🔒 🤖 CI Update lock files for free-threaded CI build(s) 🔒 🤖 - #34804

_ ERROR at call of test_function_no_callback_support[RecordingCallback-processes-2] _
joblib.externals.loky.process_executor._RemoteTraceback: 
"""
Traceback (most recent call last):
  File "/home/runner/miniconda3/envs/testvenv/lib/python3.14t/site-packages/joblib/externals/loky/backend/queues.py", line 159, in _feed
    obj_ = dumps(obj, reducers=reducers)
  File "/home/runner/miniconda3/envs/testvenv/lib/python3.14t/site-packages/joblib/externals/loky/backend/reduction.py", line 214, in dumps
    dump(obj, buf, reducers=reducers, protocol=protocol)
    ~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/runner/miniconda3/envs/testvenv/lib/python3.14t/site-packages/joblib/externals/loky/backend/reduction.py", line 207, in dump
    _LokyPickler(file, reducers=reducers, protocol=protocol).dump(obj)
    ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^
  File "/home/runner/miniconda3/envs/testvenv/lib/python3.14t/site-packages/joblib/externals/cloudpickle/cloudpickle.py", line 1313, in dump
    return super().dump(obj)
           ~~~~~~~~~~~~^^^^^
RuntimeError: list changed size during iteration
when serializing dict item 'record'
when serializing sklearn.callback.tests._common.callbacks.RecordingCallback state
when serializing sklearn.callback.tests._common.callbacks.RecordingCallback object
when serializing list item 0
when serializing dict item '_skl_callbacks'
when serializing sklearn.callback.tests._common.estimators.MaxIterEstimator state
when serializing sklearn.callback.tests._common.estimators.MaxIterEstimator object
when serializing tuple item 0
when serializing tuple item 1
when serializing list item 0
when serializing tuple item 0
when serializing joblib.parallel.BatchedCalls reconstructor arguments
when serializing joblib.parallel.BatchedCalls object
when serializing dict item 'fn'
when serializing joblib.externals.loky.process_executor._CallItem state
when serializing joblib.externals.loky.process_executor._CallItem object
"""

The above exception was the direct cause of the following exception:

n_jobs = 2, prefer = 'processes'
Callback = <class 'sklearn.callback.tests._common.callbacks.RecordingCallback'>

    @pytest.mark.parametrize("n_jobs", [1, 2])
    @pytest.mark.parametrize("prefer", ["threads", "processes"])
    @pytest.mark.parametrize(
        "Callback", [RecordingCallback, RecordingAutoPropagatedCallback]
    )
    def test_function_no_callback_support(n_jobs, prefer, Callback):
        """Check callbacks on estimators within function not supporting callbacks.
    
        Since the outer function does not support callbacks, there's no shared root context
        and the context trees of each sub-estimator are independent. As a result, the
        callback acts as a regular non-propagated callback: its on_fit_begin and on_fit_end
        are called once for each fit of the sub-estimator and the number of tasks is the sum
        of the number of tasks from all the sub-estimators.
        """
    
        def clone_and_fit(estimator):
            clone(estimator).fit()
    
        def func(estimator, n_fits, n_jobs, prefer):
            Parallel(n_jobs=n_jobs, prefer=prefer)(
                delayed(clone_and_fit)(estimator) for _ in range(n_fits)
            )
    
        n_fits, max_iter = 5, 7
        callback = Callback()
        estimator = MaxIterEstimator(max_iter=max_iter).set_callbacks(callback)
    
>       func(estimator, n_fits, n_jobs, prefer)

Callback   = <class 'sklearn.callback.tests._common.callbacks.RecordingCallback'>
callback   = <sklearn.callback.tests._common.callbacks.RecordingCallback object at 0x464b41d0310>
clone_and_fit = <function test_function_no_callback_support.<locals>.clone_and_fit at 0x464b41a0180>
estimator  = MaxIterEstimator(max_iter=7)
func       = <function test_function_no_callback_support.<locals>.func at 0x464b41a0c00>
max_iter   = 7
n_fits     = 5
n_jobs     = 2
prefer     = 'processes'

../sklearn/callback/tests/test_callback_support.py:150: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
../sklearn/callback/tests/test_callback_support.py:142: in func
    Parallel(n_jobs=n_jobs, prefer=prefer)(
        clone_and_fit = <function test_function_no_callback_support.<locals>.clone_and_fit at 0x464b41a0180>
        estimator  = MaxIterEstimator(max_iter=7)
        n_fits     = 5
        n_jobs     = 2
        prefer     = 'processes'
../sklearn/utils/parallel.py:91: in __call__
    return super().__call__(iterable_with_config_and_warning_filters)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
        __class__  = <class 'sklearn.utils.parallel.Parallel'>
        config     = {'assume_finite': False, 'working_memory': 1024, 'print_changed_only': True, 'display': 'diagram', ...}
        filters_func = <function _get_filters at 0x46340bd8700>
        iterable   = <generator object test_function_no_callback_support.<locals>.func.<locals>.<genexpr> at 0x464b4260d00>
        iterable_with_config_and_warning_filters = <generator object Parallel.__call__.<locals>.<genexpr> at 0x464b4330140>
        self       = Parallel(n_jobs=2)
        warning_filters = [('always', None, <class 'PendingDeprecationWarning'>, None, 0), ('always', None, <class 'DeprecationWarning'>, None, ...', re.IGNORECASE), <class 'Warning'>, None, 0), ('always', None, <class 'numpy.exceptions.RankWarning'>, None, 0), ...]
../../../../miniconda3/envs/testvenv/lib/python3.14t/site-packages/joblib/parallel.py:2072: in __call__
    return output if self.return_generator else list(output)
                                                ^^^^^^^^^^^^
        _batched_calls_reducer_callback = <function Parallel.__call__.<locals>._batched_calls_reducer_callback at 0x464b41a0d80>
        backend_name = 'LokyBackend'
        iterable   = <generator object Parallel.__call__.<locals>.<genexpr> at 0x464b4330140>
        iterator   = <itertools.islice object at 0x464b41605a0>
        n_jobs     = 2
        output     = <generator object Parallel._get_outputs at 0x464b4330c80>
        pre_dispatch = 4
        self       = Parallel(n_jobs=2)
../../../../miniconda3/envs/testvenv/lib/python3.14t/site-packages/joblib/parallel.py:1682: in _get_outputs
    yield from self._retrieve()
        _remaining_outputs = []
        detach_generator_exit = False
        dispatch_thread_id = 139674920146624
        iterator   = <itertools.islice object at 0x464b41605a0>
        pre_dispatch = 4
        self       = Parallel(n_jobs=2)
../../../../miniconda3/envs/testvenv/lib/python3.14t/site-packages/joblib/parallel.py:1784: in _retrieve
    self._raise_error_fast()
        batched_results = [None]
        nb_jobs    = 3
        result     = None
        self       = Parallel(n_jobs=2)
        timeout_control_job = None
../../../../miniconda3/envs/testvenv/lib/python3.14t/site-packages/joblib/parallel.py:1859: in _raise_error_fast
    error_job.get_result(self.timeout)
        error_job  = <joblib.parallel.BatchCompletionCallBack object at 0x463ba260790>
        self       = Parallel(n_jobs=2)
../../../../miniconda3/envs/testvenv/lib/python3.14t/site-packages/joblib/parallel.py:758: in get_result
    return self._return_or_raise()
           ^^^^^^^^^^^^^^^^^^^^^^^
        backend    = <joblib._parallel_backends.LokyBackend object at 0x464b4210210>
        self       = <joblib.parallel.BatchCompletionCallBack object at 0x463ba260790>
        timeout    = None
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <joblib.parallel.BatchCompletionCallBack object at 0x463ba260790>

    def _return_or_raise(self):
        try:
            if self.status == TASK_ERROR:
>               raise self._result
E               _pickle.PicklingError: Could not pickle the task to send it to the workers.

self       = <joblib.parallel.BatchCompletionCallBack object at 0x463ba260790>

../../../../miniconda3/envs/testvenv/lib/python3.14t/site-packages/joblib/parallel.py:773: PicklingError