scikit-learn · jeremiedbb · Jan 26, 2023 · Jan 26, 2023 · Feb 7, 2023 · Feb 9, 2023
diff --git a/doc/whats_new/v1.3.rst b/doc/whats_new/v1.3.rst
@@ -90,11 +90,15 @@ Changelog
     :pr:`123456` by :user:`Joe Bloggs <joeongithub>`.
     where 123456 is the *pull request* number, not the issue number.
 
-:mod:`sklearn.feature_selection`
-................................
+:mod:`sklearn`
+..............
 
-- |Enhancement| All selectors in :mod:`sklearn.feature_selection` will preserve
-  a DataFrame's dtype when transformed. :pr:`25102` by `Thomas Fan`_.
+- |Feature| Added a new option `skip_parameter_validation`, to the function
+  :func:`sklearn.set_config` and context manager :func:`sklearn.config_context`, that
+  allows to skip the validation of the parameters passed to the estimators and public
+  functions. This is useful to speed up the code but should be used with care because
+  it can lead to potential crashes.
+  :pr:`25493` by :user:`Jérémie du Boisberranger <jeremiedbb>`.
 
 :mod:`sklearn.base`
 ...................
@@ -153,6 +157,12 @@ Changelog
   inconsistent with the sckit-learn verion the estimator was pickled with.
   :pr:`25297` by `Thomas Fan`_.
 
+:mod:`sklearn.feature_selection`
+................................
+
+- |Enhancement| All selectors in :mod:`sklearn.feature_selection` will preserve
+  a DataFrame's dtype when transformed. :pr:`25102` by `Thomas Fan`_.
+
 :mod:`sklearn.impute`
 .....................
 

diff --git a/sklearn/_config.py b/sklearn/_config.py
@@ -15,6 +15,7 @@
     "enable_cython_pairwise_dist": True,
     "array_api_dispatch": False,
     "transform_output": "default",
+    "skip_parameter_validation": False,
 }
 _threadlocal = threading.local()
 
@@ -54,6 +55,7 @@ def set_config(
     enable_cython_pairwise_dist=None,
     array_api_dispatch=None,
     transform_output=None,
+    skip_parameter_validation=None,
 ):
     """Set global scikit-learn configuration
 
@@ -134,6 +136,17 @@ def set_config(
 
         .. versionadded:: 1.2
 
+    skip_parameter_validation : bool, default=None
+        If True, disable the validation of the hyper-parameters types and values in the
+        fit method of estimators and for arguments passed to public helper functions.
+        It can save time in some situations but can lead to low level crashes and
+        exceptions with confusing error messages.
+
+        Note that For data parameters, such as X and y, only type validation is skipped
+        but validation with `check_array` will continue to run.
+
+        .. versionadded:: 1.3
+
     See Also
     --------
     config_context : Context manager for global scikit-learn configuration.
@@ -157,6 +170,8 @@ def set_config(
         local_config["array_api_dispatch"] = array_api_dispatch
     if transform_output is not None:
         local_config["transform_output"] = transform_output
+    if skip_parameter_validation is not None:
+        local_config["skip_parameter_validation"] = skip_parameter_validation
 
 
 @contextmanager
@@ -170,6 +185,7 @@ def config_context(
     enable_cython_pairwise_dist=None,
     array_api_dispatch=None,
     transform_output=None,
+    skip_parameter_validation=None,
 ):
     """Context manager for global scikit-learn configuration.
 
@@ -249,6 +265,17 @@ def config_context(
 
         .. versionadded:: 1.2
 
+    skip_parameter_validation : bool, default=None
+        If True, disable the validation of the hyper-parameters types and values in the
+        fit method of estimators and for arguments passed to public helper functions.
+        It can save time in some situations but can lead to low level crashes and
+        exceptions with confusing error messages.
+
+        Note that For data parameters, such as X and y, only type validation is skipped
+        but validation with `check_array` will continue to run.
+
+        .. versionadded:: 1.3
+
     Yields
     ------
     None.
@@ -286,6 +313,7 @@ def config_context(
         enable_cython_pairwise_dist=enable_cython_pairwise_dist,
         array_api_dispatch=array_api_dispatch,
         transform_output=transform_output,
+        skip_parameter_validation=skip_parameter_validation,
     )
 
     try:

diff --git a/sklearn/base.py b/sklearn/base.py
@@ -617,6 +617,9 @@ class attribute, which is a dictionary `param_name: list of constraints`. See
         the docstring of `validate_parameter_constraints` for a description of the
         accepted constraints.
         """
+        if get_config()["skip_parameter_validation"]:
+            return
+
         validate_parameter_constraints(
             self._parameter_constraints,
             self.get_params(deep=False),

diff --git a/sklearn/decomposition/_dict_learning.py b/sklearn/decomposition/_dict_learning.py
@@ -23,6 +23,7 @@
 from ..utils.validation import check_is_fitted
 from ..utils.parallel import delayed, Parallel
 from ..linear_model import Lasso, orthogonal_mp_gram, LassoLars, Lars
+from .._config import config_context
 
 
 def _check_positive_coding(method, positive):
@@ -2381,9 +2382,10 @@ def fit(self, X, y=None):
             for i, batch in zip(range(n_steps), batches):
                 X_batch = X_train[batch]
 
-                batch_cost = self._minibatch_step(
-                    X_batch, dictionary, self._random_state, i
-                )
+                with config_context(assume_finite=True, skip_parameter_validation=True):
+                    batch_cost = self._minibatch_step(
+                        X_batch, dictionary, self._random_state, i
+                    )
 
                 if self._check_convergence(
                     X_batch, batch_cost, dictionary, old_dict, n_samples, i, n_steps
@@ -2463,7 +2465,8 @@ def partial_fit(self, X, y=None):
         else:
             dictionary = self.components_
 
-        self._minibatch_step(X, dictionary, self._random_state, self.n_steps_)
+        with config_context(assume_finite=True, skip_parameter_validation=True):
+            self._minibatch_step(X, dictionary, self._random_state, self.n_steps_)
 
         self.components_ = dictionary
         self.n_steps_ += 1

diff --git a/sklearn/tests/test_config.py b/sklearn/tests/test_config.py
@@ -17,6 +17,7 @@ def test_config_context():
         "pairwise_dist_chunk_size": 256,
         "enable_cython_pairwise_dist": True,
         "transform_output": "default",
+        "skip_parameter_validation": False,
     }
 
     # Not using as a context manager affects nothing
@@ -33,6 +34,7 @@ def test_config_context():
             "pairwise_dist_chunk_size": 256,
             "enable_cython_pairwise_dist": True,
             "transform_output": "default",
+            "skip_parameter_validation": False,
         }
     assert get_config()["assume_finite"] is False
 
@@ -66,6 +68,7 @@ def test_config_context():
         "pairwise_dist_chunk_size": 256,
         "enable_cython_pairwise_dist": True,
         "transform_output": "default",
+        "skip_parameter_validation": False,
     }
 
     # No positional arguments

diff --git a/sklearn/utils/_param_validation.py b/sklearn/utils/_param_validation.py
@@ -14,6 +14,7 @@
 from scipy.sparse import issparse
 from scipy.sparse import csr_matrix
 
+from .._config import get_config
 from .validation import _is_arraylike_not_scalar
 
 
@@ -168,6 +169,8 @@ def decorator(func):
 
         @functools.wraps(func)
         def wrapper(*args, **kwargs):
+            if get_config()["skip_parameter_validation"]:
+                return func(*args, **kwargs)
 
             func_sig = signature(func)