Remove support_usm_ndarray

doc/sources/quick-start.rst

@@ -79,12 +79,13 @@ This example shows how to patch Intel(R) extension for Scikit-Learn by modifing
   :caption: Example: Drop-In Patching
    
     import numpy as np
+
     from sklearnex import patch_sklearn
     patch_sklearn()
 
     # You need to re-import scikit-learn algorithms after the patch
     from sklearn.cluster import KMeans
-  
+
     # The use of the original Scikit-learn is not changed
     X = np.array([[1,  2], [1,  4], [1,  0],
                 [10, 2], [10, 4], [10, 0]])

onedal/spmd/linear_model/incremental_linear_model.py

@@ -18,7 +18,6 @@
 
 from daal4py.sklearn._utils import get_dtype
 
-from ..._device_offload import support_usm_ndarray
 from ...common.hyperparameters import get_hyperparameters
 from ...datatypes import _convert_to_supported, to_table
 from ...linear_model import (
@@ -34,7 +33,6 @@ def _reset(self):
             IncrementalLinearRegression_nonSPMD, self
         )._get_backend("linear_model", "regression", "partial_train_result")
 
-    @support_usm_ndarray()
     def partial_fit(self, X, y, queue=None):
         """
         Computes partial data for linear regression
@@ -91,7 +89,3 @@ def partial_fit(self, X, y, queue=None):
             self._partial_result = module.partial_train(
                 policy, self._params, self._partial_result, X_table, y_table
             )
-
-    @support_usm_ndarray()
-    def finalize_fit(self, queue=None):
-        return super().finalize_fit(queue=queue)