MAINT Parameters validation for euclidean_distances (scikit-learn#25782)

bkunde · jeremiedbb · punndcoder28 · commit e7c02a20d7a6 · 2023-07-29T17:38:00.000+05:30
Co-authored-by: jeremiedbb &lt;jeremiedbb@yahoo.fr&gt;
diff --git a/sklearn/metrics/pairwise.py b/sklearn/metrics/pairwise.py
@@ -231,6 +231,16 @@ def check_paired_arrays(X, Y):
 
 
 # Pairwise distances
+@validate_params(
+    {
+        "X": ["array-like", "sparse matrix"],
+        "Y": ["array-like", "sparse matrix", None],
+        "Y_norm_squared": ["array-like", None],
+        "squared": ["boolean"],
+        "X_norm_squared": ["array-like", None],
+    },
+    prefer_skip_nested_validation=True,
+)
 def euclidean_distances(
     X, Y=None, *, Y_norm_squared=None, squared=False, X_norm_squared=None
 ):
diff --git a/sklearn/tests/test_public_functions.py b/sklearn/tests/test_public_functions.py
@@ -237,6 +237,7 @@ def _check_function_param_validation(
     "sklearn.metrics.pairwise.additive_chi2_kernel",
     "sklearn.metrics.pairwise.cosine_distances",
     "sklearn.metrics.pairwise.cosine_similarity",
+    "sklearn.metrics.pairwise.euclidean_distances",
     "sklearn.metrics.pairwise.haversine_distances",
     "sklearn.metrics.pairwise.laplacian_kernel",
     "sklearn.metrics.pairwise.linear_kernel",
