fix an issue for F-contiguous arrays

Author: vtavana

dpnp/backend/extensions/blas/syrk.cpp

@@ -152,11 +152,20 @@ static sycl::event syrk_impl(sycl::queue &exec_q,
                 std::int64_t i = idx[0];
                 std::int64_t j = idx[1];
                 if (j > i) {
-                    res[j * ldc + i] = res[i * ldc + j];
+                    // result form row_major::syrk is row major and result form
+                    // column_major::syrk is column major, so copying upper
+                    // triangle to lower triangle is different for each case
+                    if (is_row_major) {
+                        // row-major: res[i][j] = res[i * ldc + j]
+                        res[j * ldc + i] = res[i * ldc + j];
+                    }
+                    else {
+                        // column-major: res[i][j] = res[i + j * ldc]
+                        res[i * ldc + j] = res[j * ldc + i];
+                    }
                 }
             });
     });
-
     return copy_event;
 }
 

dpnp/tests/test_product.py

@@ -1198,12 +1198,15 @@ def test_syrk(self, dt):
         assert result is iout
         assert_dtype_allclose(result, expected)
 
+        result = ia.mT @ ia
+        expected = a.T @ a
+        assert_dtype_allclose(result, expected)
+
     @pytest.mark.parametrize(
         "order, out_order",
         [("C", "C"), ("C", "F"), ("F", "C"), ("F", "F")],
     )
     def test_syrk_out_order(self, order, out_order):
-        # test syrk with out keyword
         a = generate_random_numpy_array((5, 4), order=order, low=-5, high=5)
         out = numpy.empty((5, 5), dtype=a.dtype, order=out_order)
         ia, iout = dpnp.array(a), dpnp.array(out)
@@ -1215,6 +1218,14 @@ def test_syrk_out_order(self, order, out_order):
         assert result.flags.f_contiguous == expected.flags.f_contiguous
         assert_dtype_allclose(result, expected)
 
+    @pytest.mark.parametrize("order", ["F", "C"])
+    def test_syrk_order(self, order):
+        a = generate_random_numpy_array((4, 6), order=order, low=-5, high=5)
+        ia = dpnp.array(a)
+        expected = numpy.matmul(a, a.T)
+        result = dpnp.matmul(ia, ia.mT)
+        assert_dtype_allclose(result, expected)
+
     def test_bool(self):
         a = generate_random_numpy_array((3, 4), dtype=dpnp.bool)
         b = generate_random_numpy_array((4, 5), dtype=dpnp.bool)