fix more tests

Author: icfaust

onedal/svm/tests/test_nusvc.py

@@ -39,7 +39,7 @@ def _test_libsvm_parameters(queue, array_constr, dtype):
         clf.dual_coef_, [[-0.04761905, -0.0952381, 0.0952381, 0.04761905]]
     )
     assert_array_equal(clf.support_, [0, 1, 3, 4])
-    assert_array_equal(clf.support_vectors_, X[clf.support_])
+    assert_array_equal(clf.support_vectors_, X[clf.support_.astype(int)])
     assert_array_equal(clf.intercept_, [0.0])
     assert_array_equal(clf.predict(X, queue=queue), y)
 
@@ -70,7 +70,7 @@ def test_sample_weight(queue):
     y = np.array([1, 1, 1, 2, 2, 2])
 
     clf = NuSVC(kernel="linear")
-    clf.fit(X, y, sample_weight=[1] * 6, queue=queue)
+    clf.fit(X, y, sample_weight=np.array([1] * 6), queue=queue)
     assert_array_almost_equal(clf.intercept_, [0.0])
 
 

onedal/svm/tests/test_svc.py

@@ -89,7 +89,7 @@ def test_sample_weight(queue):
     y = np.array([1, 1, 1, 2, 2, 2])
 
     clf = SVC(kernel="linear")
-    clf.fit(X, y, sample_weight=[1] * 6, queue=queue)
+    clf.fit(X, y, sample_weight=np.array([1] * 6), queue=queue)
     assert_array_almost_equal(clf.intercept_, [0.0])
 
 

onedal/svm/tests/test_svr.py

@@ -18,6 +18,7 @@
 import pytest
 from numpy.testing import assert_allclose, assert_array_almost_equal, assert_array_equal
 from sklearn import datasets
+from sklearn.metrics import r2_score
 from sklearn.metrics.pairwise import rbf_kernel
 from sklearn.svm import SVR as SklearnSVR
 
@@ -176,10 +177,12 @@ def test_synth_linear_compare_with_sklearn(queue, C):
 
 def _test_synth_poly_compare_with_sklearn(queue, params):
     x, y = datasets.make_regression(**synth_params)
-    clf = SVR(kernel="poly", **params)
+    gamma = 1.0 / (x.shape[1] * x.var())
+    clf = SVR(kernel="poly", gamma=gamma, **params)
     clf.fit(x, y, queue=queue)
-    result = clf.score(x, y, queue=queue)
+    result = r2_score(y, clf.predict(x, queue=queue))
 
+    # gamma='scale' by default in sklearn
     clf = SklearnSVR(kernel="poly", **params)
     clf.fit(x, y)
     expected = clf.score(x, y)
@@ -193,8 +196,8 @@ def _test_synth_poly_compare_with_sklearn(queue, params):
 @pytest.mark.parametrize(
     "params",
     [
-        {"degree": 2, "coef0": 0.1, "gamma": "scale", "C": 100},
-        {"degree": 3, "coef0": 0.0, "gamma": "scale", "C": 1000},
+        {"degree": 2, "coef0": 0.1, "C": 100},
+        {"degree": 3, "coef0": 0.0, "C": 1000},
     ],
 )
 def test_synth_poly_compare_with_sklearn(queue, params):