[enhancement] add sklearnex version of validate_data, ```_check…

…_sample_weight``` (#2177)

* add finiteness_checker pybind11 bindings

* added finiteness checker

* Update finiteness_checker.cpp

* Update finiteness_checker.cpp

* Update finiteness_checker.cpp

* Update finiteness_checker.cpp

* Update finiteness_checker.cpp

* Update finiteness_checker.cpp

* Rename finiteness_checker.cpp to finiteness_checker.cpp

* Update finiteness_checker.cpp

* add next step

* follow conventions

* make xtable explicit

* remove comment

* Update validation.py

* Update __init__.py

* Update validation.py

* Update __init__.py

* Update __init__.py

* Update validation.py

* Update _data_conversion.py

* Update _data_conversion.py

* Update policy_common.cpp

* Update policy_common.cpp

* Update _policy.py

* Update policy_common.cpp

* Rename finiteness_checker.cpp to finiteness_checker.cpp

* Create finiteness_checker.py

* Update validation.py

* Update __init__.py

* attempt at fixing circular imports again

* fix isort

* remove __init__ changes

* last move

* Update policy_common.cpp

* Update policy_common.cpp

* Update policy_common.cpp

* Update policy_common.cpp

* Update validation.py

* add testing

* isort

* attempt to fix module error

* add fptype

* fix typo

* Update validation.py

* remove sua_ifcae from to_table

* isort and black

* Update test_memory_usage.py

* format

* Update _data_conversion.py

* Update _data_conversion.py

* Update test_validation.py

* remove unnecessary code

* make reviewer changes

* make dtype check change

* add sparse testing

* try again

* try again

* try again

* temporary commit

* first attempt

* missing change?

* modify DummyEstimator for testing

* generalize DummyEstimator

* switch test

* further testing changes

* add initial validate_data test, will be refactored

* fixes for CI

* Update validation.py

* Update validation.py

* Update test_memory_usage.py

* Update base.py

* Update base.py

* improve tests

* fix logic

* fix logic

* fix logic again

* rename file

* Revert "rename file"

This reverts commit 8d47744.

* remove duplication

* fix imports

* Rename test_finite.py to test_validation.py

* Revert "Rename test_finite.py to test_validation.py"

This reverts commit ee799f6.

* updates

* Update validation.py

* fixes for some test failures

* fix text

* fixes for some failures

* make consistent

* fix bad logic

* fix in string

* attempt tp see if dataframe conversion is causing the issue

* fix iter problem

* fix testing issues

* formatting

* revert change

* fixes for pandas

* there is a slowdown with pandas that needs to be solved

* swap to transpose for speed

* more clarity

* add _check_sample_weight

* add more testing'

* rename

* remove unnecessary imports

* fix test slowness

* focus get_dataframes_and_queues

* put config_context around

* Update test_validation.py

* Update base.py

* Update test_validation.py

* generalize regex

* add fixes for sklearn 1.0 and input_name

* fixes for test failures

* Update validation.py

* Update test_validation.py

* Update validation.py

* formattintg

* make suggested changes

* follow changes made in #2126

* fix future device problem

* Update validation.py

* minor changes based on #2206, suggestions

* remove xp as keyword

* only_non_negative -> ensure_non_negative

* add commentary

* formatting

* address changes

* Update test_validation.py

* Update base.py

* Update test_validation.py

* Update sklearnex/utils/validation.py

Co-authored-by: ethanglaser <42726565+ethanglaser@users.noreply.github.com>

---------

Co-authored-by: ethanglaser <42726565+ethanglaser@users.noreply.github.com>

sklearnex/tests/test_memory_usage.py

@@ -35,10 +35,14 @@
     get_dataframes_and_queues,
 )
 from onedal.tests.utils._device_selection import get_queues, is_dpctl_device_available
-from onedal.utils._array_api import _get_sycl_namespace
 from onedal.utils._dpep_helpers import dpctl_available, dpnp_available
 from sklearnex import config_context
-from sklearnex.tests.utils import PATCHED_FUNCTIONS, PATCHED_MODELS, SPECIAL_INSTANCES
+from sklearnex.tests.utils import (
+    PATCHED_FUNCTIONS,
+    PATCHED_MODELS,
+    SPECIAL_INSTANCES,
+    DummyEstimator,
+)
 from sklearnex.utils._array_api import get_namespace
 
 if dpctl_available:
@@ -131,41 +135,6 @@ def gen_functions(functions):
 ORDER_DICT = {"F": np.asfortranarray, "C": np.ascontiguousarray}
 
 
-if _is_dpc_backend:
-
-    from sklearn.utils.validation import check_is_fitted
-
-    from onedal.datatypes import from_table, to_table
-
-    class DummyEstimatorWithTableConversions(BaseEstimator):
-
-        def fit(self, X, y=None):
-            sua_iface, xp, _ = _get_sycl_namespace(X)
-            X_table = to_table(X)
-            y_table = to_table(y)
-            # The presence of the fitted attributes (ending with a trailing
-            # underscore) is required for the correct check. The cleanup of
-            # the memory will occur at the estimator instance deletion.
-            self.x_attr_ = from_table(
-                X_table, sua_iface=sua_iface, sycl_queue=X.sycl_queue, xp=xp
-            )
-            self.y_attr_ = from_table(
-                y_table, sua_iface=sua_iface, sycl_queue=X.sycl_queue, xp=xp
-            )
-            return self
-
-        def predict(self, X):
-            # Checks if the estimator is fitted by verifying the presence of
-            # fitted attributes (ending with a trailing underscore).
-            check_is_fitted(self)
-            sua_iface, xp, _ = _get_sycl_namespace(X)
-            X_table = to_table(X)
-            returned_X = from_table(
-                X_table, sua_iface=sua_iface, sycl_queue=X.sycl_queue, xp=xp
-            )
-            return returned_X
-
-
 def gen_clsf_data(n_samples, n_features, dtype=None):
     data, label = make_classification(
         n_classes=2, n_samples=n_samples, n_features=n_features, random_state=777
@@ -369,7 +338,7 @@ def test_table_conversions_memory_leaks(dataframe, queue, order, data_shape, dty
         pytest.skip("SYCL device memory leak check requires the level zero sysman")
 
     _kfold_function_template(
-        DummyEstimatorWithTableConversions,
+        DummyEstimator,
         dataframe,
         data_shape,
         queue,

sklearnex/tests/utils/__init__.py

@@ -21,6 +21,7 @@
     SPECIAL_INSTANCES,
     UNPATCHED_FUNCTIONS,
     UNPATCHED_MODELS,
+    DummyEstimator,
     _get_processor_info,
     call_method,
     gen_dataset,
@@ -39,6 +40,7 @@
     "gen_models_info",
     "gen_dataset",
     "sklearn_clone_dict",
+    "DummyEstimator",
 ]
 
 _IS_INTEL = "GenuineIntel" in _get_processor_info()

sklearnex/tests/utils/base.py

@@ -32,8 +32,11 @@
 )
 from sklearn.datasets import load_diabetes, load_iris
 from sklearn.neighbors._base import KNeighborsMixin
+from sklearn.utils.validation import check_is_fitted
 
+from onedal.datatypes import from_table, to_table
 from onedal.tests.utils._dataframes_support import _convert_to_dataframe
+from onedal.utils._array_api import _get_sycl_namespace
 from sklearnex import get_patch_map, patch_sklearn, sklearn_is_patched, unpatch_sklearn
 from sklearnex.basic_statistics import BasicStatistics, IncrementalBasicStatistics
 from sklearnex.linear_model import LogisticRegression
@@ -369,3 +372,44 @@ def _get_processor_info():
         )
 
     return proc
+
+
+class DummyEstimator(BaseEstimator):
+
+    def fit(self, X, y=None):
+        sua_iface, xp, _ = _get_sycl_namespace(X)
+        X_table = to_table(X)
+        y_table = to_table(y)
+        # The presence of the fitted attributes (ending with a trailing
+        # underscore) is required for the correct check. The cleanup of
+        # the memory will occur at the estimator instance deletion.
+        if sua_iface:
+            self.x_attr_ = from_table(
+                X_table, sua_iface=sua_iface, sycl_queue=X.sycl_queue, xp=xp
+            )
+            self.y_attr_ = from_table(
+                y_table,
+                sua_iface=sua_iface,
+                sycl_queue=X.sycl_queue if y is None else y.sycl_queue,
+                xp=xp,
+            )
+        else:
+            self.x_attr = from_table(X_table)
+            self.y_attr = from_table(y_table)
+
+        return self
+
+    def predict(self, X):
+        # Checks if the estimator is fitted by verifying the presence of
+        # fitted attributes (ending with a trailing underscore).
+        check_is_fitted(self)
+        sua_iface, xp, _ = _get_sycl_namespace(X)
+        X_table = to_table(X)
+        if sua_iface:
+            returned_X = from_table(
+                X_table, sua_iface=sua_iface, sycl_queue=X.sycl_queue, xp=xp
+            )
+        else:
+            returned_X = from_table(X_table)
+
+        return returned_X

sklearnex/utils/__init__.py

@@ -14,6 +14,6 @@
 # limitations under the License.
 # ===============================================================================
 
-from .validation import _assert_all_finite
+from .validation import assert_all_finite
 
-__all__ = ["_assert_all_finite"]
+__all__ = ["assert_all_finite"]