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chore(deps): update dependency joblib to v1.4.2#280
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This PR contains the following updates:
==1.2.0->==1.4.2Release Notes
joblib/joblib (joblib)
v1.4.2Compare Source
Due to maintenance issues, 1.4.1 was not valid and we bumped the version to 1.4.2
MemorizedFunc.callwhich needs toreturn the metadata. Also make sure that
NotMemorizedFunc.callreturnan empty dict for metadata for consistenhttps://github.com/joblib/joblib/pull/1576ull/1576
v1.4.0Compare Source
Allow caching co-routines with
Memory.cache.https://github.com/joblib/joblib/pull/894/894
Try to cast
n_jobsto int in parallel and raise an error ifit fails. This means that
n_jobs=2.3will now result ineffective_n_jobs=2instead of failing.https://github.com/joblib/joblib/pull/15391539
Ensure that errors in the task generator given to Parallel's call
are raised in the results consumming threhttps://github.com/joblib/joblib/pull/1491ull/1491
Adjust codebase to NumPy 2.0 by changing
np.NaNtonp.nanand importing
byte_boundsfromnp.lib.array_utils.https://github.com/joblib/joblib/pull/15011501
The parameter
return_asinjoblib.Parallelcan now be set togenerator_unordered. In this case the results will be returned in theorder of task completion rather than the order of submissihttps://github.com/joblib/joblib/pull/1463ull/1463
dask backend now supports
return_as=generatorandreturn_as=generator_unordered.https://github.com/joblib/joblib/pull/15201520
Vendor cloudpickle 3.0.0 and end support for Python 3.7 which has
reached end of lihttps://github.com/joblib/joblib/pull/1487uhttps://github.com/joblib/joblib/pull/1515ib/pull/1515
v1.3.2Compare Source
Fix a regression in
joblib.Parallelintroduced in 1.3.0 whereexplicitly setting
n_jobs=Nonewas not interpreted as "unset".https://github.com/joblib/joblib/pull/14751475
Fix a regression in
joblib.Parallelintroduced in 1.3.0 wherejoblib.Parallellogging methods exposed from inheritance tojoblib.Loggerdidn't work because of missing loggerinitializatihttps://github.com/joblib/joblib/pull/1494ull/1494
Various maintenance updates to the doc, the ci and the test.
https://github.com/joblib/joblib/pull/148014https://github.com/joblib/joblib/pull/1481ulhttps://github.com/joblib/joblib/pull/1476ibhttps://github.com/joblib/joblib/pull/1492joblib/pull/1492
v1.3.1Compare Source
which is compatible with this versihttps://github.com/joblib/joblib/pull/1472ull/1472
v1.3.0Compare Source
Ensure native byte order for memmap arrays in
joblib.load.https://github.com/joblib/joblib/issues/13531353
Add ability to change default Parallel backend in tests by setting the
JOBLIB_TESTS_DEFAULT_PARALLEL_BACKENDenvironment variable.https://github.com/joblib/joblib/pull/13561356
Fix temporary folder creation in
joblib.Parallelon Linux subsystems on Windowswhich do have
/dev/shmbut don't have theos.statvfsfunctionhttps://github.com/joblib/joblib/issues/13531353
Drop runtime dependency on
distutils.distutilsis going awayin Python 3.12 and is deprecated from Python 3.10 onwards. This import
was kept around to avoid breaking scikit-learn, however it's now been
long enough since scikit-learn deployed a fixed (version 1.1 was released
in May 2022) that it should be safe https://github.com/joblib/joblib/pull/1361lib/joblib/pull/1361
A warning is raised when a pickling error occurs during caching operations.
In version 1.5, this warning will be turned into an error. For all other
errors, a new warning has been introduced:
joblib.memory.CacheWarning.https://github.com/joblib/joblib/pull/13591359
Avoid (module, name) collisions when caching nested functions. This fix
changes the module name of nested functions, invalidating caches from
previous versions of https://github.com/joblib/joblib/pull/1374ib/pull/1374
Add
cache_validation_callbackin :meth:joblib.Memory.cache, to allowcustom cache invalidation based on the metadata of the function cahttps://github.com/joblib/joblib/pull/1149ull/1149
Add a
return_asparameter forParallel, that enables consumingresults asynchronoushttps://github.com/joblib/joblib/pull/1393ulhttps://github.com/joblib/joblib/pull/1458ib/pull/1458
Improve the behavior of
joblibforn_jobs=1, with simplifiedtracebacks and more efficient running tihttps://github.com/joblib/joblib/pull/1393ull/1393
Add the
parallel_configcontext manager to allow for more fine-grainedcontrol over the backend configuration. It should be used in place of the
parallel_backendcontext manager. In particular, it has the advantageof not requiring to set a specific backend in the context managhttps://github.com/joblib/joblib/pull/1392ulhttps://github.com/joblib/joblib/pull/1457ib/pull/1457
Add
items_limitandage_limitin :meth:joblib.Memory.reduce_sizeto make it easy to limit the number of items and remove items that have
not been accessed for a long time in thehttps://github.com/joblib/joblib/pull/1200ib/pull/1200
Deprecate
bytes_limitinMemoryas this is not automatically enforced,the limit can be directly passed to :meth:
joblib.Memory.reduce_sizewhichneeds to be called to actually enforce the limhttps://github.com/joblib/joblib/pull/1447ull/1447
Vendor
loky3.4.0 which includes various fixes.https://github.com/joblib/joblib/pull/14221422
Various updates to the documentation and to benchmarking tools.
https://github.com/joblib/joblib/pull/134313https://github.com/joblib/joblib/pull/1348ulhttps://github.com/joblib/joblib/pull/1411ibhttps://github.com/joblib/joblib/pull/1451johttps://github.com/joblib/joblib/pull/1427lihttps://github.com/joblib/joblib/pull/1400/BENCH add benchmark script for n_jobs=1 joblib/joblib#1400
Move project metadata to
pyproject.toml.https://github.com/joblib/joblib/pull/138213https://github.com/joblib/joblib/pull/1433ull/1433
Add more tests to improve python
nogilsupport.https://github.com/joblib/joblib/pull/139413https://github.com/joblib/joblib/pull/1395ull/1395
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