scikit-learn · Shivachauhan17 · Feb 28, 2023 · Mar 1, 2023 · Mar 1, 2023
diff --git a/sklearn/datasets/_lfw.py b/sklearn/datasets/_lfw.py
@@ -10,7 +10,7 @@

 from os import listdir, makedirs, remove
 from os.path import join, exists, isdir
-
+from ..utils._param_validation import validate_params,HasMethods
 import logging

 import numpy as np
@@ -230,7 +230,18 @@ def _fetch_lfw_people(
    faces, target = faces[indices], target[indices]
    return faces, target, target_names

-
+@validate_params(
+        {
+            "data_home":[str,None],
+            "funneled":["boolean"],
+            "resize":[float,None],
+            "min_faces_per_person":[int,None],
+            "color":["boolean"],
+            "slice":["tuple of slice",(slice(0, 250), slice(0, 250))],
+            "download_if_missing":["boolean"],
+            "return_X_y":["boolean"],
+        }
+)
 def fetch_lfw_people(
    *,
    data_home=None,

diff --git a/sklearn/datasets/_svmlight_format_io.py b/sklearn/datasets/_svmlight_format_io.py
@@ -25,6 +25,7 @@
 from .. import __version__

 from ..utils import check_array, IS_PYPY
+from ..utils._param_validation import validate_params,StrOptions

 if not IS_PYPY:
    from ._svmlight_format_fast import (
@@ -403,7 +404,15 @@ def _dump_svmlight(X, y, f, multilabel, one_based, comment, query_id):
        y_is_sp,
    )

-
+@validate_params({
+    "X":["array-like","sparse matrix"],
+    "y":["array-like","sparse matrix"],
+    "f":[str,StrOptions({"file"})],
+    "zero_based":[bool,True],
+    "comment":[str,None],
+    "query_id":["array-like",None],
+    "multilabel":[bool,False],
+})
 def dump_svmlight_file(
    X,
    y,

diff --git a/sklearn/tests/test_public_functions.py b/sklearn/tests/test_public_functions.py
@@ -107,6 +107,8 @@ def _check_function_param_validation(
    "sklearn.datasets.make_classification",
    "sklearn.datasets.make_friedman1",
    "sklearn.datasets.make_sparse_coded_signal",
+    "sklearn.datasets.dump_svmlight_file",
+    "sklearn.datasets.fetch_lfw_people",
    "sklearn.decomposition.sparse_encode",
    "sklearn.feature_extraction.grid_to_graph",
    "sklearn.feature_extraction.img_to_graph",