Add sklearnex interface for polynomial kernel

Signed-off-by: SnigdhaSarkar16 <sarkarsnigdha16@gmail.com>

Author: SnigdhaSarkar16

sklearnex/svm/poly_kernel.py

@@ -7,19 +7,21 @@
 #
 #     http://www.apache.org/licenses/LICENSE-2.0
 #
-# Unless required by applicable law or agreed to in writing, software
+# Unless required by applicable law or agreed to in writing,
 # distributed under the License is distributed on an "AS IS" BASIS,
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
 # ==============================================================================
 
 import numpy as np
+
 from onedal.primitives import poly_kernel as onedal_poly_kernel
 
+
 def poly_kernel(X, Y=None, gamma=1.0, coef0=0.0, degree=3, queue=None):
     """
-    sklearnex interface for the polynomial kernel using oneDAL backend.
+    Sklearnex interface for the polynomial kernel using oneDAL backend.
 
     K(x, y) = (gamma * <x, y> + coef0) ** degree
     for each pair of rows x in X and y in Y.
@@ -49,4 +51,6 @@ def poly_kernel(X, Y=None, gamma=1.0, coef0=0.0, degree=3, queue=None):
     kernel_matrix : ndarray of shape (n_samples_X, n_samples_Y)
         Polynomial kernel Gram matrix.
     """
-    return onedal_poly_kernel(X, Y=Y, gamma=gamma, coef0=coef0, degree=degree, queue=queue)
+    return onedal_poly_kernel(
+        X, Y=Y, gamma=gamma, coef0=coef0, degree=degree, queue=queue
+    )

sklearnex/svm/tests/test_poly_kernel_sklearnex.py

@@ -7,25 +7,31 @@
 #
 #     http://www.apache.org/licenses/LICENSE-2.0
 #
-# Unless required by applicable law or agreed to in writing, software
+# Unless required by applicable law or agreed to in writing,
 # distributed under the License is distributed on an "AS IS" BASIS,
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
 # ==============================================================================
 
 import numpy as np
-from sklearnex.svm.poly_kernel import poly_kernel as skl_poly_kernel
-from onedal.primitives import poly_kernel as onedal_poly_kernel
+
+from sklearnex.svm.poly_kernel import poly_kernel
+
 
 def test_poly_kernel_basic():
     X = np.array([[1, 2], [3, 4]])
     Y = np.array([[5, 6], [7, 8]])
 
-    # sklearnex interface result
-    K_skl = skl_poly_kernel(X, Y, gamma=0.5, coef0=1.0, degree=2)
-    # direct oneDAL result
-    K_onedal = onedal_poly_kernel(X, Y, gamma=0.5, coef0=1.0, degree=2)
+    K = poly_kernel(X, Y, gamma=1.0, coef0=0.0, degree=2)
+
+    # expected polynomial kernel manually
+    expected = (np.dot(X, Y.T)) ** 2
+    assert np.allclose(K, expected), "Polynomial kernel computation is incorrect"
 
-    # check they are close
-    assert np.allclose(K_skl, K_onedal)
+
+def test_poly_kernel_default_Y():
+    X = np.array([[1, 2], [3, 4]])
+    K = poly_kernel(X)
+    expected = (np.dot(X, X.T)) ** 3  # default degree=3
+    assert np.allclose(K, expected), "Polynomial kernel with Y=None is incorrect"