Add inline comments'

adam2392 · adam2392 · commit 1d941206c431 · 2022-03-23T09:31:02.000-04:00
diff --git a/sklearn/ensemble/tests/test_forest.py b/sklearn/ensemble/tests/test_forest.py
@@ -1697,6 +1697,8 @@ def test_max_samples_boundary_regressors(name):
     assert ms_1_ms == pytest.approx(ms_None_ms)
 
 
+# TODO: Trees do not preserve dtype when fitting/predicting.
+# Add `global_dtype` when Trees have this ability.
 @pytest.mark.parametrize("name", FOREST_CLASSIFIERS)
 def test_max_samples_boundary_classifiers(name):
     X_train, X_test, y_train, _ = train_test_split(
diff --git a/sklearn/tree/tests/test_tree.py b/sklearn/tree/tests/test_tree.py
@@ -259,6 +259,8 @@ def test_weighted_classification_toy():
         assert_array_equal(clf.predict(T), true_result, "Failed with {0}".format(name))
 
 
+# TODO: Trees do not preserve dtype when fitting/predicting.
+# Add `global_dtype` when Trees have this ability.
 @pytest.mark.parametrize("Tree", REG_TREES.values())
 @pytest.mark.parametrize("criterion", REG_CRITERIONS)
 def test_regression_toy(Tree, criterion):
@@ -2138,6 +2140,8 @@ def test_poisson_vs_mse():
         assert metric_poi < 0.75 * metric_dummy
 
 
+# TODO: Trees do not preserve dtype when fitting/predicting.
+# Add `global_dtype` when Trees have this ability.
 @pytest.mark.parametrize("criterion", REG_CRITERIONS)
 def test_decision_tree_regressor_sample_weight_consistentcy(criterion):
     """Test that the impact of sample_weight is consistent."""
