Add dpnp tests

Author: vlad-perevezentsev

tests/test_mathematical.py

@@ -1370,6 +1370,40 @@ def test_power_scalar(shape, dtype):
     assert_allclose(result, expected, rtol=1e-6)
 
 
+class TestNanToNum:
+    @pytest.mark.parametrize("dtype", get_all_dtypes())
+    @pytest.mark.parametrize("shape", [(3,), (2, 3), (3, 2, 2)])
+    def test_nan_to_num(self, dtype, shape):
+        a = numpy.random.randn(*shape).astype(dtype)
+        if not dpnp.issubdtype(dtype, dpnp.integer):
+            a.flat[1] = numpy.nan
+        a_dp = dpnp.array(a)
+
+        result = dpnp.nan_to_num(a_dp)
+        expected = numpy.nan_to_num(a)
+        assert_allclose(result, expected)
+
+    @pytest.mark.parametrize(
+        "data", [[], [numpy.nan], [numpy.inf], [-numpy.inf]]
+    )
+    @pytest.mark.parametrize("dtype", get_float_complex_dtypes())
+    def test_empty_and_single_value_arrays(self, data, dtype):
+        a = numpy.array(data, dtype)
+        ia = dpnp.array(a)
+
+        result = dpnp.nan_to_num(ia)
+        expected = numpy.nan_to_num(a)
+        assert_allclose(result, expected)
+
+    def test_boolean_array(self):
+        a = numpy.array([True, False, numpy.nan], dtype=bool)
+        ia = dpnp.array(a)
+
+        result = dpnp.nan_to_num(ia)
+        expected = numpy.nan_to_num(a)
+        assert_allclose(result, expected)
+
+
 @pytest.mark.parametrize(
     "data",
     [[[1.0, -1.0], [0.1, -0.1]], [-2, -1, 0, 1, 2]],