chore(deps): update dependency joblib to v1.3.0 - #704

v1.3.0

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• 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_BACKEND environment variable.
  https://github.com/joblib/joblib/pull/13561356

• Fix temporary folder creation in joblib.Parallel on Linux subsystems on Windows
  which do have /dev/shm but don't have the os.statvfs function
  https://github.com/joblib/joblib/issues/13531353

• Drop runtime dependency on distutils. distutils is going away
  in 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 (verion 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_callback in :meth:joblib.Memory.cache, to allow
  custom cache invalidation based on the metadata of the function cahttps://github.com/joblib/joblib/pull/1149ull/1149

• Add a return_as parameter for Parallel, that enables consuming
  results asynchronoushttps://github.com/joblib/joblib/pull/1393ulhttps://github.com/joblib/joblib/pull/1458ib/pull/1458

• Improve the behavior of joblib for n_jobs=1, with simplified
  tracebacks and more efficient running tihttps://github.com/joblib/joblib/pull/1393ull/1393

• Add the parallel_config context manager to allow for more fine-grained
  control over the backend configuration. It should be used in place of the
  parallel_backend context manager. In particular, it has the advantage
  of 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_limit and age_limit in :meth:joblib.Memory.reduce_size
  to 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_limit in Memory as this is not automatically enforced,
  the limit can be directly passed to :meth:joblib.Memory.reduce_size which
  needs to be called to actually enforce the limhttps://github.com/joblib/joblib/pull/1447ull/1447

• Vendor loky 3.4.0 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 nogil support.
  https://github.com/joblib/joblib/pull/139413https://github.com/joblib/joblib/pull/1395ull/1395