scikit-learn · glemaitre · Jun 22, 2022 · Jun 13, 2022 · Jun 13, 2022 · Jun 21, 2022
diff --git a/sklearn/tests/test_public_functions.py b/sklearn/tests/test_public_functions.py
@@ -34,10 +34,14 @@ def test_function_param_validation(func_module):
     required_params = [
         p.name for p in func_sig.parameters.values() if p.default is p.empty
     ]
-    required_params = {
-        p: generate_valid_param(make_constraint(parameter_constraints[p][0]))
-        for p in required_params
-    }
+    valid_required_params = {}
+    for param_name in required_params:
+        if parameter_constraints[param_name] == "no_validation":
+            valid_required_params[param_name] = 1
+        else:
+            valid_required_params[param_name] = generate_valid_param(
+                make_constraint(parameter_constraints[param_name][0])
+            )
 
     # check that there is a constraint for each parameter
     if func_params:
@@ -51,18 +55,23 @@ def test_function_param_validation(func_module):
     param_with_bad_type = type("BadType", (), {})()
 
     for param_name in func_params:
+        constraints = parameter_constraints[param_name]
+
+        if constraints == "no_validation":
+            # This parameter is not validated
+            continue
+
         match = (
             rf"The '{param_name}' parameter of {func_name} must be .* Got .* instead."
         )
 
         # First, check that the error is raised if param doesn't match any valid type.
         with pytest.raises(ValueError, match=match):
-            func(**{**required_params, param_name: param_with_bad_type})
+            func(**{**valid_required_params, param_name: param_with_bad_type})
 
         # Then, for constraints that are more than a type constraint, check that the
         # error is raised if param does match a valid type but does not match any valid
         # value for this type.
-        constraints = parameter_constraints[param_name]
         constraints = [make_constraint(constraint) for constraint in constraints]
 
         for constraint in constraints:
@@ -72,4 +81,4 @@ def test_function_param_validation(func_module):
                 continue
 
             with pytest.raises(ValueError, match=match):
-                func(**{**required_params, param_name: bad_value})
+                func(**{**valid_required_params, param_name: bad_value})
diff --git a/sklearn/utils/_param_validation.py b/sklearn/utils/_param_validation.py
@@ -19,9 +19,12 @@ def validate_parameter_constraints(parameter_constraints, params, caller_name):
 
     Parameters
     ----------
-    parameter_constraints : dict
-        A dictionary `param_name: list of constraints`. A parameter is valid if it
-        satisfies one of the constraints from the list. Constraints can be:
+    parameter_constraints : dict or {"no_validation"}
+        If "no_validation", validation is skipped for this parameter.
+
+        If a dict, it must be a dictionary `param_name: list of constraints`.
+        A parameter is valid if it satisfies one of the constraints from the list.
+        Constraints can be:
         - an Interval object, representing a continuous or discrete range of numbers
         - the string "array-like"
         - the string "sparse matrix"
@@ -47,6 +50,10 @@ def validate_parameter_constraints(parameter_constraints, params, caller_name):
 
     for param_name, param_val in params.items():
         constraints = parameter_constraints[param_name]
+
+        if constraints == "no_validation":
+            continue
+
         constraints = [make_constraint(constraint) for constraint in constraints]
 
         for constraint in constraints:

diff --git a/sklearn/utils/estimator_checks.py b/sklearn/utils/estimator_checks.py
@@ -4064,6 +4064,12 @@ def check_param_validation(name, estimator_orig):
     methods = [method for method in fit_methods if hasattr(estimator_orig, method)]
 
     for param_name in estimator_params:
+        constraints = estimator_orig._parameter_constraints[param_name]
+
+        if constraints == "no_validation":
+            # This parameter is not validated
+            continue
+
         match = rf"The '{param_name}' parameter of {name} must be .* Got .* instead."
         err_msg = (
             f"{name} does not raise an informative error message when the "
@@ -4082,7 +4088,6 @@ def check_param_validation(name, estimator_orig):
         # Then, for constraints that are more than a type constraint, check that the
         # error is raised if param does match a valid type but does not match any valid
         # value for this type.
-        constraints = estimator_orig._parameter_constraints[param_name]
         constraints = [make_constraint(constraint) for constraint in constraints]
 
         for constraint in constraints:

diff --git a/sklearn/utils/tests/test_param_validation.py b/sklearn/utils/tests/test_param_validation.py
@@ -522,3 +522,22 @@ def f(param):
         FutureWarning, match="Passing an int for a boolean parameter is deprecated"
     ):
         f(1)
+
+
+def test_no_validation():
+    """Check that validation can be skipped for a parameter."""
+
+    @validate_params({"param1": [int, None], "param2": "no_validation"})
+    def f(param1=None, param2=None):
+        pass
+
+    # param1 is validated
+    with pytest.raises(ValueError, match="The 'param1' parameter"):
+        f(param1="wrong")
+
+    # param2 is not validated: any type is valid.
+    class SomeType:
+        pass
+
+    f(param2=SomeType)
+    f(param2=SomeType())