MAINT Parameters validation for sklearn.metrics.pairwise.paired_manhattan_distances (scikit-learn#26074)

Charlie-XIAO · web-flow · commit 427408d90deb · 2023-04-04T11:46:39.000+02:00
diff --git a/sklearn/metrics/pairwise.py b/sklearn/metrics/pairwise.py
@@ -1051,6 +1051,9 @@ def paired_euclidean_distances(X, Y):
     return row_norms(X - Y)
 
 
+@validate_params(
+    {"X": ["array-like", "sparse matrix"], "Y": ["array-like", "sparse matrix"]}
+)
 def paired_manhattan_distances(X, Y):
     """Compute the paired L1 distances between X and Y.
 
@@ -1061,10 +1064,10 @@ def paired_manhattan_distances(X, Y):
 
     Parameters
     ----------
-    X : array-like of shape (n_samples, n_features)
+    X : {array-like, sparse matrix} of shape (n_samples, n_features)
         An array-like where each row is a sample and each column is a feature.
 
-    Y : array-like of shape (n_samples, n_features)
+    Y : {array-like, sparse matrix} of shape (n_samples, n_features)
         An array-like where each row is a sample and each column is a feature.
 
     Returns
diff --git a/sklearn/tests/test_public_functions.py b/sklearn/tests/test_public_functions.py
@@ -210,6 +210,7 @@ def _check_function_param_validation(
     "sklearn.metrics.pairwise.laplacian_kernel",
     "sklearn.metrics.pairwise.linear_kernel",
     "sklearn.metrics.pairwise.paired_euclidean_distances",
+    "sklearn.metrics.pairwise.paired_manhattan_distances",
     "sklearn.metrics.precision_recall_curve",
     "sklearn.metrics.precision_recall_fscore_support",
     "sklearn.metrics.precision_score",
