6]>
kwds = {}
runtest_hook = <HookCaller 'pytest_runtest_call'>
..\miniforge3\envs\scipy-dev\Lib\site-packages\pluggy\_hooks.py:513: in __call__
return self._hookexec(self.name, self._hookimpls.copy(), kwargs, firstresult)
firstresult = False
kwargs = {'item': <Function test_cdf[x6]>}
self = <HookCaller 'pytest_runtest_call'>
..\miniforge3\envs\scipy-dev\Lib\site-packages\pluggy\_manager.py:120: in _hookexec
return self._inner_hookexec(hook_name, methods, kwargs, firstresult)
firstresult = False
hook_name = 'pytest_runtest_call'
kwargs = {'item': <Function test_cdf[x6]>}
methods = [<HookImpl plugin_name='runner', plugin=<module '_pytest.runner' from 'C:\\Users\\matth\\miniforge3\\envs\\scipy-dev\\...e>>, <HookImpl plugin_name='logging-plugin', plugin=<_pytest.logging.LoggingPlugin object at 0x000001C743F16110>>, ...]
self = <_pytest.config.PytestPluginManager object at 0x000001C73E37E350>
..\miniforge3\envs\scipy-dev\Lib\site-packages\_pytest\threadexception.py:87: in pytest_runtest_call
yield from thread_exception_runtest_hook()
..\miniforge3\envs\scipy-dev\Lib\site-packages\_pytest\threadexception.py:63: in thread_exception_runtest_hook
yield
cm = <_pytest.threadexception.catch_threading_exception object at 0x000001C92F41C910>
..\miniforge3\envs\scipy-dev\Lib\site-packages\_pytest\unraisableexception.py:90: in pytest_runtest_call
yield from unraisable_exception_runtest_hook()
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
def unraisable_exception_runtest_hook() -> Generator[None, None, None]:
with catch_unraisable_exception() as cm:
try:
yield
finally:
if cm.unraisable:
if cm.unraisable.err_msg is not None:
err_msg = cm.unraisable.err_msg
else:
err_msg = "Exception ignored in"
msg = f"{err_msg}: {cm.unraisable.object!r}\n\n"
msg += "".join(
traceback.format_exception(
cm.unraisable.exc_type,
cm.unraisable.exc_value,
cm.unraisable.exc_traceback,
)
)
> warnings.warn(pytest.PytestUnraisableExceptionWarning(msg))
E pytest.PytestUnraisableExceptionWarning: Exception ignored in: 'scipy._lib.messagestream.MessageStream.__dealloc__'
E
E Traceback (most recent call last):
E File "messagestream.pyx", line 91, in scipy._lib.messagestream.MessageStream.close
E FileNotFoundError: [WinError 2] The system cannot find the file specified: b'C:\\Users\\matth\\AppData\\Local\\Temp\\scipy-1iyihy7o'
cm = <_pytest.unraisableexception.catch_unraisable_exception object at 0x000001C92F41D9D0>
err_msg = 'Exception ignored in'
msg = "Exception ignored in: 'scipy._lib.messagestream.MessageStream.__dealloc__'\n\nTraceback (most recent call last):\n F... 2] The system cannot find the file specified: b'C:\\\\Users\\\\matth\\\\AppData\\\\Local\\\\Temp\\\\scipy-1iyihy7o'\n"
..\miniforge3\envs\scipy-dev\Lib\site-packages\_pytest\unraisableexception.py:80: PytestUnraisableExceptionWarning
---------------------------- Captured stderr call -----------------------------
Traceback (most recent call last):
File "messagestream.pyx", line 91, in scipy._lib.messagestream.MessageStream.close
FileNotFoundError: [WinError 2] The system cannot find the file specified: b'C:\\Users\\matth\\AppData\\Local\\Temp\\scipy-1iyihy7o'
I think something like that has been reported before with the scipy.stats.sampling tests. Update: may be related to gh-17360.
from scipy.
mdhaber
commented on July 20, 2024
The "Found Intel OpenMP ('libiomp') and LLVM OpenMP ('libomp')" warning suggests something is wrong with my setup, but at this point I don't think I deviate from the documentation. I do have a few other packages installed in my environment for array API testing, etc., if that could be the culprit.
from scipy.
mdhaber
commented on July 20, 2024
gh-18736 reports a failure of test_hermitian_modes, but my problem is different (hangs).
from scipy.
mdhaber
commented on July 20, 2024
The test_gh18086 failure is indeed flaky, and it seems that is the nature of the bug it is testing. I'll comment in gh-18086.
Also, it appears that test_import_cycles isn't hanging for me anymore, so that's good.
from scipy.
rgommers
commented on July 20, 2024
The "Found Intel OpenMP ('libiomp') and LLVM OpenMP ('libomp')" warning suggests something is wrong with my setup, but at this point I don't think I deviate from the documentation.
Are you by any chance using numpy from the defaults channel? That is built against MKL, which would explain how Intel OpenMP gets pulled in. I'm not sure what else could be doing that.
from scipy.
mdhaber
commented on July 20, 2024
I don't think so. I had to rebuild my environment yesterday after gh-15321 (I'll try to provide more information next time this happens... probably an editable install thing), so this may not be exactly what I performed the tests with, but:
(scipy-dev) C:\Users\matth\scipy>mamba list
# packages in environment at C:\Users\matth\miniforge3\envs\scipy-dev:
#
# Name Version Build Channel
accessible-pygments 0.0.4 pyhd8ed1ab_0 conda-forge
alabaster 0.7.16 pyhd8ed1ab_0 conda-forge
anyio 4.3.0 pyhd8ed1ab_0 conda-forge
argon2-cffi 23.1.0 pyhd8ed1ab_0 conda-forge
argon2-cffi-bindings 21.2.0 py312he70551f_4 conda-forge
array-api-compat 1.7 pyhd8ed1ab_0 conda-forge
array-api-strict 1.1.1 pyhd8ed1ab_0 conda-forge
arrow 1.3.0 pyhd8ed1ab_0 conda-forge
asttokens 2.4.1 pyhd8ed1ab_0 conda-forge
asv 0.6.3 py312h53d5487_0 conda-forge
asv_runner 0.2.1 pyhd8ed1ab_0 conda-forge
async-lru 2.0.4 pyhd8ed1ab_0 conda-forge
attrs 23.2.0 pyh71513ae_0 conda-forge
babel 2.14.0 pyhd8ed1ab_0 conda-forge
backports.zoneinfo 0.2.1 py312h2e8e312_8 conda-forge
beautifulsoup4 4.12.3 pyha770c72_0 conda-forge
beniget 0.4.1 pyhd8ed1ab_0 conda-forge
bleach 6.1.0 pyhd8ed1ab_0 conda-forge
brotli 1.1.0 hcfcfb64_1 conda-forge
brotli-bin 1.1.0 hcfcfb64_1 conda-forge
brotli-python 1.1.0 py312h53d5487_1 conda-forge
bzip2 1.0.8 hcfcfb64_5 conda-forge
ca-certificates 2024.2.2 h56e8100_0 conda-forge
cached-property 1.5.2 hd8ed1ab_1 conda-forge
cached_property 1.5.2 pyha770c72_1 conda-forge
certifi 2024.2.2 pyhd8ed1ab_0 conda-forge
cffi 1.16.0 py312he70551f_0 conda-forge
charset-normalizer 3.3.2 pyhd8ed1ab_0 conda-forge
clang 18.1.6 default_hb53fc94_0 conda-forge
clang-18 18.1.6 default_h3a3e6c3_0 conda-forge
clangxx 18.1.6 default_h3a3e6c3_0 conda-forge
click 8.1.7 win_pyh7428d3b_0 conda-forge
cloudpickle 3.0.0 pyhd8ed1ab_0 conda-forge
colorama 0.4.6 pyhd8ed1ab_0 conda-forge
colorlog 6.8.2 py312h2e8e312_0 conda-forge
comm 0.2.2 pyhd8ed1ab_0 conda-forge
contourpy 1.2.1 py312h0d7def4_0 conda-forge
coverage 7.5.2 py312h4389bb4_0 conda-forge
cuda-nvrtc 12.5.40 he0c23c2_0 conda-forge
cuda-version 12.5 hd4f0392_3 conda-forge
cupy 13.1.0 py312hbf64fcc_4 conda-forge
cupy-core 13.1.0 py312ha23c19a_4 conda-forge
cycler 0.12.1 pyhd8ed1ab_0 conda-forge
cython 3.0.10 py312h53d5487_0 conda-forge
cython-lint 0.16.2 pyhd8ed1ab_0 conda-forge
debugpy 1.8.1 py312h53d5487_0 conda-forge
decorator 5.1.1 pyhd8ed1ab_0 conda-forge
defusedxml 0.7.1 pyhd8ed1ab_0 conda-forge
distlib 0.3.8 pyhd8ed1ab_0 conda-forge
docutils 0.21.2 pyhd8ed1ab_0 conda-forge
doit 0.36.0 pyhd8ed1ab_0 conda-forge
entrypoints 0.4 pyhd8ed1ab_0 conda-forge
exceptiongroup 1.2.0 pyhd8ed1ab_2 conda-forge
execnet 2.1.1 pyhd8ed1ab_0 conda-forge
executing 2.0.1 pyhd8ed1ab_0 conda-forge
fastrlock 0.8.2 py312h53d5487_2 conda-forge
filelock 3.14.0 pyhd8ed1ab_0 conda-forge
fonttools 4.52.1 py312h4389bb4_0 conda-forge
fqdn 1.5.1 pyhd8ed1ab_0 conda-forge
freetype 2.12.1 hdaf720e_2 conda-forge
gast 0.5.4 pyhd8ed1ab_0 conda-forge
glib 2.80.2 h0df6a38_0 conda-forge
glib-tools 2.80.2 h2f9d560_0 conda-forge
gmpy2 2.1.5 py312h73d75c0_1 conda-forge
greenlet 3.0.3 py312h53d5487_0 conda-forge
gst-plugins-base 1.24.3 hba88be7_0 conda-forge
gstreamer 1.24.3 h5006eae_0 conda-forge
h11 0.14.0 pyhd8ed1ab_0 conda-forge
h2 4.1.0 pyhd8ed1ab_0 conda-forge
hpack 4.0.0 pyh9f0ad1d_0 conda-forge
httpcore 1.0.5 pyhd8ed1ab_0 conda-forge
httpx 0.27.0 pyhd8ed1ab_0 conda-forge
hyperframe 6.0.1 pyhd8ed1ab_0 conda-forge
hypothesis 6.102.6 pyha770c72_0 conda-forge
icu 73.2 h63175ca_0 conda-forge
idna 3.7 pyhd8ed1ab_0 conda-forge
imagesize 1.4.1 pyhd8ed1ab_0 conda-forge
importlib-metadata 7.1.0 pyha770c72_0 conda-forge
importlib_metadata 7.1.0 hd8ed1ab_0 conda-forge
importlib_resources 6.4.0 pyhd8ed1ab_0 conda-forge
iniconfig 2.0.0 pyhd8ed1ab_0 conda-forge
ipykernel 6.29.3 pyha63f2e9_0 conda-forge
ipython 8.24.0 pyh7428d3b_0 conda-forge
ipywidgets 8.1.2 pyhd8ed1ab_1 conda-forge
isoduration 20.11.0 pyhd8ed1ab_0 conda-forge
jedi 0.19.1 pyhd8ed1ab_0 conda-forge
jinja2 3.1.4 pyhd8ed1ab_0 conda-forge
json5 0.9.25 pyhd8ed1ab_0 conda-forge
jsonpointer 2.4 py312h2e8e312_3 conda-forge
jsonschema 4.22.0 pyhd8ed1ab_0 conda-forge
jsonschema-specifications 2023.12.1 pyhd8ed1ab_0 conda-forge
jsonschema-with-format-nongpl 4.22.0 pyhd8ed1ab_0 conda-forge
jupyter 1.0.0 pyhd8ed1ab_10 conda-forge
jupyter-cache 1.0.0 pyhd8ed1ab_0 conda-forge
jupyter-lsp 2.2.5 pyhd8ed1ab_0 conda-forge
jupyter_client 8.6.2 pyhd8ed1ab_0 conda-forge
jupyter_console 6.6.3 pyhd8ed1ab_0 conda-forge
jupyter_core 5.7.2 py312h2e8e312_0 conda-forge
jupyter_events 0.10.0 pyhd8ed1ab_0 conda-forge
jupyter_server 2.14.0 pyhd8ed1ab_0 conda-forge
jupyter_server_terminals 0.5.3 pyhd8ed1ab_0 conda-forge
jupyterlab 4.2.1 pyhd8ed1ab_0 conda-forge
jupyterlab_pygments 0.3.0 pyhd8ed1ab_1 conda-forge
jupyterlab_server 2.27.2 pyhd8ed1ab_0 conda-forge
jupyterlab_widgets 3.0.10 pyhd8ed1ab_0 conda-forge
jupyterlite-core 0.3.0 pyhd8ed1ab_0 conda-forge
jupyterlite-sphinx 0.15.0 pyhd8ed1ab_0 conda-forge
jupytext 1.16.2 pyhd8ed1ab_1 conda-forge
kiwisolver 1.4.5 py312h0d7def4_1 conda-forge
krb5 1.21.2 heb0366b_0 conda-forge
lcms2 2.16 h67d730c_0 conda-forge
lerc 4.0.0 h63175ca_0 conda-forge
libblas 3.9.0 22_win64_openblas conda-forge
libbrotlicommon 1.1.0 hcfcfb64_1 conda-forge
libbrotlidec 1.1.0 hcfcfb64_1 conda-forge
libbrotlienc 1.1.0 hcfcfb64_1 conda-forge
libcblas 3.9.0 22_win64_openblas conda-forge
libclang13 18.1.6 default_hf64faad_0 conda-forge
libcublas 12.5.2.13 he0c23c2_0 conda-forge
libcufft 11.2.3.18 he0c23c2_0 conda-forge
libcurand 10.3.6.39 he0c23c2_0 conda-forge
libcusolver 11.6.2.40 he0c23c2_0 conda-forge
libcusparse 12.4.1.24 he0c23c2_0 conda-forge
libdeflate 1.20 hcfcfb64_0 conda-forge
libexpat 2.6.2 h63175ca_0 conda-forge
libffi 3.4.2 h8ffe710_5 conda-forge
libflang 5.0.0 h6538335_20180525 conda-forge
libglib 2.80.2 h0df6a38_0 conda-forge
libiconv 1.17 hcfcfb64_2 conda-forge
libintl 0.22.5 h5728263_2 conda-forge
libintl-devel 0.22.5 h5728263_2 conda-forge
libjpeg-turbo 3.0.0 hcfcfb64_1 conda-forge
liblapack 3.9.0 22_win64_openblas conda-forge
libnvjitlink 12.5.40 he0c23c2_0 conda-forge
libogg 1.3.4 h8ffe710_1 conda-forge
libopenblas 0.3.27 pthreads_hc140b1d_0 conda-forge
libpng 1.6.43 h19919ed_0 conda-forge
libsodium 1.0.18 h8d14728_1 conda-forge
libsqlite 3.45.3 hcfcfb64_0 conda-forge
libtiff 4.6.0 hddb2be6_3 conda-forge
libvorbis 1.3.7 h0e60522_0 conda-forge
libwebp-base 1.4.0 hcfcfb64_0 conda-forge
libxcb 1.15 hcd874cb_0 conda-forge
libzlib 1.2.13 hcfcfb64_5 conda-forge
llvm-meta 5.0.0 0 conda-forge
m2w64-gcc-libgfortran 5.3.0 6 conda-forge
m2w64-gcc-libs 5.3.0 7 conda-forge
m2w64-gcc-libs-core 5.3.0 7 conda-forge
m2w64-gmp 6.1.0 2 conda-forge
m2w64-libwinpthread-git 5.0.0.4634.697f757 2 conda-forge
markdown-it-py 3.0.0 pyhd8ed1ab_0 conda-forge
markupsafe 2.1.5 py312he70551f_0 conda-forge
matplotlib 3.8.4 py312h2e8e312_2 conda-forge
matplotlib-base 3.8.4 py312hfee7060_2 conda-forge
matplotlib-inline 0.1.7 pyhd8ed1ab_0 conda-forge
mdit-py-plugins 0.4.1 pyhd8ed1ab_0 conda-forge
mdurl 0.1.2 pyhd8ed1ab_0 conda-forge
meson 1.4.0 pyhd8ed1ab_0 conda-forge
meson-python 0.16.0 pyh0c530f3_0 conda-forge
mistune 3.0.2 pyhd8ed1ab_0 conda-forge
mpc 1.3.1 h4ff82f8_0 conda-forge
mpfr 4.2.1 h64bf75a_1 conda-forge
mpir 3.0.0 he025d50_1002 conda-forge
mpmath 1.3.0 pyhd8ed1ab_0 conda-forge
msys2-conda-epoch 20160418 1 conda-forge
munkres 1.1.4 pyh9f0ad1d_0 conda-forge
mypy 1.10.0 py312h4389bb4_0 conda-forge
mypy_extensions 1.0.0 pyha770c72_0 conda-forge
myst-nb 1.1.0 pyhd8ed1ab_0 conda-forge
myst-parser 3.0.1 pyhd8ed1ab_0 conda-forge
nbclient 0.10.0 pyhd8ed1ab_0 conda-forge
nbconvert 7.16.4 hd8ed1ab_0 conda-forge
nbconvert-core 7.16.4 pyhd8ed1ab_0 conda-forge
nbconvert-pandoc 7.16.4 hd8ed1ab_0 conda-forge
nbformat 5.10.4 pyhd8ed1ab_0 conda-forge
nest-asyncio 1.6.0 pyhd8ed1ab_0 conda-forge
ninja 1.12.1 hc790b64_0 conda-forge
notebook 7.2.0 pyhd8ed1ab_0 conda-forge
notebook-shim 0.2.4 pyhd8ed1ab_0 conda-forge
numpy 1.26.4 py312h8753938_0 conda-forge
numpydoc 1.7.0 pyhd8ed1ab_0 conda-forge
openblas 0.3.27 pthreads_h3721920_0 conda-forge
openjpeg 2.5.2 h3d672ee_0 conda-forge
openmp 5.0.0 vc14_1 conda-forge
openssl 3.3.0 h2466b09_3 conda-forge
overrides 7.7.0 pyhd8ed1ab_0 conda-forge
packaging 24.0 pyhd8ed1ab_0 conda-forge
pandoc 3.2 h57928b3_0 conda-forge
pandocfilters 1.5.0 pyhd8ed1ab_0 conda-forge
parso 0.8.4 pyhd8ed1ab_0 conda-forge
pcre2 10.43 h17e33f8_0 conda-forge
pickleshare 0.7.5 py_1003 conda-forge
pillow 10.3.0 py312h6f6a607_0 conda-forge
pip 24.0 pyhd8ed1ab_0 conda-forge
pkg-config 0.29.2 h2bf4dc2_1008 conda-forge
pkgutil-resolve-name 1.3.10 pyhd8ed1ab_1 conda-forge
platformdirs 4.2.2 pyhd8ed1ab_0 conda-forge
pluggy 1.5.0 pyhd8ed1ab_0 conda-forge
ply 3.11 pyhd8ed1ab_2 conda-forge
pooch 1.8.1 pyhd8ed1ab_0 conda-forge
prometheus_client 0.20.0 pyhd8ed1ab_0 conda-forge
prompt-toolkit 3.0.42 pyha770c72_0 conda-forge
prompt_toolkit 3.0.42 hd8ed1ab_0 conda-forge
psutil 5.9.8 py312he70551f_0 conda-forge
pthread-stubs 0.4 hcd874cb_1001 conda-forge
pure_eval 0.2.2 pyhd8ed1ab_0 conda-forge
pybind11 2.12.0 py312h0d7def4_0 conda-forge
pybind11-global 2.12.0 py312h0d7def4_0 conda-forge
pycodestyle 2.11.1 pyhd8ed1ab_0 conda-forge
pycparser 2.22 pyhd8ed1ab_0 conda-forge
pydata-sphinx-theme 0.15.2 pyhd8ed1ab_0 conda-forge
pydevtool 0.3.0 pyhd8ed1ab_0 conda-forge
pygments 2.18.0 pyhd8ed1ab_0 conda-forge
pympler 1.0.1 pyhd8ed1ab_0 conda-forge
pyparsing 3.1.2 pyhd8ed1ab_0 conda-forge
pyproject-metadata 0.8.0 pyhd8ed1ab_0 conda-forge
pyqt 5.15.9 py312he09f080_5 conda-forge
pyqt5-sip 12.12.2 py312h53d5487_5 conda-forge
pysocks 1.7.1 pyh0701188_6 conda-forge
pytest 8.2.1 pyhd8ed1ab_0 conda-forge
pytest-cov 5.0.0 pyhd8ed1ab_0 conda-forge
pytest-fail-slow 0.5.0 pyhd8ed1ab_0 conda-forge
pytest-skip-slow 0.0.5 pyhd8ed1ab_0 conda-forge
pytest-timeout 2.3.1 pyhd8ed1ab_1 conda-forge
pytest-xdist 3.5.0 pyhd8ed1ab_0 conda-forge
python 3.12.3 h2628c8c_0_cpython conda-forge
python-dateutil 2.9.0 pyhd8ed1ab_0 conda-forge
python-fastjsonschema 2.19.1 pyhd8ed1ab_0 conda-forge
python-json-logger 2.0.7 pyhd8ed1ab_0 conda-forge
python_abi 3.12 4_cp312 conda-forge
pythran 0.15.0 py312hd42ba9a_1 conda-forge
pytz 2024.1 pyhd8ed1ab_0 conda-forge
pywin32 306 py312h53d5487_2 conda-forge
pywinpty 2.0.13 py312h53d5487_0 conda-forge
pyyaml 6.0.1 py312he70551f_1 conda-forge
pyzmq 26.0.3 py312hd7027bb_0 conda-forge
qt-main 5.15.8 hcef0176_21 conda-forge
qtconsole-base 5.5.2 pyha770c72_0 conda-forge
qtpy 2.4.1 pyhd8ed1ab_0 conda-forge
referencing 0.35.1 pyhd8ed1ab_0 conda-forge
requests 2.32.2 pyhd8ed1ab_0 conda-forge
rfc3339-validator 0.1.4 pyhd8ed1ab_0 conda-forge
rfc3986-validator 0.1.1 pyh9f0ad1d_0 conda-forge
rich 13.7.1 pyhd8ed1ab_0 conda-forge
rich-click 1.8.2 pyhd8ed1ab_0 conda-forge
rpds-py 0.18.1 py312h2615798_0 conda-forge
ruff 0.4.5 py312h7a6832a_0 conda-forge
scipy 1.14.0.dev0 pypi_0 pypi
send2trash 1.8.3 pyh5737063_0 conda-forge
setuptools 67.1.0 pyhd8ed1ab_0 conda-forge
sip 6.7.12 py312h53d5487_0 conda-forge
six 1.16.0 pyh6c4a22f_0 conda-forge
sniffio 1.3.1 pyhd8ed1ab_0 conda-forge
snowballstemmer 2.2.0 pyhd8ed1ab_0 conda-forge
sortedcontainers 2.4.0 pyhd8ed1ab_0 conda-forge
soupsieve 2.5 pyhd8ed1ab_1 conda-forge
sphinx 7.3.7 pyhd8ed1ab_0 conda-forge
sphinx-design 0.5.0 pyhd8ed1ab_0 conda-forge
sphinxcontrib-applehelp 1.0.8 pyhd8ed1ab_0 conda-forge
sphinxcontrib-devhelp 1.0.6 pyhd8ed1ab_0 conda-forge
sphinxcontrib-htmlhelp 2.0.5 pyhd8ed1ab_0 conda-forge
sphinxcontrib-jsmath 1.0.1 pyhd8ed1ab_0 conda-forge
sphinxcontrib-qthelp 1.0.7 pyhd8ed1ab_0 conda-forge
sphinxcontrib-serializinghtml 1.1.10 pyhd8ed1ab_0 conda-forge
sqlalchemy 2.0.30 py312h4389bb4_0 conda-forge
stack_data 0.6.2 pyhd8ed1ab_0 conda-forge
sympy 1.12 pyh04b8f61_3 conda-forge
tabulate 0.9.0 pyhd8ed1ab_1 conda-forge
terminado 0.18.1 pyh5737063_0 conda-forge
threadpoolctl 3.5.0 pyhc1e730c_0 conda-forge
tinycss2 1.3.0 pyhd8ed1ab_0 conda-forge
tk 8.6.13 h5226925_1 conda-forge
tokenize-rt 5.2.0 pyhd8ed1ab_1 conda-forge
toml 0.10.2 pyhd8ed1ab_0 conda-forge
tomli 2.0.1 pyhd8ed1ab_0 conda-forge
tornado 6.4 py312he70551f_0 conda-forge
traitlets 5.14.3 pyhd8ed1ab_0 conda-forge
types-psutil 5.9.5.6 pyhd8ed1ab_0 conda-forge
types-python-dateutil 2.9.0.20240316 pyhd8ed1ab_0 conda-forge
typing-extensions 4.11.0 hd8ed1ab_0 conda-forge
typing_extensions 4.11.0 pyha770c72_0 conda-forge
typing_utils 0.1.0 pyhd8ed1ab_0 conda-forge
tzdata 2024a h0c530f3_0 conda-forge
ucrt 10.0.22621.0 h57928b3_0 conda-forge
uri-template 1.3.0 pyhd8ed1ab_0 conda-forge
urllib3 2.2.1 pyhd8ed1ab_0 conda-forge
vc 14.3 ha32ba9b_20 conda-forge
vc14_runtime 14.38.33135 h835141b_20 conda-forge
virtualenv 20.26.2 pyhd8ed1ab_0 conda-forge
vs2015_runtime 14.38.33135 h22015db_20 conda-forge
wcwidth 0.2.13 pyhd8ed1ab_0 conda-forge
webcolors 1.13 pyhd8ed1ab_0 conda-forge
webencodings 0.5.1 pyhd8ed1ab_2 conda-forge
websocket-client 1.8.0 pyhd8ed1ab_0 conda-forge
wheel 0.43.0 pyhd8ed1ab_1 conda-forge
widgetsnbextension 4.0.10 pyhd8ed1ab_0 conda-forge
win_inet_pton 1.1.0 pyhd8ed1ab_6 conda-forge
winpty 0.4.3 4 conda-forge
xorg-libxau 1.0.11 hcd874cb_0 conda-forge
xorg-libxdmcp 1.1.3 hcd874cb_0 conda-forge
xz 5.2.6 h8d14728_0 conda-forge
yaml 0.2.5 h8ffe710_2 conda-forge
zeromq 4.3.5 he1f189c_4 conda-forge
zipp 3.17.0 pyhd8ed1ab_0 conda-forge
zstd 1.5.6 h0ea2cb4_0 conda-forge
With this environment, running pytest scipy/io/tests/test_mmio.py::test_threadpoolctl, I get:
====================================================== FAILURES =======================================================
_________________________________________ test_threadpoolctl[scipy.io._mmio] __________________________________________
def test_threadpoolctl():
try:
import threadpoolctl
if not hasattr(threadpoolctl, "register"):
pytest.skip("threadpoolctl too old")
return
except ImportError:
pytest.skip("no threadpoolctl")
return
with threadpoolctl.threadpool_limits(limits=4):
> assert_equal(fmm.PARALLELISM, 4)
E AssertionError:
E Items are not equal:
E ACTUAL: 0
E DESIRED: 4
threadpoolctl = <module 'threadpoolctl' from 'C:\\Users\\matth\\miniforge3\\envs\\scipy-dev\\Lib\\site-packages\\threadpoolctl.py'>
scipy\io\tests\test_mmio.py:800: AssertionError
__________________________________ test_threadpoolctl[scipy.io._fast_matrix_market] ___________________________________
def test_threadpoolctl():
try:
import threadpoolctl
if not hasattr(threadpoolctl, "register"):
pytest.skip("threadpoolctl too old")
return
except ImportError:
pytest.skip("no threadpoolctl")
return
with threadpoolctl.threadpool_limits(limits=4):
> assert_equal(fmm.PARALLELISM, 4)
E AssertionError:
E Items are not equal:
E ACTUAL: 0
E DESIRED: 4
threadpoolctl = <module 'threadpoolctl' from 'C:\\Users\\matth\\miniforge3\\envs\\scipy-dev\\Lib\\site-packages\\threadpoolctl.py'>
scipy\io\tests\test_mmio.py:800: AssertionError
=============================================== short test summary info ===============================================
FAILED scipy/io/tests/test_mmio.py::test_threadpoolctl[scipy.io._mmio] - AssertionError:
FAILED scipy/io/tests/test_mmio.py::test_threadpoolctl[scipy.io._fast_matrix_market] - AssertionError:
================================================== 2 failed in 0.96s ==================================================
from scipy.
rgommers
commented on July 20, 2024
With this environment, running
pytest scipy/io/tests/test_mmio.py::test_threadpoolctl, I get:
Ah that is a different failure - no sign of the OpenMP conflict once all packages come from conda-forge. This may be a genuine threadpoolctl issue on Windows (the custom controller thing that fast_matrix_market uses is fairly new).
from scipy.
mdhaber
commented on July 20, 2024
If after creating the environment with environment.yml I had tried to install pytorch like this, would that explain it? (I think I had used conda before to set up the environment rather than mamba like this time.)
(scipy-dev) C:\Users\matth\scipy>conda install -c conda-forge pytorch
Collecting package metadata (current_repodata.json): done
Solving environment: done
==> WARNING: A newer version of conda exists. <==
current version: 23.3.1
latest version: 24.5.0
Please update conda by running
$ conda update -n base -c conda-forge conda
Or to minimize the number of packages updated during conda update use
conda install conda=24.5.0
## Package Plan ##
environment location: C:\Users\matth\miniforge3\envs\scipy-dev
added / updated specs:
- pytorch
The following packages will be downloaded:
package | build
---------------------------|-----------------
fsspec-2024.5.0 | pyhff2d567_0 211 KB conda-forge
libhwloc-2.10.0 |default_h8125262_1001 2.3 MB conda-forge
libxml2-2.12.7 | h283a6d9_0 1.5 MB conda-forge
mkl-service-2.4.1 | py312hd947a6f_0 60 KB conda-forge
pytorch-2.2.0 |cpu_py312h746a3fd_0 111.8 MB
tbb-2021.12.0 | hc790b64_1 158 KB conda-forge
------------------------------------------------------------
Total: 116.0 MB
The following NEW packages will be INSTALLED:
blas pkgs/main/win-64::blas-1.0-mkl
fsspec conda-forge/noarch::fsspec-2024.5.0-pyhff2d567_0
intel-openmp pkgs/main/win-64::intel-openmp-2023.1.0-h59b6b97_46320
libhwloc conda-forge/win-64::libhwloc-2.10.0-default_h8125262_1001
libuv conda-forge/win-64::libuv-1.48.0-hcfcfb64_0
libxml2 conda-forge/win-64::libxml2-2.12.7-h283a6d9_0
mkl conda-forge/win-64::mkl-2023.2.0-h6a75c08_50497
mkl-service conda-forge/win-64::mkl-service-2.4.1-py312hd947a6f_0
networkx conda-forge/noarch::networkx-3.3-pyhd8ed1ab_1
pthreads-win32 conda-forge/win-64::pthreads-win32-2.9.1-hfa6e2cd_3
pytorch pkgs/main/win-64::pytorch-2.2.0-cpu_py312h746a3fd_0
tbb conda-forge/win-64::tbb-2021.12.0-hc790b64_1
The following packages will be DOWNGRADED:
libblas 3.9.0-22_win64_openblas --> 3.9.0-20_win64_mkl
libcblas 3.9.0-22_win64_openblas --> 3.9.0-20_win64_mkl
liblapack 3.9.0-22_win64_openblas --> 3.9.0-20_win64_mkl```
</details>from scipy.
rgommers
commented on July 20, 2024
Yes, that would definitely explain it - PyTorch depends on MKL. It may also explain also some of the other failures (test_complex_dotc & co), since that's about Fortran ABI and OpenBLAS and MKL ABI's do not match.
Installing complex packages in an existing env is inherently a bit fragile (not just for conda, also for pypi/wheels). What I do instead is edit environment.yml to add the new dependencies I want, rename the env (e.g., scipy-dev-torch in this case) and then run mamba env create -f environment.yml. That should avoid this kind of problem. Downloads are cached, so it also shouldn't increase total download size by too much.
from scipy.
mdhaber
commented on July 20, 2024
I know it's fragile - so fragile that last time I tried, I couldn't add PyTorch to environment.yml without conflicts : ) I could install it after the fact, though, so I went ahead, since I have work to do.
I'll go ahead and re-run those test with this new environment, though.
from scipy.
mdhaber
commented on July 20, 2024
In the pristine environment.yml environment (except for the fact that I removed compilers and added cupy, sympy, jupyter, pytest-fail-slow, pytest-skip-slow, and array-api-compat before creating the environment), I get the same failures, hangs, and access violations except:
scipy/sparse/linalg/_isolve/tests/test_iterative.py::test_x0_equals_Mbpasses- None of the 150
scipy.stats.samplingfailures
When I add pytorch with mamber install -c conda-forge pytorch, the failures of scipy/io/tests/test_mmio.py::test_threadpoolctl turn into RuntimeWarnings about Intel and LLVM OpenMP, and the scipy/sparse/linalg/_isolve/tests/test_iterative.py::test_x0_equals_Mb failure comes back. I still don't get the scipy.stats.sampling errors, though.
from scipy.
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from scipy.