Add sklearnex interface for polynomial kernel (poly_kernel)

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

Author: SnigdhaSarkar16

sklearnex/svm/poly_kernel.py

@@ -0,0 +1,52 @@
+# ==============================================================================
+# Copyright contributors to the oneDAL project
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# 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.
+
+    K(x, y) = (gamma * <x, y> + coef0) ** degree
+    for each pair of rows x in X and y in Y.
+
+    Parameters
+    ----------
+    X : array-like of shape (n_samples_X, n_features)
+        Input feature array.
+
+    Y : array-like of shape (n_samples_Y, n_features), default=None
+        Optional second feature array. If None, Y = X.
+
+    gamma : float, default=1.0
+        Scaling factor for the inner product.
+
+    coef0 : float, default=0.0
+        Constant term added to scaled inner product.
+
+    degree : int, default=3
+        Degree of the polynomial kernel.
+
+    queue : SyclQueue or None, default=None
+        Optional SYCL queue for device execution.
+
+    Returns
+    -------
+    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)

sklearnex/svm/tests/test_poly_kernel_sklearnex.py

@@ -0,0 +1,31 @@
+# ==============================================================================
+# Copyright contributors to the oneDAL project
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# 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
+
+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)
+
+    # check they are close
+    assert np.allclose(K_skl, K_onedal)