scikit-learn · jnothman · Apr 28, 2020 · Jul 5, 2019 · Jul 5, 2019 · Jul 26, 2019
diff --git a/doc/whats_new/v0.23.rst b/doc/whats_new/v0.23.rst
@@ -308,6 +308,12 @@ Changelog
   random noise to the target. This might help with stability in some edge
   cases. :pr:`15179` by :user:`angelaambroz`.
 
+- |Fix| Fixed a bug in :class:`linear_model.ElasticNetCV`,
+  :class:`linear_model.MultitaskElasticNetCV`, :class:`linear_model.LassoCV`
+  and :class:`linear_model.MultitaskLassoCV` where fitting would fail when
+  using joblib loky backend. :pr:`14264` by
+  :user:`Jérémie du Boisberranger <jeremiedbb>`.
+
 :mod:`sklearn.metrics`
 ......................
 

diff --git a/sklearn/linear_model/_coordinate_descent.py b/sklearn/linear_model/_coordinate_descent.py
@@ -1068,6 +1068,15 @@ def _path_residuals(X, y, train, test, path, path_params, alphas=None,
     y_train = y[train]
     X_test = X[test]
     y_test = y[test]
+
+    if not sparse.issparse(X):
+        for array, array_input in ((X_train, X), (y_train, y),
+                      
F099
             (X_test, X), (y_test, y)):
+            if array.base is not array_input and not array.flags['WRITEABLE']:
+                # fancy indexing should create a writable copy but it doesn't
+                # for read-only memmaps (cf. numpy#14132).
+                array.setflags(write=True)
+
     fit_intercept = path_params['fit_intercept']
     normalize = path_params['normalize']
 

diff --git a/sklearn/linear_model/tests/test_coordinate_descent.py b/sklearn/linear_model/tests/test_coordinate_descent.py
@@ -7,8 +7,11 @@
 import pytest
 from scipy import interpolate, sparse
 from copy import deepcopy
+import joblib
+from distutils.version import LooseVersion
 
 from sklearn.datasets import load_boston
+from sklearn.datasets import make_regression
 from sklearn.exceptions import ConvergenceWarning
 from sklearn.utils._testing import assert_array_almost_equal
 from sklearn.utils._testing import assert_almost_equal
@@ -1020,3 +1023,23 @@ def test_enet_sample_weight_sparse():
     with pytest.raises(ValueError, match="Sample weights do not.*support "
                                          "sparse matrices"):
         reg.fit(X, y, sample_weight=sw, check_input=True)
+
+
+@pytest.mark.parametrize("backend", ["loky", "threading"])
+@pytest.mark.parametrize("estimator",
+                         [ElasticNetCV, MultiTaskElasticNetCV,
+                          LassoCV, MultiTaskLassoCV])
+def test_linear_models_cv_fit_for_all_backends(backend, estimator):
+    # LinearModelsCV.fit performs inplace operations on input data which is
+    # memmapped when using loky backend, causing an error due to unexpected
+    # behavior of fancy indexing of read-only memmaps (cf. numpy#14132).
+
+    if joblib.__version__ < LooseVersion('0.12') and backend == 'loky':
+        pytest.skip('loky backend does not exist in joblib <0.12')
+
+    # Create a problem sufficiently large to cause memmapping (1MB).
+    n_targets = 1 + (estimator in (MultiTaskElasticNetCV, MultiTaskLassoCV))
+    X, y = make_regression(20000, 10, n_targets=n_targets)
+
+    with joblib.parallel_backend(backend=backend):
+        estimator(n_jobs=2, cv=3).fit(X, y)