address comments

dpnp/dpnp_algo/dpnp_elementwise_common.py

@@ -1418,6 +1418,13 @@ def dpnp_multiply(x1, x2, out=None, order="K"):
 def dpnp_negative(x, out=None, order="K"):
     """Invokes negative() from dpctl.tensor implementation for negative() function."""
 
+    # TODO: discuss with dpctl if the check is needed to be moved there
+    if not dpnp.isscalar(x) and x.dtype == dpnp.bool:
+        raise TypeError(
+            "DPNP boolean negative, the `-` operator, is not supported, "
+            "use the `~` operator or the logical_not function instead."
+        )
+
     # dpctl.tensor only works with usm_ndarray
     x1_usm = dpnp.get_usm_ndarray(x)
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
@@ -1594,6 +1601,10 @@ def dpnp_right_shift(x1, x2, out=None, order="K"):
 def dpnp_sign(x, out=None, order="K"):
     """Invokes sign() from dpctl.tensor implementation for sign() function."""
 
+    # TODO: discuss with dpctl if the check is needed to be moved there
+    if not dpnp.isscalar(x) and x.dtype == dpnp.bool:
+        raise TypeError("DPNP boolean sign is not supported.")
+
     # dpctl.tensor only works with usm_ndarray
     x1_usm = dpnp.get_usm_ndarray(x)
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)

dpnp/dpnp_iface_logic.py

@@ -95,8 +95,8 @@ def all(x, /, axis=None, out=None, keepdims=False, *, where=True):
     Returns
     -------
     dpnp.ndarray
-        An array with a data type of `bool`
-        containing the results of the logical AND reduction.
+    An array with a data type of `bool`
+    containing the results of the logical AND reduction.
 
     Limitations
     -----------
@@ -160,8 +160,8 @@ def allclose(x1, x2, rtol=1.0e-5, atol=1.0e-8, **kwargs):
 
     Limitations
     -----------
-    Parameters ``x1`` and ``x2`` are supported as either :obj:`dpnp.ndarray` or scalar.
-    Keyword arguments ``kwargs`` are currently unsupported.
+    Parameters `x1` and `x2` are supported as either :class:`dpnp.ndarray` or scalar.
+    Keyword argument `kwargs` is currently unsupported.
     Otherwise the functions will be executed sequentially on CPU.
     Input array data types are limited by supported DPNP :ref:`Data types`.
 
@@ -276,7 +276,7 @@ def equal(
     Returns
     -------
     out : dpnp.ndarray
-        Output array of bool type, element-wise comparison of `x1` and `x2`.
+    Output array of bool type, element-wise comparison of `x1` and `x2`.
 
     Limitations
     -----------
@@ -352,7 +352,7 @@ def greater(
     Returns
     -------
     out : dpnp.ndarray
-        Output array of bool type, element-wise comparison of `x1` and `x2`.
+    Output array of bool type, element-wise comparison of `x1` and `x2`.
 
     Limitations
     -----------
@@ -422,7 +422,7 @@ def greater_equal(
     Returns
     -------
     out : dpnp.ndarray
-        Output array of bool type, element-wise comparison of `x1` and `x2`.
+    Output array of bool type, element-wise comparison of `x1` and `x2`.
 
     Limitations
     -----------
@@ -480,8 +480,8 @@ def isclose(x1, x2, rtol=1e-05, atol=1e-08, equal_nan=False):
 
     Limitations
     -----------
-    ``x2`` is supported to be integer if ``x1`` is :obj:`dpnp.ndarray` or
-    at least either ``x1`` or ``x2`` should be as :obj:`dpnp.ndarray`.
+    `x2` is supported to be integer if `x1` is :class:`dpnp.ndarray` or
+    at least either `x1` or `x2` should be as :class:`dpnp.ndarray`.
     Otherwise the function will be executed sequentially on CPU.
     Input array data types are limited by supported DPNP :ref:`Data types`.
 
@@ -678,7 +678,7 @@ def less(
     Returns
     -------
     out : dpnp.ndarray
-        Output array of bool type, element-wise comparison of `x1` and `x2`.
+    Output array of bool type, element-wise comparison of `x1` and `x2`.
 
     Limitations
     -----------
@@ -748,7 +748,7 @@ def less_equal(
     Returns
     -------
     out : dpnp.ndarray
-        Output array of bool type, element-wise comparison of `x1` and `x2`.
+    Output array of bool type, element-wise comparison of `x1` and `x2`.
 
     Limitations
     -----------
@@ -818,8 +818,8 @@ def logical_and(
     Returns
     -------
     out : dpnp.ndarray
-        Boolean result of the logical AND operation applied to the elements
-        of `x1` and `x2`; the shape is determined by broadcasting.
+    Boolean result of the logical AND operation applied to the elements
+    of `x1` and `x2`; the shape is determined by broadcasting.
 
     Limitations
     -----------
@@ -891,8 +891,8 @@ def logical_not(
     Returns
     -------
     out : dpnp.ndarray
-        Boolean result with the same shape as `x` of the NOT operation
-        on elements of `x`.
+    Boolean result with the same shape as `x` of the NOT operation
+    on elements of `x`.
 
     Limitations
     -----------
@@ -953,8 +953,8 @@ def logical_or(
     Returns
     -------
     out : dpnp.ndarray
-        Boolean result of the logical OR operation applied to the elements
-        of `x1` and `x2`; the shape is determined by broadcasting.
+    Boolean result of the logical OR operation applied to the elements
+    of `x1` and `x2`; the shape is determined by broadcasting.
 
     Limitations
     -----------
@@ -1027,8 +1027,8 @@ def logical_xor(
     Returns
     -------
     out : dpnp.ndarray
-        Boolean result of the logical XOR operation applied to the elements
-        of `x1` and `x2`; the shape is determined by broadcasting.
+    Boolean result of the logical XOR operation applied to the elements
+    of `x1` and `x2`; the shape is determined by broadcasting.
 
     Limitations
     -----------

dpnp/dpnp_iface_mathematical.py

@@ -1507,7 +1507,7 @@ def negative(
     Returns
     -------
     out : dpnp.ndarray
-        The numerical negative of each element of `x`.
+    The numerical negative of each element of `x`.
 
     Limitations
     -----------
@@ -1805,7 +1805,7 @@ def sign(
     Returns
     -------
     out : dpnp.ndarray
-        The indication of the sign of each element of `x`.
+    The indication of the sign of each element of `x`.
 
     Limitations
     -----------
@@ -1814,6 +1814,7 @@ def sign(
     Keyword argument `kwargs` is currently unsupported.
     Otherwise the function will be executed sequentially on CPU.
     Input array data types are limited by supported DPNP :ref:`Data types`.
+    However, if the input array data type is complex, the function will be executed sequentially on CPU.
 
     Examples
     --------

dpnp/dpnp_utils/dpnp_algo_utils.pyx

@@ -131,8 +131,8 @@ def call_origin(function, *args, **kwargs):
     if not allow_fallback and config.__DPNP_RAISE_EXCEPION_ON_NUMPY_FALLBACK__ == 1:
         raise NotImplementedError(f"Requested funtion={function.__name__} with args={args} and kwargs={kwargs} "
                                    "isn't currently supported and would fall back on NumPy implementation. "
-                                   "Define enviroment variable `DPNP_RAISE_EXCEPION_ON_NUMPY_FALLBACK` to `0` "
-                                   "if the fall back is required to be supported without rasing an exception.")
+                                   "Define environment variable `DPNP_RAISE_EXCEPION_ON_NUMPY_FALLBACK` to `0` "
+                                   "if the fall back is required to be supported without raising an exception.")
 
     dpnp_inplace = kwargs.pop("dpnp_inplace", False)
     sycl_queue = kwargs.pop("sycl_queue", None)

tests/test_mathematical.py

@@ -392,14 +392,37 @@ def test_nancumsum(array):
     [[[1.0, -1.0], [0.1, -0.1]], [-2, -1, 0, 1, 2]],
     ids=["[[1., -1.], [0.1, -0.1]]", "[-2, -1, 0, 1, 2]"],
 )
-@pytest.mark.parametrize("dtype", get_all_dtypes(no_bool=True, no_complex=True))
+@pytest.mark.parametrize("dtype", get_all_dtypes())
 def test_negative(data, dtype):
     np_a = numpy.array(data, dtype=dtype)
     dpnp_a = dpnp.array(data, dtype=dtype)
 
-    result = dpnp.negative(dpnp_a)
-    expected = numpy.negative(np_a)
-    assert_allclose(result, expected)
+    if dtype == dpnp.bool:
+        with pytest.raises(TypeError):
+            dpnp.negative(dpnp_a)
+    else:
+        result = dpnp.negative(dpnp_a)
+        expected = numpy.negative(np_a)
+        assert_allclose(result, expected)
+
+
+@pytest.mark.parametrize(
+    "data",
+    [[2, 0, -2], [1.1, -1.1]],
+    ids=["[2, 0, -2]", "[1.1, -1.1]"],
+)
+@pytest.mark.parametrize("dtype", get_all_dtypes(no_complex=True))
+def test_sign(data, dtype):
+    np_a = numpy.array(data, dtype=dtype)
+    dpnp_a = dpnp.array(data, dtype=dtype)
+
+    if dtype == dpnp.bool:
+        with pytest.raises(TypeError):
+            dpnp.sign(dpnp_a)
+    else:
+        result = dpnp.sign(dpnp_a)
+        expected = numpy.sign(np_a)
+        assert_allclose(result, expected)
 
 
 @pytest.mark.parametrize("val_type", get_all_dtypes(no_none=True))

tests/test_usm_type.py

@@ -249,8 +249,10 @@ def test_meshgrid(usm_type_x, usm_type_y):
     "func,data",
     [
         pytest.param("ceil", [-1.7, -1.5, -0.2, 0.2, 1.5, 1.7, 2.0]),
-        pytest.param("floor", [-1.7, -1.5, -0.2, 0.2, 1.5, 1.7, 2.0]),
         pytest.param("conjugate", [[1.0 + 1.0j, 0.0], [0.0, 1.0 + 1.0j]]),
+        pytest.param("floor", [-1.7, -1.5, -0.2, 0.2, 1.5, 1.7, 2.0]),
+        pytest.param("negative", [1.0, -1.0]),
+        pytest.param("sign", [-5.0, 4.5]),
         pytest.param("sqrt", [1.0, 3.0, 9.0]),
         pytest.param("trunc", [-1.7, -1.5, -0.2, 0.2, 1.5, 1.7, 2.0]),
     ],