Add checks for nan, posinf, neginf args

Author: vlad-perevezentsev

dpnp/dpnp_iface_mathematical.py

@@ -2347,6 +2347,9 @@ def nan_to_num(x, copy=True, nan=0.0, posinf=None, neginf=None):
 
     dpnp.check_supported_arrays_type(x)
 
+    if not dpnp.isscalar(nan):
+        raise TypeError(f"nan must be a scalar, but got {type(nan)}")
+
     out = dpnp.empty_like(x) if copy else x
     x_type = x.dtype.type
 
@@ -2363,8 +2366,16 @@ def nan_to_num(x, copy=True, nan=0.0, posinf=None, neginf=None):
     )
     max_f, min_f = _get_max_min(x.real.dtype)
     if posinf is not None:
+        if not dpnp.isscalar(posinf):
+            raise TypeError(
+                f"posinf must be a scalar or None, but got {type(posinf)}"
+            )
         max_f = posinf
     if neginf is not None:
+        if not dpnp.isscalar(neginf):
+            raise TypeError(
+                f"neginf must be a scalar or None, but got {type(neginf)}"
+            )
         min_f = neginf
 
     for part, part_out in zip(parts, parts_out):

tests/test_mathematical.py

@@ -1149,6 +1149,25 @@ def test_boolean_array(self):
         expected = numpy.nan_to_num(a)
         assert_allclose(result, expected)
 
+    def test_errors(self):
+        ia = dpnp.array([0, 1, dpnp.nan, dpnp.inf, -dpnp.inf])
+
+        # unsupported type `a`
+        a_np = dpnp.asnumpy(ia)
+        assert_raises(TypeError, dpnp.nan_to_num, a_np)
+
+        # unsupported type `nan`
+        i_nan = dpnp.array(1)
+        assert_raises(TypeError, dpnp.nan_to_num, ia, nan=i_nan)
+
+        # unsupported type `posinf`
+        i_posinf = dpnp.array(1)
+        assert_raises(TypeError, dpnp.nan_to_num, ia, posinf=i_posinf)
+
+        # unsupported type `neginf`
+        i_neginf = dpnp.array(1)
+        assert_raises(TypeError, dpnp.nan_to_num, ia, neginf=i_neginf)
+
 
 class TestNextafter:
     @pytest.mark.parametrize("dt", get_float_dtypes())

tests/third_party/cupy/math_tests/test_misc.py

@@ -273,16 +273,17 @@ def test_nan_to_num_inplace(self, xp):
         assert x is y
         return y
 
+    @pytest.mark.skip(reason="nan, posinf, neginf as array are not supported")
     @pytest.mark.parametrize("kwarg", ["nan", "posinf", "neginf"])
     def test_nan_to_num_broadcast(self, kwarg):
         for xp in (numpy, cupy):
             x = xp.asarray([0, 1, xp.nan, 4], dtype=cupy.default_float_type())
             y = xp.zeros((2, 4), dtype=cupy.default_float_type())
-            with pytest.raises(ValueError):
+            with pytest.raises(TypeError):
                 xp.nan_to_num(x, **{kwarg: y})
             # dpnp.nan_to_num() doesn`t support a scalar as an input
             # convert 0.0 to 0-ndim array
-            with pytest.raises(ValueError):
+            with pytest.raises(TypeError):
                 x_ndim_0 = xp.array(0.0)
                 xp.nan_to_num(x_ndim_0, **{kwarg: y})