DOC Ensures that config_context passes numpydoc validation (#21426)

glemaitre · majauhar · thomasjpfan · glemaitre · commit 91215fc60aba · 2021-12-25T12:26:49.000+01:00
Co-authored-by: majauhar &lt;siddmohamed19@gmail.com&gt;
Co-authored-by: Thomas J. Fan &lt;thomasjpfan@gmail.com&gt;
diff --git a/maint_tools/test_docstrings.py b/maint_tools/test_docstrings.py
@@ -12,7 +12,6 @@
 numpydoc_validation = pytest.importorskip("numpydoc.validate")
 
 FUNCTION_DOCSTRING_IGNORE_LIST = [
-    "sklearn._config.config_context",
     "sklearn._config.get_config",
     "sklearn.base.clone",
     "sklearn.cluster._affinity_propagation.affinity_propagation",
diff --git a/sklearn/_config.py b/sklearn/_config.py
@@ -98,40 +98,55 @@ def set_config(
 
 
 @contextmanager
-def config_context(**new_config):
-    """Context manager for global scikit-learn configuration
+def config_context(
+    *, assume_finite=None, working_memory=None, print_changed_only=None, display=None
+):
+    """Context manager for global scikit-learn configuration.
 
     Parameters
     ----------
-    assume_finite : bool, default=False
+    assume_finite : bool, default=None
         If True, validation for finiteness will be skipped,
         saving time, but leading to potential crashes. If
         False, validation for finiteness will be performed,
-        avoiding error.  Global default: False.
+        avoiding error. If None, the existing value won't change.
+        The default value is False.
 
-    working_memory : int, default=1024
+    working_memory : int, default=None
         If set, scikit-learn will attempt to limit the size of temporary arrays
         to this number of MiB (per job when parallelised), often saving both
         computation time and memory on expensive operations that can be
-        performed in chunks. Global default: 1024.
+        performed in chunks. If None, the existing value won't change.
+        The default value is 1024.
 
-    print_changed_only : bool, default=True
+    print_changed_only : bool, default=None
         If True, only the parameters that were set to non-default
         values will be printed when printing an estimator. For example,
         ``print(SVC())`` while True will only print 'SVC()', but would print
         'SVC(C=1.0, cache_size=200, ...)' with all the non-changed parameters
-        when False. Default is True.
+        when False. If None, the existing value won't change.
+        The default value is True.
 
         .. versionchanged:: 0.23
            Default changed from False to True.
 
-    display : {'text', 'diagram'}, default='text'
+    display : {'text', 'diagram'}, default=None
         If 'diagram', estimators will be displayed as a diagram in a Jupyter
         lab or notebook context. If 'text', estimators will be displayed as
-        text. Default is 'text'.
+        text. If None, the existing value won't change.
+        The default value is 'text'.
 
         .. versionadded:: 0.23
 
+    Yields
+    ------
+    None.
+
+    See Also
+    --------
+    set_config : Set global scikit-learn configuration.
+    get_config : Retrieve current values of the global configuration.
+
     Notes
     -----
     All settings, not just those presently modified, will be returned to
@@ -148,15 +163,15 @@ def config_context(**new_config):
     ...         assert_all_finite([float('nan')])
     Traceback (most recent call last):
     ...
-    ValueError: Input contains NaN, ...
-
-    See Also
-    --------
-    set_config : Set global scikit-learn configuration.
-    get_config : Retrieve current values of the global configuration.
+    ValueError: Input contains NaN...
     """
     old_config = get_config()
-    set_config(**new_config)
+    set_config(
+        assume_finite=assume_finite,
+        working_memory=working_memory,
+        print_changed_only=print_changed_only,
+        display=display,
+    )
 
     try:
         yield
