FIX propagate configuration to workers in parallel

benchmarks/bench_saga.py

@@ -7,8 +7,7 @@
 import time
 import os
 
-from joblib import Parallel
-from sklearn.utils.fixes import delayed
+from sklearn.utils.parallel import delayed, Parallel
 import matplotlib.pyplot as plt
 import numpy as np
 

build_tools/azure/linting.sh

@@ -34,10 +34,15 @@ then
     exit 1
 fi
 
-joblib_import="$(git grep -l -A 10 -E "joblib import.+delayed" -- "*.py" ":!sklearn/utils/_joblib.py" ":!sklearn/utils/fixes.py")"
-
-if [ ! -z "$joblib_import" ]; then
-    echo "Use from sklearn.utils.fixes import delayed instead of joblib delayed. The following files contains imports to joblib.delayed:"
-    echo "$joblib_import"
+joblib_delayed_import="$(git grep -l -A 10 -E "joblib import.+delayed" -- "*.py" ":!sklearn/utils/_joblib.py" ":!sklearn/utils/parallel.py")"
+if [ ! -z "$joblib_delayed_import" ]; then
+    echo "Use from sklearn.utils.parallel import delayed instead of joblib delayed. The following files contains imports to joblib.delayed:"
+    echo "$joblib_delayed_import"
+    exit 1
+fi
+joblib_Parallel_import="$(git grep -l -A 10 -E "joblib import.+Parallel" -- "*.py" ":!sklearn/utils/_joblib.py" ":!sklearn/utils/parallel.py")"
+if [ ! -z "$joblib_Parallel_import" ]; then
+    echo "Use from sklearn.utils.parallel import Parallel instead of joblib Parallel. The following files contains imports to joblib.Parallel:"
+    echo "$joblib_Parallel_import"
     exit 1
 fi

doc/modules/classes.rst

@@ -1668,9 +1668,16 @@ Utilities from joblib:
    :toctree: generated/
    :template: function.rst
 
+   utils.parallel.delayed
    utils.parallel_backend
    utils.register_parallel_backend
 
+.. autosummary::
+   :toctree: generated/
+   :template: class.rst
+
+   utils.parallel.Parallel
+
 
 Recently deprecated
 ===================

doc/whats_new/v1.2.rst

@@ -9,6 +9,16 @@ Version 1.2.1
 
 **In Development**
 
+Changes impacting all modules
+-----------------------------
+
+- |Fix| Fix a bug where the current configuration was ignored in estimators using
+  `n_jobs > 1`. This bug was triggered for tasks dispatched by the auxillary
+  thread of `joblib` as :func:`sklearn.get_config` used to access an empty thread
+  local configuration instead of the configuration visible from the thread where
+  `joblib.Parallel` was first called.
+  :pr:`25363` by :user:`Guillaume Lemaitre <glemaitre>`.
+
 Changed models
 --------------
 
@@ -105,6 +115,10 @@ Changelog
   boolean. The type is maintained, instead of converting to `float64.`
   :pr:`25147` by :user:`Tim Head <betatim>`.
 
+- |API| :func:`utils.fixes.delayed` is deprecated in 1.2.1 and will be removed
+  in 1.5. Instead, import :func:`utils.parallel.delayed`.
+  :pr:`25363` by :user:`Guillaume Lemaitre <glemaitre>`.
+
 .. _changes_1_2:
 
 Version 1.2.0

sklearn/calibration.py

@@ -14,7 +14,6 @@
 
 from math import log
 import numpy as np
-from joblib import Parallel
 
 from scipy.special import expit
 from scipy.special import xlogy
@@ -36,7 +35,7 @@
 )
 
 from .utils.multiclass import check_classification_targets
-from .utils.fixes import delayed
+from .utils.parallel import delayed, Parallel
 from .utils._param_validation import StrOptions, HasMethods, Hidden
 from .utils.validation import (
     _check_fit_params,

sklearn/cluster/_mean_shift.py

@@ -16,13 +16,12 @@
 
 import numpy as np
 import warnings
-from joblib import Parallel
 from numbers import Integral, Real
 
 from collections import defaultdict
 from ..utils._param_validation import Interval, validate_params
 from ..utils.validation import check_is_fitted
-from ..utils.fixes import delayed
+from ..utils.parallel import delayed, Parallel
 from ..utils import check_random_state, gen_batches, check_array
 from ..base import BaseEstimator, ClusterMixin
 from ..neighbors import NearestNeighbors

sklearn/compose/_column_transformer.py

@@ -12,7 +12,6 @@
 
 import numpy as np
 from scipy import sparse
-from joblib import Parallel
 
 from ..base import clone, TransformerMixin
 from ..utils._estimator_html_repr import _VisualBlock
@@ -26,7 +25,7 @@
 from ..utils import check_pandas_support
 from ..utils.metaestimators import _BaseComposition
 from ..utils.validation import check_array, check_is_fitted, _check_feature_names_in
-from ..utils.fixes import delayed
+from ..utils.parallel import delayed, Parallel
 
 
 __all__ = ["ColumnTransformer", "make_column_transformer", "make_column_selector"]

sklearn/covariance/_graph_lasso.py

@@ -13,7 +13,6 @@
 from numbers import Integral, Real
 import numpy as np
 from scipy import linalg
-from joblib import Parallel
 
 from . import empirical_covariance, EmpiricalCovariance, log_likelihood
 
@@ -23,7 +22,7 @@
     check_random_state,
     check_scalar,
 )
-from ..utils.fixes import delayed
+from ..utils.parallel import delayed, Parallel
 from ..utils._param_validation import Interval, StrOptions
 
 # mypy error: Module 'sklearn.linear_model' has no attribute '_cd_fast'

sklearn/decomposition/_dict_learning.py

@@ -13,15 +13,15 @@
 
 import numpy as np
 from scipy import linalg
-from joblib import Parallel, effective_n_jobs
+from joblib import effective_n_jobs
 
 from ..base import BaseEstimator, TransformerMixin, ClassNamePrefixFeaturesOutMixin
 from ..utils import check_array, check_random_state, gen_even_slices, gen_batches
 from ..utils._param_validation import Hidden, Interval, StrOptions
 from ..utils._param_validation import validate_params
 from ..utils.extmath import randomized_svd, row_norms, svd_flip
 from ..utils.validation import check_is_fitted
-from ..utils.fixes import delayed
+from ..utils.parallel import delayed, Parallel
 from ..linear_model import Lasso, orthogonal_mp_gram, LassoLars, Lars
 
 

sklearn/decomposition/_lda.py

@@ -15,13 +15,13 @@
 import numpy as np
 import scipy.sparse as sp
 from scipy.special import gammaln, logsumexp
-from joblib import Parallel, effective_n_jobs
+from joblib import effective_n_jobs
 
 from ..base import BaseEstimator, TransformerMixin, ClassNamePrefixFeaturesOutMixin
 from ..utils import check_random_state, gen_batches, gen_even_slices
 from ..utils.validation import check_non_negative
 from ..utils.validation import check_is_fitted
-from ..utils.fixes import delayed
+from ..utils.parallel import delayed, Parallel
 from ..utils._param_validation import Interval, StrOptions
 
 from ._online_lda_fast import (

sklearn/decomposition/tests/test_dict_learning.py

@@ -5,15 +5,14 @@
 from functools import partial
 import itertools
 
-from joblib import Parallel
-
 import sklearn
 
 from sklearn.base import clone
 
 from sklearn.exceptions import ConvergenceWarning
 
 from sklearn.utils import check_array
+from sklearn.utils.parallel import Parallel
 
 from sklearn.utils._testing import assert_allclose
 from sklearn.utils._testing import assert_array_almost_equal

sklearn/ensemble/_bagging.py

@@ -12,8 +12,6 @@
 from warnings import warn
 from functools import partial
 
-from joblib import Parallel
-
 from ._base import BaseEnsemble, _partition_estimators
 from ..base import ClassifierMixin, RegressorMixin
 from ..metrics import r2_score, accuracy_score
@@ -25,7 +23,7 @@
 from ..utils.random import sample_without_replacement
 from ..utils._param_validation import Interval, HasMethods, StrOptions
 from ..utils.validation import has_fit_parameter, check_is_fitted, _check_sample_weight
-from ..utils.fixes import delayed
+from ..utils.parallel import delayed, Parallel
 
 
 __all__ = ["BaggingClassifier", "BaggingRegressor"]

sklearn/ensemble/_forest.py

@@ -48,7 +48,6 @@ class calls the ``fit`` method of each sub-estimator on random samples
 import numpy as np
 from scipy.sparse import issparse
 from scipy.sparse import hstack as sparse_hstack
-from joblib import Parallel
 
 from ..base import is_classifier
 from ..base import ClassifierMixin, MultiOutputMixin, RegressorMixin, TransformerMixin
@@ -66,7 +65,7 @@ class calls the ``fit`` method of each sub-estimator on random samples
 from ..utils import check_random_state, compute_sample_weight
 from ..exceptions import DataConversionWarning
 from ._base import BaseEnsemble, _partition_estimators
-from ..utils.fixes import delayed
+from ..utils.parallel import delayed, Parallel
 from ..utils.multiclass import check_classification_targets, type_of_target
 from ..utils.validation import (
     check_is_fitted,

sklearn/ensemble/_stacking.py

@@ -8,7 +8,6 @@
 from numbers import Integral
 
 import numpy as np
-from joblib import Parallel
 import scipy.sparse as sparse
 
 from ..base import clone
@@ -33,7 +32,7 @@
 from ..utils.metaestimators import available_if
 from ..utils.validation import check_is_fitted
 from ..utils.validation import column_or_1d
-from ..utils.fixes import delayed
+from ..utils.parallel import delayed, Parallel
 from ..utils._param_validation import HasMethods, StrOptions
 from ..utils.validation import _check_feature_names_in
 

sklearn/ensemble/_voting.py

@@ -18,8 +18,6 @@
 
 import numpy as np
 
-from joblib import Parallel
-
 from ..base import ClassifierMixin
 from ..base import RegressorMixin
 from ..base import TransformerMixin
@@ -36,7 +34,7 @@
 from ..utils._param_validation import StrOptions
 from ..exceptions import NotFittedError
 from ..utils._estimator_html_repr import _VisualBlock
-from ..utils.fixes import delayed
+from ..utils.parallel import delayed, Parallel
 
 
 class _BaseVoting(TransformerMixin, _BaseHeterogeneousEnsemble):

sklearn/ensemble/tests/test_forest.py

@@ -18,16 +18,15 @@
 from typing import Dict, Any
 
 import numpy as np
-from joblib import Parallel
 from scipy.sparse import csr_matrix
 from scipy.sparse import csc_matrix
 from scipy.sparse import coo_matrix
 from scipy.special import comb
 
-import pytest
-
 import joblib
 
+import pytest
+
 import sklearn
 from sklearn.dummy import DummyRegressor
 from sklearn.metrics import mean_poisson_deviance
@@ -52,6 +51,7 @@
 from sklearn.model_selection import train_test_split, cross_val_score
 from sklearn.model_selection import GridSearchCV
 from sklearn.svm import LinearSVC
+from sklearn.utils.parallel import Parallel
 from sklearn.utils.validation import check_random_state
 
 from sklearn.metrics import mean_squared_error

sklearn/feature_selection/_rfe.py

@@ -8,15 +8,15 @@
 
 import numpy as np
 from numbers import Integral, Real
-from joblib import Parallel, effective_n_jobs
+from joblib import effective_n_jobs
 
 
 from ..utils.metaestimators import available_if
 from ..utils.metaestimators import _safe_split
 from ..utils._param_validation import HasMethods, Interval
 from ..utils._tags import _safe_tags
 from ..utils.validation import check_is_fitted
-from ..utils.fixes import delayed
+from ..utils.parallel import delayed, Parallel
 from ..base import BaseEstimator
 from ..base import MetaEstimatorMixin
 from ..base import clone

sklearn/inspection/_permutation_importance.py

@@ -1,7 +1,6 @@
 """Permutation importance for estimators."""
 import numbers
 import numpy as np
-from joblib import Parallel
 
 from ..ensemble._bagging import _generate_indices
 from ..metrics import check_scoring
@@ -10,7 +9,7 @@
 from ..utils import Bunch, _safe_indexing
 from ..utils import check_random_state
 from ..utils import check_array
-from ..utils.fixes import delayed
+from ..utils.parallel import delayed, Parallel
 
 
 def _weights_scorer(scorer, estimator, X, y, sample_weight):

sklearn/inspection/_plot/partial_dependence.py

@@ -6,7 +6,6 @@
 import numpy as np
 from scipy import sparse
 from scipy.stats.mstats import mquantiles
-from joblib import Parallel
 
 from .. import partial_dependence
 from .._pd_utils import _check_feature_names, _get_feature_index
@@ -16,7 +15,7 @@
 from ...utils import check_matplotlib_support  # noqa
 from ...utils import check_random_state
 from ...utils import _safe_indexing
-from ...utils.fixes import delayed
+from ...utils.parallel import delayed, Parallel
 from ...utils._encode import _unique
 
 

sklearn/linear_model/_base.py

@@ -25,7 +25,6 @@
 from scipy import sparse
 from scipy.sparse.linalg import lsqr
 from scipy.special import expit
-from joblib import Parallel
 from numbers import Integral
 
 from ..base import BaseEstimator, ClassifierMixin, RegressorMixin, MultiOutputMixin
@@ -40,7 +39,7 @@
 from ..utils._seq_dataset import ArrayDataset32, CSRDataset32
 from ..utils._seq_dataset import ArrayDataset64, CSRDataset64
 from ..utils.validation import check_is_fitted, _check_sample_weight
-from ..utils.fixes import delayed
+from ..utils.parallel import delayed, Parallel
 
 # TODO: bayesian_ridge_regression and bayesian_regression_ard
 # should be squashed into its respective objects.

sklearn/linear_model/_coordinate_descent.py

@@ -14,7 +14,7 @@
 
 import numpy as np
 from scipy import sparse
-from joblib import Parallel, effective_n_jobs
+from joblib import effective_n_jobs
 
 from ._base import LinearModel, _pre_fit
 from ..base import RegressorMixin, MultiOutputMixin
@@ -30,7 +30,7 @@
     check_is_fitted,
     column_or_1d,
 )
-from ..utils.fixes import delayed
+from ..utils.parallel import delayed, Parallel
 
 # mypy error: Module 'sklearn.linear_model' has no attribute '_cd_fast'
 from . import _cd_fast as cd_fast  # type: ignore

sklearn/linear_model/_least_angle.py

@@ -16,7 +16,6 @@
 import numpy as np
 from scipy import linalg, interpolate
 from scipy.linalg.lapack import get_lapack_funcs
-from joblib import Parallel
 
 from ._base import LinearModel, LinearRegression
 from ._base import _deprecate_normalize, _preprocess_data
@@ -28,7 +27,7 @@
 from ..utils._param_validation import Hidden, Interval, StrOptions
 from ..model_selection import check_cv
 from ..exceptions import ConvergenceWarning
-from ..utils.fixes import delayed
+from ..utils.parallel import delayed, Parallel
 
 SOLVE_TRIANGULAR_ARGS = {"check_finite": False}