scikit-learn · ogrisel · Nov 4, 2021 · Oct 31, 2021 · Oct 31, 2021 · Oct 31, 2021
diff --git a/build_tools/azure/test_script.sh b/build_tools/azure/test_script.sh
@@ -35,18 +35,21 @@ if [[ "$COVERAGE" == "true" ]]; then
     # report that otherwise hides the test failures and forces long scrolls in
     # the CI logs.
     export COVERAGE_PROCESS_START="$BUILD_SOURCESDIRECTORY/.coveragerc"
-    TEST_CMD="$TEST_CMD --cov-config=$COVERAGE_PROCESS_START --cov sklearn --cov-report="
+    TEST_CMD="$TEST_CMD --cov-config='$COVERAGE_PROCESS_START' --cov sklearn --cov-report="
 fi
 
 if [[ -n "$CHECK_WARNINGS" ]]; then
     # numpy's 1.19.0's tostring() deprecation is ignored until scipy and joblib removes its usage
     TEST_CMD="$TEST_CMD -Werror::DeprecationWarning -Werror::FutureWarning -Wignore:tostring:DeprecationWarning"
+
+    # Python 3.10 deprecates disutils and is imported by numpy interally during import time
+    TEST_CMD="$TEST_CMD -Wignore:The\ distutils:DeprecationWarning"
 fi
 
 if [[ "$PYTEST_XDIST_VERSION" != "none" ]]; then
     TEST_CMD="$TEST_CMD -n2"
 fi
 
 set -x
-$TEST_CMD --pyargs sklearn
+eval "$TEST_CMD --pyargs sklearn"
 set +x
diff --git a/doc/whats_new/v1.0.rst b/doc/whats_new/v1.0.rst
@@ -28,6 +28,12 @@ Changelog
   and :class:`decomposition.MiniBatchSparsePCA` to be convex and match the referenced
   article. :pr:`19210` by :user:`Jérémie du Boisberranger <jeremiedbb>`.
 
+:mod:`sklearn.preprocessing`
+............................
+
+- |Fix| Fixes compatibility bug with NumPy 1.22 in :class:`preprocessing.OneHotEncoder`.
+  :pr:`21517` by `Thomas Fan`_.
+
 :mod:`sklearn.utils`
 ....................
 

diff --git a/sklearn/cluster/tests/test_dbscan.py b/sklearn/cluster/tests/test_dbscan.py
@@ -180,7 +180,7 @@ def test_dbscan_metric_params():
             min_samples=min_samples,
             algorithm="ball_tree",
         ).fit(X)
-    assert not warns
+    assert not warns, warns[0].message
     core_sample_1, labels_1 = db.core_sample_indices_, db.labels_
 
     # Test that sample labels are the same as passing Minkowski 'p' directly

diff --git a/sklearn/preprocessing/_encoders.py b/sklearn/preprocessing/_encoders.py
@@ -544,7 +544,7 @@ def transform(self, X):
    
         indptr = np.empty(n_samples + 1, dtype=int)
         indptr[0] = 0
-        np.sum(X_mask, axis=1, out=indptr[1:])
+        np.sum(X_mask, axis=1, out=indptr[1:], dtype=indptr.dtype)
         np.cumsum(indptr[1:], out=indptr[1:])
         data = np.ones(indptr[-1])