FIX fix comparison between array-like parameters when detecting non-default params for HTML representation (scikit-learn#31528)

Author: DeaMariaLeon

doc/whats_new/upcoming_changes/sklearn.base/31528.fix.rst

@@ -0,0 +1,3 @@
+- Fix regression in HTML representation when detecting the non-default parameters
+  that where of array-like types.
+  By :user:`Dea María Léon <deamarialeon>`

sklearn/base.py

@@ -292,12 +292,14 @@ def is_non_default(param_name, param_value):
                 init_default_params[param_name]
             ):
                 return True
-
-            if param_value != init_default_params[param_name] and not (
+            if not np.array_equal(
+                param_value, init_default_params[param_name]
+            ) and not (
                 is_scalar_nan(init_default_params[param_name])
                 and is_scalar_nan(param_value)
             ):
                 return True
+
             return False
 
         # reorder the parameters from `self.get_params` using the `__init__`

sklearn/tests/test_base.py

@@ -26,7 +26,8 @@
 from sklearn.decomposition import PCA
 from sklearn.ensemble import IsolationForest
 from sklearn.exceptions import InconsistentVersionWarning
-from sklearn.model_selection import GridSearchCV
+from sklearn.metrics import get_scorer
+from sklearn.model_selection import GridSearchCV, KFold
 from sklearn.pipeline import Pipeline
 from sklearn.preprocessing import StandardScaler
 from sklearn.svm import SVC, SVR
@@ -1000,3 +1001,81 @@ def test_get_params_html():
 
     assert est._get_params_html() == {"l1": 0, "empty": "test"}
     assert est._get_params_html().non_default == ("empty",)
+
+
+def make_estimator_with_param(default_value):
+    class DynamicEstimator(BaseEstimator):
+        def __init__(self, param=default_value):
+            self.param = param
+
+    return DynamicEstimator
+
+
+@pytest.mark.parametrize(
+    "default_value, test_value",
+    [
+        ((), (1,)),
+        ((), [1]),
+        ((), np.array([1])),
+        ((1, 2), (3, 4)),
+        ((1, 2), [3, 4]),
+        ((1, 2), np.array([3, 4])),
+        (None, 1),
+        (None, []),
+        (None, lambda x: x),
+        (np.nan, 1.0),
+        (np.nan, np.array([np.nan])),
+        ("abc", "def"),
+        ("abc", ["abc"]),
+        (True, False),
+        (1, 2),
+        (1, [1]),
+        (1, np.array([1])),
+        (1.0, 2.0),
+        (1.0, [1.0]),
+        (1.0, np.array([1.0])),
+        ([1, 2], [3]),
+        (np.array([1]), [2, 3]),
+        (None, KFold()),
+        (None, get_scorer("accuracy")),
+    ],
+)
+def test_param_is_non_default(default_value, test_value):
+    """Check that we detect non-default parameters with various types.
+
+    Non-regression test for:
+    https://github.com/scikit-learn/scikit-learn/issues/31525
+    """
+    estimator = make_estimator_with_param(default_value)(param=test_value)
+    non_default = estimator._get_params_html().non_default
+    assert "param" in non_default
+
+
+@pytest.mark.parametrize(
+    "default_value, test_value",
+    [
+        (None, None),
+        ((), ()),
+        ((), []),
+        ((), np.array([])),
+        ((1, 2, 3), (1, 2, 3)),
+        ((1, 2, 3), [1, 2, 3]),
+        ((1, 2, 3), np.array([1, 2, 3])),
+        (np.nan, np.nan),
+        ("abc", "abc"),
+        (True, True),
+        (1, 1),
+        (1.0, 1.0),
+        (2, 2.0),
+    ],
+)
+def test_param_is_default(default_value, test_value):
+    """Check that we detect the default parameters and values in an array-like will
+    be reported as default as well.
+
+    Non-regression test for:
+    https://github.com/scikit-learn/scikit-learn/issues/31525
+    """
+    estimator = make_estimator_with_param(default_value)(param=test_value)
+    non_default = estimator._get_params_html().non_default
+    assert "param" not in non_default