From 08fe8bac5fdb329d685b95a9d7b7947b01b13af6 Mon Sep 17 00:00:00 2001
From: Vahid Tavanashad <vahid.tavanashad@intel.com>
Date: Fri, 12 Jan 2024 10:32:40 -0600
Subject: [PATCH 1/3] update out keyword elementwise

update out keyword elementwise
---
 doc/reference/math.rst                    |   1 +
 doc/reference/ufunc.rst                   |   2 +
 dpnp/dpnp_algo/dpnp_elementwise_common.py | 340 +++++++--
 dpnp/dpnp_iface_mathematical.py           |   2 +-
 dpnp/dpnp_iface_trigonometric.py          |   2 +-
 tests/test_umath.py                       | 801 ++++++----------------
 6 files changed, 469 insertions(+), 679 deletions(-)

diff --git a/doc/reference/math.rst b/doc/reference/math.rst
index 430ce5b6de67..2b8b2befd799 100644
--- a/doc/reference/math.rst
+++ b/doc/reference/math.rst
@@ -205,6 +205,7 @@ Miscellaneous
    dpnp.sqrt
    dpnp.cbrt
    dpnp.square
+   dpnp.rsqrt
    dpnp.abs
    dpnp.absolute
    dpnp.fabs
diff --git a/doc/reference/ufunc.rst b/doc/reference/ufunc.rst
index 4c1e9f4d5d98..025692a0adf8 100644
--- a/doc/reference/ufunc.rst
+++ b/doc/reference/ufunc.rst
@@ -44,8 +44,10 @@ Math operations
    dpnp.log1p
    dpnp.proj
    dpnp.sqrt
+   dpnp.cbrt
    dpnp.square
    dpnp.reciprocal
+   dpnp.rsqrt
    dpnp.gcd
    dpnp.lcm
 
diff --git a/dpnp/dpnp_algo/dpnp_elementwise_common.py b/dpnp/dpnp_algo/dpnp_elementwise_common.py
index b6bf9faf8ace..5f1441f423a0 100644
--- a/dpnp/dpnp_algo/dpnp_elementwise_common.py
+++ b/dpnp/dpnp_algo/dpnp_elementwise_common.py
@@ -273,7 +273,10 @@ def dpnp_abs(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = abs_func(x1_usm, out=out_usm, order=order)
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _acos_docstring = """
@@ -314,7 +317,10 @@ def dpnp_acos(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = acos_func(x1_usm, out=out_usm, order=order)
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _acosh_docstring = """
@@ -355,7 +361,10 @@ def dpnp_acosh(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = acosh_func(x1_usm, out=out_usm, order=order)
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _add_docstring = """
@@ -401,7 +410,10 @@ def dpnp_add(x1, x2, out=None, order="K"):
     res_usm = add_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _asin_docstring = """
@@ -442,7 +454,10 @@ def dpnp_asin(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = asin_func(x1_usm, out=out_usm, order=order)
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _asinh_docstring = """
@@ -483,7 +498,10 @@ def dpnp_asinh(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = asinh_func(x1_usm, out=out_usm, order=order)
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _atan_docstring = """
@@ -524,7 +542,10 @@ def dpnp_atan(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = atan_func(x1_usm, out=out_usm, order=order)
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _atan2_docstring = """
@@ -574,7 +595,10 @@ def dpnp_atan2(x1, x2, out=None, order="K"):
     res_usm = atan2_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _atanh_docstring = """
@@ -615,7 +639,10 @@ def dpnp_atanh(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = atanh_func(x1_usm, out=out_usm, order=order)
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _bitwise_and_docstring = """
@@ -659,7 +686,10 @@ def dpnp_bitwise_and(x1, x2, out=None, order="K"):
     res_usm = bitwise_and_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _bitwise_or_docstring = """
@@ -703,7 +733,10 @@ def dpnp_bitwise_or(x1, x2, out=None, order="K"):
     res_usm = bitwise_or_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _bitwise_xor_docstring = """
@@ -747,7 +780,10 @@ def dpnp_bitwise_xor(x1, x2, out=None, order="K"):
     res_usm = bitwise_xor_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _cbrt_docstring = """
@@ -787,7 +823,10 @@ def dpnp_cbrt(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = cbrt_func(x1_usm, out=out_usm, order=order)
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _ceil_docstring = """
@@ -827,7 +866,10 @@ def dpnp_ceil(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = ceil_func(x1_usm, out=out_usm, order=order)
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _conj_docstring = """
@@ -866,7 +908,10 @@ def dpnp_conj(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = conj_func(x1_usm, out=out_usm, order=order)
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _copysign_docstring = """
@@ -907,7 +952,10 @@ def dpnp_copysign(x1, x2, out=None, order="K"):
     res_usm = copysign_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _cos_docstring = """
@@ -947,7 +995,10 @@ def dpnp_cos(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = cos_func(x1_usm, out=out_usm, order=order)
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _cosh_docstring = """
@@ -987,7 +1038,10 @@ def dpnp_cosh(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = cosh_func(x1_usm, out=out_usm, order=order)
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _divide_docstring = """
@@ -1033,7 +1087,10 @@ def dpnp_divide(x1, x2, out=None, order="K"):
     res_usm = divide_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _equal_docstring = """
@@ -1073,7 +1130,10 @@ def dpnp_equal(x1, x2, out=None, order="K"):
     res_usm = equal_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _exp_docstring = """
@@ -1114,7 +1174,10 @@ def dpnp_exp(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = exp_func(x1_usm, out=out_usm, order=order)
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _exp2_docstring = """
@@ -1155,7 +1218,10 @@ def dpnp_exp2(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = exp2_func(x1_usm, out=out_usm, order=order)
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _expm1_docstring = """
@@ -1198,7 +1264,10 @@ def dpnp_expm1(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = expm1_func(x1_usm, out=out_usm, order=order)
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _floor_docstring = """
@@ -1238,7 +1307,10 @@ def dpnp_floor(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = floor_func(x1_usm, out=out_usm, order=order)
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _floor_divide_docstring = """
@@ -1282,7 +1354,10 @@ def dpnp_floor_divide(x1, x2, out=None, order="K"):
     res_usm = floor_divide_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _greater_docstring = """
@@ -1322,7 +1397,10 @@ def dpnp_greater(x1, x2, out=None, order="K"):
     res_usm = greater_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _greater_equal_docstring = """
@@ -1364,7 +1442,10 @@ def dpnp_greater_equal(x1, x2, out=None, order="K"):
     res_usm = greater_equal_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _hypot_docstring = """
@@ -1410,7 +1491,10 @@ def dpnp_hypot(x1, x2, out=None, order="K"):
     res_usm = hypot_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _imag_docstring = """
@@ -1447,7 +1531,10 @@ def dpnp_imag(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = imag_func(x1_usm, out=out_usm, order=order)
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _invert_docstring = """
@@ -1482,7 +1569,10 @@ def dpnp_invert(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = invert_func(x_usm, out=out_usm, order=order)
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _isfinite_docstring = """
@@ -1517,7 +1607,10 @@ def dpnp_isfinite(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = isfinite_func(x1_usm, out=out_usm, order=order)
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _isinf_docstring = """
@@ -1551,7 +1644,10 @@ def dpnp_isinf(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = isinf_func(x1_usm, out=out_usm, order=order)
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _isnan_docstring = """
@@ -1585,7 +1681,10 @@ def dpnp_isnan(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = isnan_func(x1_usm, out=out_usm, order=order)
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _left_shift_docstring = """
@@ -1629,7 +1728,10 @@ def dpnp_left_shift(x1, x2, out=None, order="K"):
     res_usm = left_shift_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _less_docstring = """
@@ -1669,7 +1771,10 @@ def dpnp_less(x1, x2, out=None, order="K"):
     res_usm = less_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _less_equal_docstring = """
@@ -1711,7 +1816,10 @@ def dpnp_less_equal(x1, x2, out=None, order="K"):
     res_usm = less_equal_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _log_docstring = """
@@ -1752,7 +1860,10 @@ def dpnp_log(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = log_func(x1_usm, out=out_usm, order=order)
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _log10_docstring = """
@@ -1793,7 +1904,10 @@ def dpnp_log10(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = log10_func(x1_usm, out=out_usm, order=order)
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _log1p_docstring = """
@@ -1833,7 +1947,10 @@ def dpnp_log1p(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = log1p_func(x1_usm, out=out_usm, order=order)
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _log2_docstring = """
@@ -1874,7 +1991,10 @@ def dpnp_log2(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = log2_func(x1_usm, out=out_usm, order=order)
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _logaddexp_docstring = """
@@ -1922,7 +2042,10 @@ def dpnp_logaddexp(x1, x2, out=None, order="K"):
     res_usm = logaddexp_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _logical_and_docstring = """
@@ -1963,7 +2086,10 @@ def dpnp_logical_and(x1, x2, out=None, order="K"):
     res_usm = logical_and_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _logical_not_docstring = """
@@ -1998,7 +2124,10 @@ def dpnp_logical_not(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = logical_not_func(x_usm, out=out_usm, order=order)
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _logical_or_docstring = """
@@ -2039,7 +2168,10 @@ def dpnp_logical_or(x1, x2, out=None, order="K"):
     res_usm = logical_or_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _logical_xor_docstring = """
@@ -2080,7 +2212,10 @@ def dpnp_logical_xor(x1, x2, out=None, order="K"):
     res_usm = logical_xor_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _maximum_docstring = """
@@ -2120,7 +2255,10 @@ def dpnp_maximum(x1, x2, out=None, order="K"):
     res_usm = maximum_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _minimum_docstring = """
@@ -2160,7 +2298,10 @@ def dpnp_minimum(x1, x2, out=None, order="K"):
     res_usm = minimum_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _multiply_docstring = """
@@ -2210,7 +2351,10 @@ def dpnp_multiply(x1, x2, out=None, order="K"):
     res_usm = multiply_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _negative_docstring = """
@@ -2250,7 +2394,10 @@ def dpnp_negative(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = negative_func(x1_usm, out=out_usm, order=order)
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _not_equal_docstring = """
@@ -2292,7 +2439,10 @@ def dpnp_not_equal(x1, x2, out=None, order="K"):
     res_usm = not_equal_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _positive_docstring = """
@@ -2331,7 +2481,10 @@ def dpnp_positive(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = positive_func(x1_usm, out=out_usm, order=order)
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _power_docstring = """
@@ -2378,7 +2531,10 @@ def dpnp_power(x1, x2, out=None, order="K"):
     res_usm = power_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _proj_docstring = """
@@ -2412,7 +2568,10 @@ def dpnp_proj(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = proj_func(x1_usm, out=out_usm, order=order)
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _real_docstring = """
@@ -2449,7 +2608,10 @@ def dpnp_real(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = real_func(x1_usm, out=out_usm, order=order)
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _remainder_docstring = """
@@ -2490,7 +2652,10 @@ def dpnp_remainder(x1, x2, out=None, order="K"):
     res_usm = remainder_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _right_shift_docstring = """
@@ -2533,7 +2698,10 @@ def dpnp_right_shift(x1, x2, out=None, order="K"):
     res_usm = right_shift_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _round_docstring = """
@@ -2573,7 +2741,10 @@ def dpnp_round(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = round_func(x1_usm, out=out_usm, order=order)
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _rsqrt_docstring = """
@@ -2608,7 +2779,10 @@ def dpnp_rsqrt(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = rsqrt_func(x1_usm, out=out_usm, order=order)
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _sign_docstring = """
@@ -2650,7 +2824,10 @@ def dpnp_sign(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = sign_func(x1_usm, out=out_usm, order=order)
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _signbit_docstring = """
@@ -2685,7 +2862,10 @@ def dpnp_signbit(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = signbit_func(x1_usm, out=out_usm, order=order)
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _sin_docstring = """
@@ -2725,7 +2905,10 @@ def dpnp_sin(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = sin_func(x1_usm, out=out_usm, order=order)
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _sinh_docstring = """
@@ -2765,7 +2948,10 @@ def dpnp_sinh(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = sinh_func(x1_usm, out=out_usm, order=order)
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _sqrt_docstring = """
@@ -2804,7 +2990,10 @@ def dpnp_sqrt(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = sqrt_func(x_usm, out=out_usm, order=order)
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _square_docstring = """
@@ -2843,7 +3032,10 @@ def dpnp_square(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = square_func(x_usm, out=out_usm, order=order)
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _subtract_docstring = """
@@ -2904,7 +3096,10 @@ def dpnp_subtract(x1, x2, out=None, order="K"):
     res_usm = subtract_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _tan_docstring = """
@@ -2944,7 +3139,10 @@ def dpnp_tan(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = tan_func(x1_usm, out=out_usm, order=order)
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _tanh_docstring = """
@@ -2984,7 +3182,10 @@ def dpnp_tanh(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = tanh_func(x1_usm, out=out_usm, order=order)
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
 
 
 _trunc_docstring = """
@@ -3026,4 +3227,7 @@ def dpnp_trunc(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = trunc_func(x1_usm, out=out_usm, order=order)
-    return dpnp_array._create_from_usm_ndarray(res_usm)
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
diff --git a/dpnp/dpnp_iface_mathematical.py b/dpnp/dpnp_iface_mathematical.py
index a38fe9b8cfbe..add9c1304ce6 100644
--- a/dpnp/dpnp_iface_mathematical.py
+++ b/dpnp/dpnp_iface_mathematical.py
@@ -574,7 +574,7 @@ def copysign(
     Parameters `where`, `dtype` and `subok` are supported with their default values.
     Keyword argument `kwargs` is currently unsupported.
     Otherwise the function will be executed sequentially on CPU.
-    Input array data types are limited by supported real data types.
+    Input array data types are limited by supported real-valued data types.
 
     See Also
     --------
diff --git a/dpnp/dpnp_iface_trigonometric.py b/dpnp/dpnp_iface_trigonometric.py
index 18c874215e43..f21f67f43689 100644
--- a/dpnp/dpnp_iface_trigonometric.py
+++ b/dpnp/dpnp_iface_trigonometric.py
@@ -437,7 +437,7 @@ def arctan2(
     Parameters `where`, `dtype` and `subok` are supported with their default values.
     Keyword arguments `kwargs` are currently unsupported.
     Otherwise the function will be executed sequentially on CPU.
-    Input array data types are limited by supported DPNP :ref:`Data types`.
+    Input array data types are limited by real-valued data types.
 
     See Also
     --------
diff --git a/tests/test_umath.py b/tests/test_umath.py
index 35955c935bcb..05c75b51a6ae 100644
--- a/tests/test_umath.py
+++ b/tests/test_umath.py
@@ -2,15 +2,13 @@
 import pytest
 from numpy.testing import (
     assert_allclose,
-    assert_array_almost_equal,
-    assert_array_equal,
 )
 
 import dpnp
 
 from .helper import (
+    assert_dtype_allclose,
     get_all_dtypes,
-    get_complex_dtypes,
     get_float_dtypes,
     has_support_aspect16,
     has_support_aspect64,
@@ -93,65 +91,60 @@ def test_umaths(test_cases):
     assert_allclose(result, expected, rtol=1e-6)
 
 
-class TestSin:
-    @pytest.mark.parametrize(
-        "dtype", get_all_dtypes(no_bool=True, no_complex=True)
-    )
-    def test_sin(self, dtype):
-        np_array = numpy.arange(10, dtype=dtype)
-        np_out = numpy.empty(10, dtype=numpy.float64)
-
-        # DPNP
-        dp_out_dtype = dpnp.float32
-        if has_support_aspect64() and dtype != dpnp.float32:
-            dp_out_dtype = dpnp.float64
-
-        dp_out = dpnp.array(np_out, dtype=dp_out_dtype)
-        dp_array = dpnp.array(np_array, dtype=dtype)
-        result = dpnp.sin(dp_array, out=dp_out)
-
-        # original
-        expected = numpy.sin(np_array, out=np_out)
+def _get_numpy_arrays(func_name, dtype, range):
+    """
+    Return a sample array and an output array.
+
+    Create an appropriate array specified by `dtype` and `range` which is used as
+    an input for a function specified by `func_name` to obtain the output.
+    """
+    low = range[0]
+    high = range[1]
+    size = range[2]
+    if dtype == numpy.bool_:
+        np_array = numpy.arange(2, dtype=dtype)
+        result = getattr(numpy, func_name)(np_array)
+    elif dpnp.issubdtype(dtype, dpnp.complexfloating):
+        a = numpy.random.uniform(low=low, high=high, size=size)
+        b = numpy.random.uniform(low=low, high=high, size=size)
+        np_array = numpy.array(a + 1j * b, dtype=dtype)
+        result = getattr(numpy, func_name)(np_array)
+    else:
+        a = numpy.random.uniform(low=low, high=high, size=size)
+        np_array = numpy.array(a, dtype=dtype)
+        result = getattr(numpy, func_name)(np_array)
 
-        precision = numpy.finfo(dtype=result.dtype).precision
-        assert_array_almost_equal(expected, result.asnumpy(), decimal=precision)
+    return np_array, result
 
-    @pytest.mark.parametrize("dtype", get_complex_dtypes())
-    def test_sin_complex(self, dtype):
-        np_array = numpy.arange(10, 20, dtype=dtype)
-        np_out = numpy.empty(10, dtype=numpy.complex128)
 
-        # DPNP
-        dp_out_dtype = dpnp.complex64
+def _get_output_data_type(dtype):
+    """Return a data type specified by input `dtype` and device capabilities."""
+    if dpnp.issubdtype(dtype, dpnp.bool):
+        out_dtype = dpnp.float16 if has_support_aspect16() else dpnp.float32
+    elif dpnp.issubdtype(dtype, dpnp.complexfloating):
+        out_dtype = dpnp.complex64
         if has_support_aspect64() and dtype != dpnp.complex64:
-            dp_out_dtype = dpnp.complex128
-
-        dp_out = dpnp.array(np_out, dtype=dp_out_dtype)
-        dp_array = dpnp.array(np_array, dtype=dtype)
-        result = dpnp.sin(dp_array, out=dp_out)
+            out_dtype = dpnp.complex128
+    else:
+        out_dtype = dpnp.float32
+        if has_support_aspect64() and dtype != dpnp.float32:
+            out_dtype = dpnp.float64
 
-        # original
-        expected = numpy.sin(np_array, out=np_out)
+    return out_dtype
 
-        precision = numpy.finfo(dtype=result.dtype).precision
-        assert_array_almost_equal(expected, result.asnumpy(), decimal=precision)
 
-    @pytest.mark.usefixtures("suppress_divide_numpy_warnings")
-    @pytest.mark.skipif(
-        not has_support_aspect16(), reason="No fp16 support by device"
-    )
-    def test_sin_bool(self):
-        np_array = numpy.arange(2, dtype=numpy.bool_)
-        np_out = numpy.empty(2, dtype=numpy.float16)
+class TestSin:
+    @pytest.mark.parametrize("dtype", get_all_dtypes())
+    def test_sin(self, dtype):
+        np_array, expected = _get_numpy_arrays("sin", dtype, [-5, 5, 10])
 
-        # DPNP
-        dp_array = dpnp.array(np_array, dtype=np_array.dtype)
-        dp_out = dpnp.array(np_out, dtype=np_out.dtype)
+        dp_array = dpnp.array(np_array)
+        out_dtype = _get_output_data_type(dtype)
+        dp_out = dpnp.empty(expected.shape, dtype=out_dtype)
         result = dpnp.sin(dp_array, out=dp_out)
 
-        # original
-        expected = numpy.sin(np_array, out=np_out)
-        assert_allclose(expected, result)
+        assert result is dp_out
+        assert_dtype_allclose(result, expected)
 
     @pytest.mark.parametrize(
         "dtype",
@@ -177,64 +170,17 @@ def test_invalid_shape(self, shape):
 
 
 class TestSinh:
-    @pytest.mark.parametrize(
-        "dtype", get_all_dtypes(no_bool=True, no_complex=True)
-    )
+    @pytest.mark.parametrize("dtype", get_all_dtypes())
     def test_sinh(self, dtype):
-        np_array = numpy.arange(10, dtype=dtype)
-        np_out = numpy.empty(10, dtype=numpy.float64)
-
-        # DPNP
-        dp_out_dtype = dpnp.float32
-        if has_support_aspect64() and dtype != dpnp.float32:
-            dp_out_dtype = dpnp.float64
-
-        dp_out = dpnp.array(np_out, dtype=dp_out_dtype)
-        dp_array = dpnp.array(np_array, dtype=dtype)
-        result = dpnp.sinh(dp_array, out=dp_out)
-
-        # original
-        expected = numpy.sinh(np_array, out=np_out)
-
-        tol = numpy.finfo(dtype=result.dtype).resolution
-        assert_allclose(expected, result.asnumpy(), rtol=tol)
-
-    @pytest.mark.parametrize("dtype", get_complex_dtypes())
-    def test_sinh_complex(self, dtype):
-        np_array = numpy.arange(10, 20, dtype=dtype)
-        np_out = numpy.empty(10, dtype=numpy.complex128)
-
-        # DPNP
-        dp_out_dtype = dpnp.complex64
-        if has_support_aspect64() and dtype != dpnp.complex64:
-            dp_out_dtype = dpnp.complex128
+        np_array, expected = _get_numpy_arrays("sinh", dtype, [-5, 5, 10])
 
-        dp_out = dpnp.array(np_out, dtype=dp_out_dtype)
-        dp_array = dpnp.array(np_array, dtype=dtype)
+        dp_array = dpnp.array(np_array)
+        out_dtype = _get_output_data_type(dtype)
+        dp_out = dpnp.empty(expected.shape, dtype=out_dtype)
         result = dpnp.sinh(dp_array, out=dp_out)
 
-        # original
-        expected = numpy.sinh(np_array, out=np_out)
-
-        tol = numpy.finfo(dtype=result.dtype).resolution
-        assert_allclose(expected, result.asnumpy(), rtol=tol)
-
-    @pytest.mark.usefixtures("suppress_divide_numpy_warnings")
-    @pytest.mark.skipif(
-        not has_support_aspect16(), reason="No fp16 support by device"
-    )
-    def test_sinh_bool(self):
-        np_array = numpy.arange(2, dtype=numpy.bool_)
-        np_out = numpy.empty(2, dtype=numpy.float16)
-
-        # DPNP
-        dp_array = dpnp.array(np_array, dtype=np_array.dtype)
-        dp_out = dpnp.array(np_out, dtype=np_out.dtype)
-        result = dpnp.sinh(dp_array, out=dp_out)
-
-        # original
-        expected = numpy.sinh(np_array, out=np_out)
-        assert_allclose(expected, result)
+        assert result is dp_out
+        assert_dtype_allclose(result, expected)
 
     @pytest.mark.parametrize(
         "dtype",
@@ -260,64 +206,17 @@ def test_invalid_shape(self, shape):
 
 
 class TestCos:
-    @pytest.mark.parametrize(
-        "dtype", get_all_dtypes(no_bool=True, no_complex=True)
-    )
+    @pytest.mark.parametrize("dtype", get_all_dtypes())
     def test_cos(self, dtype):
-        np_array = numpy.arange(10, dtype=dtype)
-        np_out = numpy.empty(10, dtype=numpy.float64)
-
-        # DPNP
-        dp_out_dtype = dpnp.float32
-        if has_support_aspect64() and dtype != dpnp.float32:
-            dp_out_dtype = dpnp.float64
-
-        dp_out = dpnp.array(np_out, dtype=dp_out_dtype)
-        dp_array = dpnp.array(np_array, dtype=dtype)
-        result = dpnp.cos(dp_array, out=dp_out)
-
-        # original
-        expected = numpy.cos(np_array, out=np_out)
-
-        precision = numpy.finfo(dtype=result.dtype).precision
-        assert_array_almost_equal(expected, result.asnumpy(), decimal=precision)
-
-    @pytest.mark.parametrize("dtype", get_complex_dtypes())
-    def test_cos_complex(self, dtype):
-        np_array = numpy.arange(10, 20, dtype=dtype)
-        np_out = numpy.empty(10, dtype=numpy.complex128)
-
-        # DPNP
-        dp_out_dtype = dpnp.complex64
-        if has_support_aspect64() and dtype != dpnp.complex64:
-            dp_out_dtype = dpnp.complex128
-
-        dp_out = dpnp.array(np_out, dtype=dp_out_dtype)
-        dp_array = dpnp.array(np_array, dtype=dtype)
-        result = dpnp.cos(dp_array, out=dp_out)
-
-        # original
-        expected = numpy.cos(np_array, out=np_out)
-
-        precision = numpy.finfo(dtype=result.dtype).precision
-        assert_array_almost_equal(expected, result.asnumpy(), decimal=precision)
-
-    @pytest.mark.usefixtures("suppress_divide_numpy_warnings")
-    @pytest.mark.skipif(
-        not has_support_aspect16(), reason="No fp16 support by device"
-    )
-    def test_cos_bool(self):
-        np_array = numpy.arange(2, dtype=numpy.bool_)
-        np_out = numpy.empty(2, dtype=numpy.float16)
+        np_array, expected = _get_numpy_arrays("cos", dtype, [-5, 5, 10])
 
-        # DPNP
-        dp_array = dpnp.array(np_array, dtype=np_array.dtype)
-        dp_out = dpnp.array(np_out, dtype=np_out.dtype)
+        dp_array = dpnp.array(np_array)
+        out_dtype = _get_output_data_type(dtype)
+        dp_out = dpnp.empty(expected.shape, dtype=out_dtype)
         result = dpnp.cos(dp_array, out=dp_out)
 
-        # original
-        expected = numpy.cos(np_array, out=np_out)
-        assert_allclose(expected, result)
+        assert result is dp_out
+        assert_dtype_allclose(result, expected)
 
     @pytest.mark.parametrize(
         "dtype",
@@ -343,64 +242,17 @@ def test_invalid_shape(self, shape):
 
 
 class TestCosh:
-    @pytest.mark.parametrize(
-        "dtype", get_all_dtypes(no_bool=True, no_complex=True)
-    )
+    @pytest.mark.parametrize("dtype", get_all_dtypes())
     def test_cosh(self, dtype):
-        np_array = numpy.arange(10, dtype=dtype)
-        np_out = numpy.empty(10, dtype=numpy.float64)
-
-        # DPNP
-        dp_out_dtype = dpnp.float32
-        if has_support_aspect64() and dtype != dpnp.float32:
-            dp_out_dtype = dpnp.float64
-
-        dp_out = dpnp.array(np_out, dtype=dp_out_dtype)
-        dp_array = dpnp.array(np_array, dtype=dtype)
-        result = dpnp.cosh(dp_array, out=dp_out)
-
-        # original
-        expected = numpy.cosh(np_array, out=np_out)
-
-        tol = numpy.finfo(dtype=result.dtype).resolution
-        assert_allclose(expected, result.asnumpy(), rtol=tol)
-
-    @pytest.mark.parametrize("dtype", get_complex_dtypes())
-    def test_cosh_complex(self, dtype):
-        np_array = numpy.arange(10, 20, dtype=dtype)
-        np_out = numpy.empty(10, dtype=numpy.complex128)
-
-        # DPNP
-        dp_out_dtype = dpnp.complex64
-        if has_support_aspect64() and dtype != dpnp.complex64:
-            dp_out_dtype = dpnp.complex128
-
-        dp_out = dpnp.array(np_out, dtype=dp_out_dtype)
-        dp_array = dpnp.array(np_array, dtype=dtype)
-        result = dpnp.cosh(dp_array, out=dp_out)
-
-        # original
-        expected = numpy.cosh(np_array, out=np_out)
-
-        tol = numpy.finfo(dtype=result.dtype).resolution
-        assert_allclose(expected, result.asnumpy(), rtol=tol)
+        np_array, expected = _get_numpy_arrays("cosh", dtype, [-5, 5, 10])
 
-    @pytest.mark.usefixtures("suppress_divide_numpy_warnings")
-    @pytest.mark.skipif(
-        not has_support_aspect16(), reason="No fp16 support by device"
-    )
-    def test_cosh_bool(self):
-        np_array = numpy.arange(2, dtype=numpy.bool_)
-        np_out = numpy.empty(2, dtype=numpy.float16)
-
-        # DPNP
-        dp_array = dpnp.array(np_array, dtype=np_array.dtype)
-        dp_out = dpnp.array(np_out, dtype=np_out.dtype)
+        dp_array = dpnp.array(np_array)
+        out_dtype = _get_output_data_type(dtype)
+        dp_out = dpnp.empty(expected.shape, dtype=out_dtype)
         result = dpnp.cosh(dp_array, out=dp_out)
 
-        # original
-        expected = numpy.cosh(np_array, out=np_out)
-        assert_allclose(expected, result)
+        assert result is dp_out
+        assert_dtype_allclose(result, expected)
 
     @pytest.mark.parametrize(
         "dtype",
@@ -425,65 +277,19 @@ def test_invalid_shape(self, shape):
             dpnp.cosh(dp_array, out=dp_out)
 
 
-class TestsLog:
-    @pytest.mark.parametrize(
-        "dtype", get_all_dtypes(no_bool=True, no_complex=True)
-    )
-    def test_log(self, dtype):
-        np_array = numpy.arange(10, dtype=dtype)
-        np_out = numpy.empty(10, dtype=numpy.float64)
-
-        # DPNP
-        dp_out_dtype = dpnp.float32
-        if has_support_aspect64() and dtype != dpnp.float32:
-            dp_out_dtype = dpnp.float64
-
-        dp_out = dpnp.array(np_out, dtype=dp_out_dtype)
-        dp_array = dpnp.array(np_array, dtype=dtype)
-        result = dpnp.log(dp_array, out=dp_out)
-
-        # original
-        expected = numpy.log(np_array, out=np_out)
-
-        precision = numpy.finfo(dtype=result.dtype).precision
-        assert_array_almost_equal(expected, result.asnumpy(), decimal=precision)
-
-    @pytest.mark.parametrize("dtype", get_complex_dtypes())
-    def test_log_complex(self, dtype):
-        np_array = numpy.arange(10, 20, dtype=dtype)
-        np_out = numpy.empty(10, dtype=numpy.complex128)
-
-        # DPNP
-        dp_out_dtype = dpnp.complex64
-        if has_support_aspect64() and dtype != dpnp.complex64:
-            dp_out_dtype = dpnp.complex128
-
-        dp_out = dpnp.array(np_out, dtype=dp_out_dtype)
-        dp_array = dpnp.array(np_array, dtype=dtype)
-        result = dpnp.log(dp_array, out=dp_out)
-
-        # original
-        expected = numpy.log(np_array, out=np_out)
-
-        precision = numpy.finfo(dtype=result.dtype).precision
-        assert_array_almost_equal(expected, result.asnumpy(), decimal=precision)
-
+class TestLog:
     @pytest.mark.usefixtures("suppress_divide_numpy_warnings")
-    @pytest.mark.skipif(
-        not has_support_aspect16(), reason="No fp16 support by device"
-    )
-    def test_log_bool(self):
-        np_array = numpy.arange(2, dtype=numpy.bool_)
-        np_out = numpy.empty(2, dtype=numpy.float16)
+    @pytest.mark.parametrize("dtype", get_all_dtypes())
+    def test_log(self, dtype):
+        np_array, expected = _get_numpy_arrays("log", dtype, [0.1, 10, 10])
 
-        # DPNP
-        dp_array = dpnp.array(np_array, dtype=np_array.dtype)
-        dp_out = dpnp.array(np_out, dtype=np_out.dtype)
+        dp_array = dpnp.array(np_array)
+        out_dtype = _get_output_data_type(dtype)
+        dp_out = dpnp.empty(expected.shape, dtype=out_dtype)
         result = dpnp.log(dp_array, out=dp_out)
 
-        # original
-        expected = numpy.log(np_array, out=np_out)
-        assert_allclose(expected, result)
+        assert result is dp_out
+        assert_dtype_allclose(result, expected)
 
     @pytest.mark.parametrize(
         "dtype",
@@ -509,50 +315,17 @@ def test_invalid_shape(self, shape):
 
 
 class TestExp:
-    @pytest.mark.parametrize(
-        "dtype", get_all_dtypes(no_bool=True, no_complex=True)
-    )
+    @pytest.mark.parametrize("dtype", get_all_dtypes())
     def test_exp(self, dtype):
-        np_array = numpy.arange(10, dtype=dtype)
-        np_out = numpy.empty(10, dtype=numpy.float64)
-
-        # DPNP
-        dp_out_dtype = dpnp.float32
-        if has_support_aspect64() and dtype != dpnp.float32:
-            dp_out_dtype = dpnp.float64
-
-        dp_array = dpnp.array(np_array, dtype=dp_out_dtype)
-        dp_out = dpnp.array(np_out, dtype=dp_out_dtype)
-        result = dpnp.exp(dp_array, out=dp_out)
-
-        # original
-        expected = numpy.exp(np_array, out=np_out)
+        np_array, expected = _get_numpy_arrays("exp", dtype, [-3, 8, 10])
 
-        tol = numpy.finfo(dtype=result.dtype).resolution
-        assert_allclose(expected, result.asnumpy(), rtol=tol)
-
-    @pytest.mark.parametrize("dtype", get_complex_dtypes())
-    def test_exp_complex(self, dtype):
-        x1 = numpy.linspace(0, 8, num=10)
-        x2 = numpy.linspace(0, 6, num=10)
-        Xnp = x1 + 1j * x2
-        np_array = numpy.asarray(Xnp, dtype=dtype)
-        np_out = numpy.empty(10, dtype=numpy.complex128)
-
-        # DPNP
-        dp_out_dtype = dpnp.complex64
-        if has_support_aspect64() and dtype != dpnp.complex64:
-            dp_out_dtype = dpnp.complex128
-
-        dp_array = dpnp.array(np_array, dtype=dp_out_dtype)
-        dp_out = dpnp.array(np_out, dtype=dp_out_dtype)
+        dp_array = dpnp.array(np_array)
+        out_dtype = _get_output_data_type(dtype)
+        dp_out = dpnp.empty(expected.shape, dtype=out_dtype)
         result = dpnp.exp(dp_array, out=dp_out)
 
-        # original
-        expected = numpy.exp(np_array, out=np_out)
-
-        tol = numpy.finfo(dtype=result.dtype).resolution
-        assert_allclose(expected, result.asnumpy(), rtol=tol)
+        assert result is dp_out
+        assert_dtype_allclose(result, expected)
 
     @pytest.mark.parametrize(
         "dtype", get_all_dtypes(no_complex=True, no_none=True)[:-1]
@@ -578,50 +351,17 @@ def test_invalid_shape(self, shape, dtype):
 
 
 class TestExp2:
-    @pytest.mark.parametrize(
-        "dtype", get_all_dtypes(no_bool=True, no_complex=True)
-    )
+    @pytest.mark.parametrize("dtype", get_all_dtypes())
     def test_exp2(self, dtype):
-        np_array = numpy.arange(7, dtype=dtype)
-        np_out = numpy.empty(7, dtype=numpy.float64)
-
-        # DPNP
-        dp_out_dtype = dpnp.float32
-        if has_support_aspect64() and dtype != dpnp.float32:
-            dp_out_dtype = dpnp.float64
+        np_array, expected = _get_numpy_arrays("exp2", dtype, [-3, 8, 10])
 
-        dp_array = dpnp.array(np_array, dtype=dp_out_dtype)
-        dp_out = dpnp.array(np_out, dtype=dp_out_dtype)
+        dp_array = dpnp.array(np_array)
+        out_dtype = _get_output_data_type(dtype)
+        dp_out = dpnp.empty(expected.shape, dtype=out_dtype)
         result = dpnp.exp2(dp_array, out=dp_out)
 
-        # original
-        expected = numpy.exp2(np_array, out=np_out)
-
-        tol = dpnp.finfo(dtype=result.dtype).resolution
-        assert_allclose(expected, result.asnumpy(), rtol=tol)
-
-    @pytest.mark.parametrize("dtype", get_complex_dtypes())
-    def test_exp2_complex(self, dtype):
-        x1 = numpy.linspace(0, 8, num=10)
-        x2 = numpy.linspace(0, 6, num=10)
-        Xnp = x1 + 1j * x2
-        np_array = numpy.asarray(Xnp, dtype=dtype)
-        np_out = numpy.empty(10, dtype=numpy.complex128)
-
-        # DPNP
-        dp_out_dtype = dpnp.complex64
-        if has_support_aspect64() and dtype != dpnp.complex64:
-            dp_out_dtype = dpnp.complex128
-
-        dp_array = dpnp.array(np_array, dtype=dp_out_dtype)
-        dp_out = dpnp.array(np_out, dtype=dp_out_dtype)
-        result = dpnp.exp2(dp_array, out=dp_out)
-
-        # original
-        expected = numpy.exp2(np_array, out=np_out)
-
-        tol = dpnp.finfo(dtype=result.dtype).resolution
-        assert_allclose(expected, result.asnumpy(), rtol=tol)
+        assert result is dp_out
+        assert_dtype_allclose(result, expected)
 
     @pytest.mark.parametrize(
         "dtype", get_all_dtypes(no_complex=True, no_none=True)[:-1]
@@ -647,27 +387,17 @@ def test_invalid_shape(self, shape, dtype):
 
 
 class TestCbrt:
-    @pytest.mark.parametrize(
-        "dtype", get_all_dtypes(no_bool=True, no_complex=True)
-    )
+    @pytest.mark.parametrize("dtype", get_all_dtypes(no_complex=True))
     def test_cbrt(self, dtype):
-        np_array = numpy.arange(7, dtype=dtype)
-        np_out = numpy.empty(7, dtype=numpy.float64)
-
-        # DPNP
-        dp_out_dtype = dpnp.float32
-        if has_support_aspect64() and dtype != dpnp.float32:
-            dp_out_dtype = dpnp.float64
+        np_array, expected = _get_numpy_arrays("cbrt", dtype, [-5, 5, 10])
 
-        dp_array = dpnp.array(np_array, dtype=dp_out_dtype)
-        dp_out = dpnp.array(np_out, dtype=dp_out_dtype)
+        dp_array = dpnp.array(np_array)
+        out_dtype = _get_output_data_type(dtype)
+        dp_out = dpnp.empty(expected.shape, dtype=out_dtype)
         result = dpnp.cbrt(dp_array, out=dp_out)
 
-        # original
-        expected = numpy.cbrt(np_array, out=np_out)
-
-        tol = dpnp.finfo(dtype=result.dtype).resolution
-        assert_allclose(expected, result.asnumpy(), rtol=tol)
+        assert result is dp_out
+        assert_dtype_allclose(result, expected)
 
     @pytest.mark.parametrize(
         "dtype", get_all_dtypes(no_complex=True, no_none=True)[:-1]
@@ -693,27 +423,19 @@ def test_invalid_shape(self, shape, dtype):
 
 
 class TestRsqrt:
-    @pytest.mark.parametrize(
-        "dtype", get_all_dtypes(no_bool=True, no_complex=True)
-    )
+    @pytest.mark.usefixtures("suppress_divide_numpy_warnings")
+    @pytest.mark.parametrize("dtype", get_all_dtypes(no_complex=True))
     def test_rsqrt(self, dtype):
-        np_array = numpy.arange(1, 10, dtype=dtype)
-        np_out = numpy.empty(9, dtype=numpy.float64)
-
-        # DPNP
-        dp_out_dtype = dpnp.float32
-        if has_support_aspect64() and dtype != dpnp.float32:
-            dp_out_dtype = dpnp.float64
+        np_array, expected = _get_numpy_arrays("sqrt", dtype, [0, 10, 10])
+        expected = numpy.reciprocal(expected)
 
-        dp_array = dpnp.array(np_array, dtype=dp_out_dtype)
-        dp_out = dpnp.array(np_out, dtype=dp_out_dtype)
+        dp_array = dpnp.array(np_array)
+        out_dtype = _get_output_data_type(dtype)
+        dp_out = dpnp.empty(expected.shape, dtype=out_dtype)
         result = dpnp.rsqrt(dp_array, out=dp_out)
 
-        # original
-        expected = numpy.reciprocal(numpy.sqrt(np_array), out=np_out)
-
-        tol = dpnp.finfo(dtype=result.dtype).resolution
-        assert_allclose(expected, result.asnumpy(), rtol=tol)
+        assert result is dp_out
+        assert_dtype_allclose(result, expected)
 
     @pytest.mark.parametrize(
         "dtype", get_all_dtypes(no_complex=True, no_none=True)[:-1]
@@ -739,23 +461,17 @@ def test_invalid_shape(self, shape, dtype):
 
 
 class TestArccos:
-    @pytest.mark.parametrize("dtype", get_float_dtypes())
-    @pytest.mark.usefixtures("suppress_invalid_numpy_warnings")
+    @pytest.mark.parametrize("dtype", get_all_dtypes())
     def test_arccos(self, dtype):
-        array_data = numpy.arange(-9, 10, 2) / 10
-        out = numpy.empty(10, dtype=dtype)
+        np_array, expected = _get_numpy_arrays("arccos", dtype, [-1, 1, 10])
 
-        # DPNP
-        dp_array = dpnp.array(array_data, dtype=dtype)
-        dp_out = dpnp.array(out, dtype=dtype)
+        dp_array = dpnp.array(np_array)
+        out_dtype = _get_output_data_type(dtype)
+        dp_out = dpnp.empty(expected.shape, dtype=out_dtype)
         result = dpnp.arccos(dp_array, out=dp_out)
 
-        # original
-        np_array = numpy.array(array_data, dtype=dtype)
-        expected = numpy.arccos(np_array, out=out)
-
-        tol = numpy.finfo(dtype=result.dtype).resolution
-        assert_allclose(expected, result.asnumpy(), rtol=tol)
+        assert result is dp_out
+        assert_dtype_allclose(result, expected)
 
     @pytest.mark.parametrize(
         "dtype", get_all_dtypes(no_complex=True, no_none=True)[:-1]
@@ -781,23 +497,18 @@ def test_invalid_shape(self, shape, dtype):
 
 
 class TestArccosh:
-    @pytest.mark.parametrize("dtype", get_float_dtypes())
     @pytest.mark.usefixtures("suppress_invalid_numpy_warnings")
+    @pytest.mark.parametrize("dtype", get_all_dtypes())
     def test_arccosh(self, dtype):
-        array_data = numpy.arange(2, 12)
-        out = numpy.empty(10, dtype=dtype)
+        np_array, expected = _get_numpy_arrays("arccosh", dtype, [1, 10, 10])
 
-        # DPNP
-        dp_array = dpnp.array(array_data, dtype=dtype)
-        dp_out = dpnp.array(out, dtype=dtype)
+        dp_array = dpnp.array(np_array)
+        out_dtype = _get_output_data_type(dtype)
+        dp_out = dpnp.empty(expected.shape, dtype=out_dtype)
         result = dpnp.arccosh(dp_array, out=dp_out)
 
-        # original
-        np_array = numpy.array(array_data, dtype=dtype)
-        expected = numpy.arccosh(np_array, out=out)
-
-        tol = numpy.finfo(dtype=result.dtype).resolution
-        assert_allclose(expected, result.asnumpy(), rtol=tol)
+        assert result is dp_out
+        assert_dtype_allclose(result, expected)
 
     @pytest.mark.parametrize(
         "dtype", get_all_dtypes(no_complex=True, no_none=True)[:-1]
@@ -823,23 +534,17 @@ def test_invalid_shape(self, shape, dtype):
 
 
 class TestArcsin:
-    @pytest.mark.parametrize("dtype", get_float_dtypes())
-    @pytest.mark.usefixtures("suppress_invalid_numpy_warnings")
+    @pytest.mark.parametrize("dtype", get_all_dtypes())
     def test_arcsin(self, dtype):
-        array_data = numpy.arange(-9, 10, 2) / 10
-        out = numpy.empty(10, dtype=dtype)
+        np_array, expected = _get_numpy_arrays("arcsin", dtype, [-1, 1, 10])
 
-        # DPNP
-        dp_array = dpnp.array(array_data, dtype=dtype)
-        dp_out = dpnp.array(out, dtype=dtype)
+        dp_array = dpnp.array(np_array)
+        out_dtype = _get_output_data_type(dtype)
+        dp_out = dpnp.empty(expected.shape, dtype=out_dtype)
         result = dpnp.arcsin(dp_array, out=dp_out)
 
-        # original
-        np_array = numpy.array(array_data, dtype=dtype)
-        expected = numpy.arcsin(np_array, out=out)
-
-        tol = numpy.finfo(dtype=result.dtype).resolution
-        assert_allclose(expected, result.asnumpy(), rtol=tol)
+        assert result is dp_out
+        assert_dtype_allclose(result, expected)
 
     @pytest.mark.parametrize(
         "dtype", get_all_dtypes(no_complex=True, no_none=True)[:-1]
@@ -865,23 +570,17 @@ def test_invalid_shape(self, shape, dtype):
 
 
 class TestArcsinh:
-    @pytest.mark.parametrize("dtype", get_float_dtypes())
-    @pytest.mark.usefixtures("suppress_invalid_numpy_warnings")
+    @pytest.mark.parametrize("dtype", get_all_dtypes())
     def test_arcsinh(self, dtype):
-        array_data = numpy.arange(10)
-        out = numpy.empty(10, dtype=dtype)
+        np_array, expected = _get_numpy_arrays("arcsinh", dtype, [-5, 5, 10])
 
-        # DPNP
-        dp_array = dpnp.array(array_data, dtype=dtype)
-        dp_out = dpnp.array(out, dtype=dtype)
+        dp_array = dpnp.array(np_array)
+        out_dtype = _get_output_data_type(dtype)
+        dp_out = dpnp.empty(expected.shape, dtype=out_dtype)
         result = dpnp.arcsinh(dp_array, out=dp_out)
 
-        # original
-        np_array = numpy.array(array_data, dtype=dtype)
-        expected = numpy.arcsinh(np_array, out=out)
-
-        tol = numpy.finfo(dtype=result.dtype).resolution
-        assert_allclose(expected, result.asnumpy(), rtol=tol)
+        assert result is dp_out
+        assert_dtype_allclose(result, expected)
 
     @pytest.mark.parametrize(
         "dtype", get_all_dtypes(no_complex=True, no_none=True)[:-1]
@@ -907,22 +606,17 @@ def test_invalid_shape(self, shape, dtype):
 
 
 class TestArctan:
-    @pytest.mark.parametrize("dtype", get_float_dtypes())
+    @pytest.mark.parametrize("dtype", get_all_dtypes())
     def test_arctan(self, dtype):
-        array_data = numpy.arange(10)
-        out = numpy.empty(10, dtype=dtype)
+        np_array, expected = _get_numpy_arrays("arctan", dtype, [-5, 5, 10])
 
-        # DPNP
-        dp_array = dpnp.array(array_data, dtype=dtype)
-        dp_out = dpnp.array(out, dtype=dtype)
+        dp_array = dpnp.array(np_array)
+        out_dtype = _get_output_data_type(dtype)
+        dp_out = dpnp.empty(expected.shape, dtype=out_dtype)
         result = dpnp.arctan(dp_array, out=dp_out)
 
-        # original
-        np_array = numpy.array(array_data, dtype=dtype)
-        expected = numpy.arctan(np_array, out=out)
-
-        tol = numpy.finfo(dtype).resolution
-        assert_allclose(expected, result, tol)
+        assert result is dp_out
+        assert_dtype_allclose(result, expected)
 
     @pytest.mark.parametrize(
         "dtype", get_all_dtypes(no_complex=True, no_none=True)[:-1]
@@ -948,22 +642,18 @@ def test_invalid_shape(self, shape, dtype):
 
 
 class TestArctanh:
-    @pytest.mark.parametrize("dtype", get_float_dtypes())
+    @pytest.mark.usefixtures("suppress_divide_numpy_warnings")
+    @pytest.mark.parametrize("dtype", get_all_dtypes())
     def test_arctanh(self, dtype):
-        array_data = numpy.arange(-9, 10, 2) / 10
-        out = numpy.empty(10, dtype=dtype)
+        np_array, expected = _get_numpy_arrays("arctanh", dtype, [-1, 1, 10])
 
-        # DPNP
-        dp_array = dpnp.array(array_data, dtype=dtype)
-        dp_out = dpnp.array(out, dtype=dtype)
+        dp_array = dpnp.array(np_array)
+        out_dtype = _get_output_data_type(dtype)
+        dp_out = dpnp.empty(expected.shape, dtype=out_dtype)
         result = dpnp.arctanh(dp_array, out=dp_out)
 
-        # original
-        np_array = numpy.array(array_data, dtype=dtype)
-        expected = numpy.arctanh(np_array, out=out)
-
-        tol = numpy.finfo(dtype).resolution
-        assert_allclose(expected, result, tol)
+        assert result is dp_out
+        assert_dtype_allclose(result, expected)
 
     @pytest.mark.parametrize(
         "dtype", get_all_dtypes(no_complex=True, no_none=True)[:-1]
@@ -989,22 +679,17 @@ def test_invalid_shape(self, shape, dtype):
 
 
 class TestTan:
-    @pytest.mark.parametrize("dtype", get_float_dtypes())
+    @pytest.mark.parametrize("dtype", get_all_dtypes())
     def test_tan(self, dtype):
-        array_data = numpy.arange(10)
-        out = numpy.empty(10, dtype=dtype)
+        np_array, expected = _get_numpy_arrays("tan", dtype, [-5, 5, 10])
 
-        # DPNP
-        dp_array = dpnp.array(array_data, dtype=dtype)
-        dp_out = dpnp.array(out, dtype=dtype)
+        dp_array = dpnp.array(np_array)
+        out_dtype = _get_output_data_type(dtype)
+        dp_out = dpnp.empty(expected.shape, dtype=out_dtype)
         result = dpnp.tan(dp_array, out=dp_out)
 
-        # original
-        np_array = numpy.array(array_data, dtype=dtype)
-        expected = numpy.tan(np_array, out=out)
-
-        tol = numpy.finfo(dtype).resolution
-        assert_allclose(expected, result, rtol=tol)
+        assert result is dp_out
+        assert_dtype_allclose(result, expected)
 
     @pytest.mark.parametrize(
         "dtype", get_all_dtypes(no_complex=True, no_none=True)[:-1]
@@ -1030,41 +715,20 @@ def test_invalid_shape(self, shape, dtype):
 
 
 class TestArctan2:
-    @pytest.mark.parametrize("dtype", get_float_dtypes())
+    @pytest.mark.parametrize("dtype", get_all_dtypes(no_complex=True))
     def test_arctan2(self, dtype):
-        array_data = numpy.arange(10)
-        out = numpy.empty(10, dtype=dtype)
-
-        # DPNP
-        dp_array = dpnp.array(array_data, dtype=dtype)
-        dp_out = dpnp.array(out, dtype=dtype)
-        result = dpnp.arctan2(dp_array, dp_array, out=dp_out)
-
-        # original
-        np_array = numpy.array(array_data, dtype=dtype)
-        expected = numpy.arctan2(np_array, np_array, out=out)
+        np_array1, _ = _get_numpy_arrays("array", dtype, [-5, 5, 10])
+        np_array2, _ = _get_numpy_arrays("array", dtype, [-5, 5, 10])
+        expected = numpy.arctan2(np_array1, np_array2)
 
-        assert_allclose(expected, result)
-
-    @pytest.mark.parametrize(
-        "dtype", get_all_dtypes(no_bool=True, no_complex=True, no_none=True)
-    )
-    def test_out_dtypes(self, dtype):
-        if has_support_aspect64() and dtype != numpy.float32:
-            dtype_out = numpy.float64
-        else:
-            dtype_out = numpy.float32
-        size = 2 if dtype == dpnp.bool else 10
+        dp_array1 = dpnp.array(np_array1)
+        dp_array2 = dpnp.array(np_array2)
+        out_dtype = _get_output_data_type(dtype)
+        dp_out = dpnp.empty(expected.shape, dtype=out_dtype)
+        result = dpnp.arctan2(dp_array1, dp_array2, out=dp_out)
 
-        np_array = numpy.arange(size, dtype=dtype)
-        np_out = numpy.empty(size, dtype=dtype_out)
-        expected = numpy.arctan2(np_array, np_array, out=np_out)
-
-        dp_array = dpnp.arange(size, dtype=dtype)
-        dp_out = dpnp.empty(size, dtype=dtype_out)
-        result = dpnp.arctan2(dp_array, dp_array, out=dp_out)
-
-        assert_allclose(expected, result)
+        assert result is dp_out
+        assert_dtype_allclose(result, expected)
 
     @pytest.mark.parametrize("dtype", get_float_dtypes())
     @pytest.mark.parametrize(
@@ -1079,41 +743,20 @@ def test_invalid_shape(self, shape, dtype):
 
 
 class TestCopySign:
-    @pytest.mark.parametrize("dtype", get_float_dtypes())
+    @pytest.mark.parametrize("dtype", get_all_dtypes(no_complex=True))
     def test_copysign(self, dtype):
-        array_data = numpy.arange(10)
-        out = numpy.empty(10, dtype=dtype)
+        np_array1, _ = _get_numpy_arrays("array", dtype, [1, 10, 10])
+        np_array2, _ = _get_numpy_arrays("array", dtype, [-10, -1, 10])
+        expected = numpy.copysign(np_array1, np_array2)
 
-        # DPNP
-        dp_array = dpnp.array(array_data, dtype=dtype)
-        dp_out = dpnp.array(out, dtype=dtype)
-        result = dpnp.copysign(dp_array, -dp_array, out=dp_out)
+        dp_array1 = dpnp.array(np_array1)
+        dp_array2 = dpnp.array(np_array2)
+        out_dtype = _get_output_data_type(dtype)
+        dp_out = dpnp.empty(expected.shape, dtype=out_dtype)
+        result = dpnp.copysign(dp_array1, dp_array2, out=dp_out)
 
-        # original
-        np_array = numpy.array(array_data, dtype=dtype)
-        expected = numpy.copysign(np_array, -np_array, out=out)
-
-        assert_allclose(expected, result)
-
-    @pytest.mark.parametrize(
-        "dtype", get_all_dtypes(no_bool=True, no_complex=True, no_none=True)
-    )
-    def test_out_dtypes(self, dtype):
-        if has_support_aspect64() and dtype != numpy.float32:
-            dtype_out = numpy.float64
-        else:
-            dtype_out = numpy.float32
-        size = 2 if dtype == dpnp.bool else 10
-
-        np_array = numpy.arange(size, dtype=dtype)
-        np_out = numpy.empty(size, dtype=dtype_out)
-        expected = numpy.copysign(np_array, -np_array, out=np_out)
-
-        dp_array = dpnp.arange(size, dtype=dtype)
-        dp_out = dpnp.empty(size, dtype=dtype_out)
-        result = dpnp.copysign(dp_array, -dp_array, out=dp_out)
-
-        assert_allclose(expected, result)
+        assert result is dp_out
+        assert_dtype_allclose(result, expected)
 
     @pytest.mark.parametrize("dtype", get_float_dtypes())
     @pytest.mark.parametrize(
@@ -1128,60 +771,17 @@ def test_invalid_shape(self, shape, dtype):
 
 
 class TestSqrt:
-    @pytest.mark.parametrize(
-        "dtype", get_all_dtypes(no_bool=True, no_complex=True)
-    )
-    def test_sqrt_int_float(self, dtype):
-        np_array = numpy.arange(10, dtype=dtype)
-        np_out = numpy.empty(10, dtype=numpy.float64)
-
-        # DPNP
-        dp_out_dtype = dpnp.float32
-        if has_support_aspect64() and dtype != dpnp.float32:
-            dp_out_dtype = dpnp.float64
-
-        dp_out = dpnp.array(np_out, dtype=dp_out_dtype)
-        dp_array = dpnp.array(np_array, dtype=dtype)
-        result = dpnp.sqrt(dp_array, out=dp_out)
-
-        # original
-        expected = numpy.sqrt(np_array, out=np_out)
-        assert_allclose(expected, result)
-
-    @pytest.mark.parametrize("dtype", get_complex_dtypes())
-    def test_sqrt_complex(self, dtype):
-        np_array = numpy.arange(10, 20, dtype=dtype)
-        np_out = numpy.empty(10, dtype=numpy.complex128)
-
-        # DPNP
-        dp_out_dtype = dpnp.complex64
-        if has_support_aspect64() and dtype != dpnp.complex64:
-            dp_out_dtype = dpnp.complex128
-
-        dp_out = dpnp.array(np_out, dtype=dp_out_dtype)
-        dp_array = dpnp.array(np_array, dtype=dtype)
-        result = dpnp.sqrt(dp_array, out=dp_out)
+    @pytest.mark.parametrize("dtype", get_all_dtypes())
+    def test_sqrt(self, dtype):
+        np_array, expected = _get_numpy_arrays("sqrt", dtype, [0, 10, 10])
 
-        # original
-        expected = numpy.sqrt(np_array, out=np_out)
-        assert_allclose(expected, result)
-
-    @pytest.mark.usefixtures("suppress_divide_numpy_warnings")
-    @pytest.mark.skipif(
-        not has_support_aspect16(), reason="No fp16 support by device"
-    )
-    def test_sqrt_bool(self):
-        np_array = numpy.arange(2, dtype=numpy.bool_)
-        np_out = numpy.empty(2, dtype=numpy.float16)
-
-        # DPNP
-        dp_array = dpnp.array(np_array, dtype=np_array.dtype)
-        dp_out = dpnp.array(np_out, dtype=np_out.dtype)
+        dp_array = dpnp.array(np_array)
+        out_dtype = _get_output_data_type(dtype)
+        dp_out = dpnp.empty(expected.shape, dtype=out_dtype)
         result = dpnp.sqrt(dp_array, out=dp_out)
 
-        # original
-        expected = numpy.sqrt(np_array, out=np_out)
-        assert_allclose(expected, result)
+        assert result is dp_out
+        assert_dtype_allclose(result, expected)
 
     @pytest.mark.parametrize(
         "dtype", [numpy.int64, numpy.int32], ids=["numpy.int64", "numpy.int32"]
@@ -1216,34 +816,17 @@ def test_invalid_out(self, out):
 
 
 class TestSquare:
-    @pytest.mark.parametrize(
-        "dtype", get_all_dtypes(no_bool=True, no_none=True)
-    )
+    @pytest.mark.parametrize("dtype", get_all_dtypes())
     def test_square(self, dtype):
-        np_array = numpy.arange(10, dtype=dtype)
-        np_out = numpy.empty(10, dtype=dtype)
-
-        # DPNP
-        dp_out = dpnp.array(np_out, dtype=dtype)
-        dp_array = dpnp.array(np_array, dtype=dtype)
-        result = dpnp.square(dp_array, out=dp_out)
-
-        # original
-        expected = numpy.square(np_array, out=np_out)
-        assert_allclose(expected, result)
-
-    def test_square_bool(self):
-        np_array = numpy.arange(2, dtype=numpy.bool_)
-        np_out = numpy.empty(2, dtype=numpy.int8)
+        np_array, expected = _get_numpy_arrays("square", dtype, [-5, 5, 10])
 
-        # DPNP
-        dp_array = dpnp.array(np_array, dtype=np_array.dtype)
-        dp_out = dpnp.array(np_out, dtype=np_out.dtype)
+        dp_array = dpnp.array(np_array)
+        out_dtype = numpy.int8 if dtype == numpy.bool_ else dtype
+        dp_out = dpnp.empty(expected.shape, dtype=out_dtype)
         result = dpnp.square(dp_array, out=dp_out)
 
-        # original
-        expected = numpy.square(np_array, out=np_out)
-        assert_allclose(expected, result)
+        assert result is dp_out
+        assert_dtype_allclose(result, expected)
 
     @pytest.mark.parametrize(
         "dtype", get_all_dtypes(no_bool=True, no_none=True)

From b6f4b4b51ba03cbb50e6979e3e1e846847ddab25 Mon Sep 17 00:00:00 2001
From: Vahid Tavanashad <vahid.tavanashad@intel.com>
Date: Mon, 15 Jan 2024 10:43:36 -0600
Subject: [PATCH 2/3] improve test coverage

---
 dpnp/dpnp_iface_trigonometric.py |   2 +-
 tests/test_absolute.py           |  18 +-
 tests/test_bitwise.py            |  14 +
 tests/test_logic.py              |  21 +-
 tests/test_mathematical.py       |  68 ++-
 tests/test_umath.py              | 690 +++++++------------------------
 6 files changed, 255 insertions(+), 558 deletions(-)

diff --git a/dpnp/dpnp_iface_trigonometric.py b/dpnp/dpnp_iface_trigonometric.py
index f21f67f43689..c293707e2b9f 100644
--- a/dpnp/dpnp_iface_trigonometric.py
+++ b/dpnp/dpnp_iface_trigonometric.py
@@ -1305,7 +1305,7 @@ def logaddexp(
     Parameters `where`, `dtype` and `subok` are supported with their default values.
     Keyword arguments `kwargs` are currently unsupported.
     Otherwise the function will be executed sequentially on CPU.
-    Input array data types are limited by supported DPNP :ref:`Data types`.
+    Input array data types are limited by real-valued data types.
 
     See Also
     --------
diff --git a/tests/test_absolute.py b/tests/test_absolute.py
index aac8a71ca585..1c6a42e98c64 100644
--- a/tests/test_absolute.py
+++ b/tests/test_absolute.py
@@ -1,10 +1,15 @@
 import numpy
 import pytest
-from numpy.testing import assert_array_equal, assert_equal
+from numpy.testing import assert_equal
 
 import dpnp
 
-from .helper import get_all_dtypes, get_complex_dtypes, get_float_complex_dtypes
+from .helper import (
+    assert_dtype_allclose,
+    get_all_dtypes,
+    get_complex_dtypes,
+    get_float_complex_dtypes,
+)
 
 
 @pytest.mark.parametrize("func", ["abs", "absolute"])
@@ -15,8 +20,13 @@ def test_abs(func, dtype):
 
     result = getattr(dpnp, func)(ia)
     expected = getattr(numpy, func)(a)
-    assert_array_equal(expected, result)
-    assert_equal(result.dtype, expected.dtype)
+    assert_dtype_allclose(result, expected)
+
+    # out keyword
+    dp_out = dpnp.empty(expected.shape, dtype=expected.dtype)
+    result = getattr(dpnp, func)(ia, out=dp_out)
+    assert result is dp_out
+    assert_dtype_allclose(result, expected)
 
 
 @pytest.mark.parametrize("stride", [-4, -2, -1, 1, 2, 4])
diff --git a/tests/test_bitwise.py b/tests/test_bitwise.py
index f8484eaecb5b..e3393e43beeb 100644
--- a/tests/test_bitwise.py
+++ b/tests/test_bitwise.py
@@ -4,6 +4,8 @@
 
 import dpnp as inp
 
+from .helper import assert_dtype_allclose, get_integer_dtypes
+
 
 @pytest.mark.parametrize(
     "lhs",
@@ -134,3 +136,15 @@ def test_right_shift(self, lhs, rhs, dtype):
             dp_a >>= dp_b
             np_a >>= np_b
             assert_array_equal(dp_a, np_a)
+
+
+@pytest.mark.parametrize("dtype", get_integer_dtypes())
+def test_invert_out(dtype):
+    np_a = numpy.arange(-5, 5, dtype=dtype)
+    dp_a = inp.array(np_a)
+
+    expected = numpy.invert(np_a)
+    dp_out = inp.empty(expected.shape, dtype=expected.dtype)
+    result = inp.invert(dp_a, out=dp_out)
+    assert result is dp_out
+    assert_dtype_allclose(result, expected)
diff --git a/tests/test_logic.py b/tests/test_logic.py
index b9d2a9b4303a..1e110b4c717b 100644
--- a/tests/test_logic.py
+++ b/tests/test_logic.py
@@ -250,6 +250,11 @@ def test_logical_not(dtype):
     dpnp_res = dpnp.logical_not(a)
     assert_equal(dpnp_res, np_res)
 
+    dp_out = dpnp.empty(np_res.shape, dtype=dpnp.bool)
+    dpnp_res = dpnp.logical_not(a, out=dp_out)
+    assert dpnp_res is dp_out
+    assert_equal(dpnp_res, np_res)
+
 
 @pytest.mark.parametrize(
     "op",
@@ -316,6 +321,13 @@ def test_elemwise_comparison(op, x1, x2, dtype):
     dpnp_res = getattr(dpnp, op)(dp_x1[::-1], dp_x2)
     assert_equal(dpnp_res, np_res)
 
+    # out keyword
+    np_res = getattr(numpy, op)(np_x1, np_x2)
+    dp_out = dpnp.empty(np_res.shape, dtype=dpnp.bool)
+    dpnp_res = getattr(dpnp, op)(dp_x1, dp_x2, out=dp_out)
+    assert dp_out is dpnp_res
+    assert_equal(dpnp_res, np_res)
+
 
 @pytest.mark.parametrize(
     "op",
@@ -374,6 +386,11 @@ def test_comparison_no_broadcast_with_shapes(op, sh1, sh2):
 @pytest.mark.parametrize("dtype", get_float_complex_dtypes())
 def test_finite(op, data, dtype):
     x = dpnp.asarray(data, dtype=dtype)
-    np_res = getattr(dpnp, op)(x)
-    dpnp_res = getattr(numpy, op)(x.asnumpy())
+    np_res = getattr(numpy, op)(x.asnumpy())
+    dpnp_res = getattr(dpnp, op)(x)
+    assert_equal(dpnp_res, np_res)
+
+    dp_out = dpnp.empty(np_res.shape, dtype=dpnp.bool)
+    dpnp_res = getattr(dpnp, op)(x, out=dp_out)
+    assert dp_out is dpnp_res
     assert_equal(dpnp_res, np_res)
diff --git a/tests/test_mathematical.py b/tests/test_mathematical.py
index 6c95093a01b9..86c31dc25ae3 100644
--- a/tests/test_mathematical.py
+++ b/tests/test_mathematical.py
@@ -660,6 +660,17 @@ def test_negative(data, dtype):
     expected = numpy.negative(np_a)
     assert_allclose(result, expected)
 
+    result = -dpnp_a
+    expected = -np_a
+    assert_allclose(result, expected)
+
+    # out keyword
+    if dtype is not None:
+        dp_out = dpnp.empty(expected.shape, dtype=dtype)
+        result = dpnp.negative(dpnp_a, out=dp_out)
+        assert result is dp_out
+        assert_allclose(result, expected)
+
 
 def test_negative_boolean():
     dpnp_a = dpnp.array([True, False])
@@ -686,6 +697,13 @@ def test_positive(data, dtype):
     expected = +np_a
     assert_allclose(result, expected)
 
+    # out keyword
+    if dtype is not None:
+        dp_out = dpnp.empty(expected.shape, dtype=dtype)
+        result = dpnp.positive(dpnp_a, out=dp_out)
+        assert result is dp_out
+        assert_allclose(result, expected)
+
 
 def test_positive_boolean():
     dpnp_a = dpnp.array([True, False])
@@ -811,7 +829,14 @@ def test_sign(data, dtype):
 
     result = dpnp.sign(dpnp_a)
     expected = numpy.sign(np_a)
-    assert_allclose(result, expected)
+    assert_dtype_allclose(result, expected)
+
+    # out keyword
+    if dtype is not None:
+        dp_out = dpnp.empty(expected.shape, dtype=expected.dtype)
+        result = dpnp.sign(dpnp_a, out=dp_out)
+        assert dp_out is result
+        assert_dtype_allclose(result, expected)
 
 
 def test_sign_boolean():
@@ -833,9 +858,20 @@ def test_signbit(data, dtype):
 
     result = dpnp.signbit(dpnp_a)
     expected = numpy.signbit(np_a)
-    assert_allclose(result, expected)
+    assert_dtype_allclose(result, expected)
+
+    # out keyword
+    dp_out = dpnp.empty(expected.shape, dtype=expected.dtype)
+    result = dpnp.signbit(dpnp_a, out=dp_out)
+    assert dp_out is result
+    assert_dtype_allclose(result, expected)
 
 
+@pytest.mark.parametrize(
+    "func",
+    ["real", "imag", "conj"],
+    ids=["real", "imag", "conj"],
+)
 @pytest.mark.parametrize(
     "data",
     [complex(-1, -4), complex(-1, 2), complex(3, -7), complex(4, 12)],
@@ -847,17 +883,20 @@ def test_signbit(data, dtype):
     ],
 )
 @pytest.mark.parametrize("dtype", get_complex_dtypes())
-def test_real_imag(data, dtype):
+def test_complex_funcs(func, data, dtype):
     np_a = numpy.array(data, dtype=dtype)
     dpnp_a = dpnp.array(data, dtype=dtype)
 
-    result = dpnp.real(dpnp_a)
-    expected = numpy.real(np_a)
-    assert_allclose(result, expected)
+    result = getattr(dpnp, func)(dpnp_a)
+    expected = getattr(numpy, func)(np_a)
+    assert_dtype_allclose(result, expected)
 
-    result = dpnp.imag(dpnp_a)
-    expected = numpy.imag(np_a)
-    assert_allclose(result, expected)
+    # out keyword
+    if func == "conj":
+        dp_out = dpnp.empty(expected.shape, dtype=expected.dtype)
+        result = getattr(dpnp, func)(dpnp_a, out=dp_out)
+        assert dp_out is result
+        assert_dtype_allclose(result, expected)
 
 
 @pytest.mark.parametrize("dtype", get_complex_dtypes())
@@ -875,9 +914,16 @@ def test_projection_infinity(dtype):
         complex(dpnp.inf, 0.0),
     ]
 
-    result = dpnp.proj(dpnp.array(X, dtype=dtype))
+    a = dpnp.array(X, dtype=dtype)
+    result = dpnp.proj(a)
     expected = dpnp.array(Y, dtype=dtype)
-    assert_allclose(result, expected)
+    assert_dtype_allclose(result, expected)
+
+    # out keyword
+    dp_out = dpnp.empty(expected.shape, dtype=expected.dtype)
+    result = dpnp.proj(a, out=dp_out)
+    assert dp_out is result
+    assert_dtype_allclose(result, expected)
 
 
 @pytest.mark.parametrize("dtype", get_all_dtypes())
diff --git a/tests/test_umath.py b/tests/test_umath.py
index 05c75b51a6ae..d9bbacdf4ef3 100644
--- a/tests/test_umath.py
+++ b/tests/test_umath.py
@@ -133,257 +133,100 @@ def _get_output_data_type(dtype):
     return out_dtype
 
 
-class TestSin:
+class TestUmath:
+    @pytest.fixture(
+        params=[
+            {"func_name": "arccos", "input_values": [-1, 1, 10]},
+            {"func_name": "arccosh", "input_values": [1, 10, 10]},
+            {"func_name": "arcsin", "input_values": [-1, 1, 10]},
+            {"func_name": "arcsinh", "input_values": [-5, 5, 10]},
+            {"func_name": "arctan", "input_values": [-5, 5, 10]},
+            {"func_name": "arctanh", "input_values": [-1, 1, 10]},
+            {"func_name": "cos", "input_values": [-5, 5, 10]},
+            {"func_name": "cosh", "input_values": [-5, 5, 10]},
+            {"func_name": "exp", "input_values": [-3, 8, 10]},
+            {"func_name": "exp2", "input_values": [-5, 5, 10]},
+            {"func_name": "expm1", "input_values": [-5, 5, 10]},
+            {"func_name": "log", "input_values": [0, 10, 10]},
+            {"func_name": "log10", "input_values": [0, 10, 10]},
+            {"func_name": "log2", "input_values": [0, 10, 10]},
+            {"func_name": "log1p", "input_values": [0, 10, 10]},
+            {"func_name": "sin", "input_values": [-5, 5, 10]},
+            {"func_name": "sinh", "input_values": [-5, 5, 10]},
+            {"func_name": "sqrt", "input_values": [0, 10, 10]},
+            {"func_name": "tan", "input_values": [-1.5, 1.5, 10]},
+            {"func_name": "tanh", "input_values": [-5, 5, 10]},
+        ],
+        ids=[
+            "arccos",
+            "arccosh",
+            "arcsin",
+            "arcsinh",
+            "arctan",
+            "arctanh",
+            "cos",
+            "cosh",
+            "exp",
+            "exp2",
+            "expm1",
+            "log",
+            "log10",
+            "log2",
+            "log1p",
+            "sin",
+            "sinh",
+            "sqrt",
+            "tan",
+            "tnah",
+        ],
+    )
+    def func_params(self, request):
+        return request.param
+
+    @pytest.mark.usefixtures("suppress_divide_invalid_numpy_warnings")
     @pytest.mark.parametrize("dtype", get_all_dtypes())
-    def test_sin(self, dtype):
-        np_array, expected = _get_numpy_arrays("sin", dtype, [-5, 5, 10])
+    def test_out(self, func_params, dtype):
+        func_name = func_params["func_name"]
+        input_values = func_params["input_values"]
+        np_array, expected = _get_numpy_arrays(func_name, dtype, input_values)
 
         dp_array = dpnp.array(np_array)
         out_dtype = _get_output_data_type(dtype)
         dp_out = dpnp.empty(expected.shape, dtype=out_dtype)
-        result = dpnp.sin(dp_array, out=dp_out)
+        result = getattr(dpnp, func_name)(dp_array, out=dp_out)
 
         assert result is dp_out
         assert_dtype_allclose(result, expected)
 
-    @pytest.mark.parametrize(
-        "dtype",
-        [numpy.float32, numpy.int64, numpy.int32],
-        ids=["numpy.float32", "numpy.int64", "numpy.int32"],
-    )
-    def test_invalid_dtype(self, dtype):
-        dp_array = dpnp.arange(10, dtype=dpnp.complex64)
-        dp_out = dpnp.empty(10, dtype=dtype)
-
-        with pytest.raises(TypeError):
-            dpnp.sin(dp_array, out=dp_out)
-
-    @pytest.mark.parametrize(
-        "shape", [(0,), (15,), (2, 2)], ids=["(0,)", "(15, )", "(2,2)"]
-    )
-    def test_invalid_shape(self, shape):
-        dp_array = dpnp.arange(10)
-        dp_out = dpnp.empty(shape, dtype=dp_array.dtype)
-
-        with pytest.raises(ValueError):
-            dpnp.sin(dp_array, out=dp_out)
-
-
-class TestSinh:
-    @pytest.mark.parametrize("dtype", get_all_dtypes())
-    def test_sinh(self, dtype):
-        np_array, expected = _get_numpy_arrays("sinh", dtype, [-5, 5, 10])
-
-        dp_array = dpnp.array(np_array)
-        out_dtype = _get_output_data_type(dtype)
-        dp_out = dpnp.empty(expected.shape, dtype=out_dtype)
-        result = dpnp.sinh(dp_array, out=dp_out)
-
-        assert result is dp_out
-        assert_dtype_allclose(result, expected)
-
-    @pytest.mark.parametrize(
-        "dtype",
-        [numpy.float32, numpy.int64, numpy.int32],
-        ids=["numpy.float32", "numpy.int64", "numpy.int32"],
-    )
-    def test_invalid_dtype(self, dtype):
-        dp_array = dpnp.arange(10, dtype=dpnp.complex64)
-        dp_out = dpnp.empty(10, dtype=dtype)
-
-        with pytest.raises(TypeError):
-            dpnp.sinh(dp_array, out=dp_out)
-
-    @pytest.mark.parametrize(
-        "shape", [(0,), (15,), (2, 2)], ids=["(0,)", "(15, )", "(2,2)"]
-    )
-    def test_invalid_shape(self, shape):
-        dp_array = dpnp.arange(10)
-        dp_out = dpnp.empty(shape, dtype=dp_array.dtype)
-
-        with pytest.raises(ValueError):
-            dpnp.sinh(dp_array, out=dp_out)
-
-
-class TestCos:
-    @pytest.mark.parametrize("dtype", get_all_dtypes())
-    def test_cos(self, dtype):
-        np_array, expected = _get_numpy_arrays("cos", dtype, [-5, 5, 10])
-
-        dp_array = dpnp.array(np_array)
-        out_dtype = _get_output_data_type(dtype)
-        dp_out = dpnp.empty(expected.shape, dtype=out_dtype)
-        result = dpnp.cos(dp_array, out=dp_out)
-
-        assert result is dp_out
-        assert_dtype_allclose(result, expected)
-
-    @pytest.mark.parametrize(
-        "dtype",
-        [numpy.float32, numpy.int64, numpy.int32],
-        ids=["numpy.float32", "numpy.int64", "numpy.int32"],
-    )
-    def test_invalid_dtype(self, dtype):
-        dp_array = dpnp.arange(10, dtype=dpnp.complex64)
-        dp_out = dpnp.empty(10, dtype=dtype)
-
-        with pytest.raises(TypeError):
-            dpnp.cos(dp_array, out=dp_out)
-
-    @pytest.mark.parametrize(
-        "shape", [(0,), (15,), (2, 2)], ids=["(0,)", "(15, )", "(2,2)"]
-    )
-    def test_invalid_shape(self, shape):
-        dp_array = dpnp.arange(10)
-        dp_out = dpnp.empty(shape, dtype=dp_array.dtype)
-
-        with pytest.raises(ValueError):
-            dpnp.cos(dp_array, out=dp_out)
-
-
-class TestCosh:
-    @pytest.mark.parametrize("dtype", get_all_dtypes())
-    def test_cosh(self, dtype):
-        np_array, expected = _get_numpy_arrays("cosh", dtype, [-5, 5, 10])
-
-        dp_array = dpnp.array(np_array)
-        out_dtype = _get_output_data_type(dtype)
-        dp_out = dpnp.empty(expected.shape, dtype=out_dtype)
-        result = dpnp.cosh(dp_array, out=dp_out)
-
-        assert result is dp_out
-        assert_dtype_allclose(result, expected)
-
-    @pytest.mark.parametrize(
-        "dtype",
-        [numpy.float32, numpy.int64, numpy.int32],
-        ids=["numpy.float32", "numpy.int64", "numpy.int32"],
-    )
-    def test_invalid_dtype(self, dtype):
-        dp_array = dpnp.arange(10, dtype=dpnp.complex64)
-        dp_out = dpnp.empty(10, dtype=dtype)
-
-        with pytest.raises(TypeError):
-            dpnp.cosh(dp_array, out=dp_out)
-
-    @pytest.mark.parametrize(
-        "shape", [(0,), (15,), (2, 2)], ids=["(0,)", "(15, )", "(2,2)"]
-    )
-    def test_invalid_shape(self, shape):
-        dp_array = dpnp.arange(10)
-        dp_out = dpnp.empty(shape, dtype=dp_array.dtype)
-
-        with pytest.raises(ValueError):
-            dpnp.cosh(dp_array, out=dp_out)
-
-
-class TestLog:
-    @pytest.mark.usefixtures("suppress_divide_numpy_warnings")
-    @pytest.mark.parametrize("dtype", get_all_dtypes())
-    def test_log(self, dtype):
-        np_array, expected = _get_numpy_arrays("log", dtype, [0.1, 10, 10])
-
-        dp_array = dpnp.array(np_array)
-        out_dtype = _get_output_data_type(dtype)
-        dp_out = dpnp.empty(expected.shape, dtype=out_dtype)
-        result = dpnp.log(dp_array, out=dp_out)
-
-        assert result is dp_out
-        assert_dtype_allclose(result, expected)
-
-    @pytest.mark.parametrize(
-        "dtype",
-        [numpy.float32, numpy.int64, numpy.int32],
-        ids=["numpy.float32", "numpy.int64", "numpy.int32"],
-    )
-    def test_invalid_dtype(self, dtype):
-        dp_array = dpnp.arange(10, dtype=dpnp.complex64)
-        dp_out = dpnp.empty(10, dtype=dtype)
-
-        with pytest.raises(TypeError):
-            dpnp.log(dp_array, out=dp_out)
-
-    @pytest.mark.parametrize(
-        "shape", [(0,), (15,), (2, 2)], ids=["(0,)", "(15, )", "(2,2)"]
-    )
-    def test_invalid_shape(self, shape):
-        dp_array = dpnp.arange(10)
-        dp_out = dpnp.empty(shape, dtype=dp_array.dtype)
-
-        with pytest.raises(ValueError):
-            dpnp.log(dp_array, out=dp_out)
-
-
-class TestExp:
-    @pytest.mark.parametrize("dtype", get_all_dtypes())
-    def test_exp(self, dtype):
-        np_array, expected = _get_numpy_arrays("exp", dtype, [-3, 8, 10])
-
-        dp_array = dpnp.array(np_array)
-        out_dtype = _get_output_data_type(dtype)
-        dp_out = dpnp.empty(expected.shape, dtype=out_dtype)
-        result = dpnp.exp(dp_array, out=dp_out)
-
-        assert result is dp_out
-        assert_dtype_allclose(result, expected)
-
-    @pytest.mark.parametrize(
-        "dtype", get_all_dtypes(no_complex=True, no_none=True)[:-1]
-    )
-    def test_invalid_dtype(self, dtype):
-        dpnp_dtype = get_all_dtypes(no_complex=True, no_none=True)[-1]
+    @pytest.mark.parametrize("dtype", get_all_dtypes(no_none=True)[:-1])
+    def test_invalid_dtype(self, func_params, dtype):
+        func_name = func_params["func_name"]
+        dpnp_dtype = get_all_dtypes(no_none=True)[-1]
         dp_array = dpnp.arange(10, dtype=dpnp_dtype)
         dp_out = dpnp.empty(10, dtype=dtype)
 
         with pytest.raises(TypeError):
-            dpnp.exp(dp_array, out=dp_out)
+            getattr(dpnp, func_name)(dp_array, out=dp_out)
 
-    @pytest.mark.parametrize("dtype", get_float_dtypes())
     @pytest.mark.parametrize(
         "shape", [(0,), (15,), (2, 2)], ids=["(0,)", "(15, )", "(2,2)"]
     )
-    def test_invalid_shape(self, shape, dtype):
-        dp_array = dpnp.arange(10, dtype=dtype)
-        dp_out = dpnp.empty(shape, dtype=dtype)
-
+    def test_invalid_shape(self, func_params, shape):
+        func_name = func_params["func_name"]
+        dp_array = dpnp.arange(10)
+        dp_out = dpnp.empty(shape)
         with pytest.raises(ValueError):
-            dpnp.exp(dp_array, out=dp_out)
-
-
-class TestExp2:
-    @pytest.mark.parametrize("dtype", get_all_dtypes())
-    def test_exp2(self, dtype):
-        np_array, expected = _get_numpy_arrays("exp2", dtype, [-3, 8, 10])
-
-        dp_array = dpnp.array(np_array)
-        out_dtype = _get_output_data_type(dtype)
-        dp_out = dpnp.empty(expected.shape, dtype=out_dtype)
-        result = dpnp.exp2(dp_array, out=dp_out)
-
-        assert result is dp_out
-        assert_dtype_allclose(result, expected)
+            getattr(dpnp, func_name)(dp_array, out=dp_out)
 
     @pytest.mark.parametrize(
-        "dtype", get_all_dtypes(no_complex=True, no_none=True)[:-1]
-    )
-    def test_invalid_dtype(self, dtype):
-        dpnp_dtype = get_all_dtypes(no_complex=True, no_none=True)[-1]
-        dp_array = dpnp.arange(10, dtype=dpnp_dtype)
-        dp_out = dpnp.empty(10, dtype=dtype)
-
-        with pytest.raises(TypeError):
-            dpnp.exp2(dp_array, out=dp_out)
-
-    @pytest.mark.parametrize("dtype", get_float_dtypes())
-    @pytest.mark.parametrize(
-        "shape", [(0,), (15,), (2, 2)], ids=["(0,)", "(15, )", "(2,2)"]
+        "out",
+        [4, (), [], (3, 7), [2, 4]],
+        ids=["4", "()", "[]", "(3, 7)", "[2, 4]"],
     )
-    def test_invalid_shape(self, shape, dtype):
-        dp_array = dpnp.arange(10, dtype=dtype)
-        dp_out = dpnp.empty(shape, dtype=dtype)
-
-        with pytest.raises(ValueError):
-            dpnp.exp2(dp_array, out=dp_out)
+    def test_invalid_out(self, func_params, out):
+        func_name = func_params["func_name"]
+        a = dpnp.arange(10)
+        numpy.testing.assert_raises(TypeError, getattr(dpnp, func_name), a, out)
 
 
 class TestCbrt:
@@ -410,17 +253,25 @@ def test_invalid_dtype(self, dtype):
         with pytest.raises(TypeError):
             dpnp.cbrt(dp_array, out=dp_out)
 
-    @pytest.mark.parametrize("dtype", get_float_dtypes())
     @pytest.mark.parametrize(
         "shape", [(0,), (15,), (2, 2)], ids=["(0,)", "(15, )", "(2,2)"]
     )
-    def test_invalid_shape(self, shape, dtype):
-        dp_array = dpnp.arange(10, dtype=dtype)
-        dp_out = dpnp.empty(shape, dtype=dtype)
+    def test_invalid_shape(self, shape):
+        dp_array = dpnp.arange(10)
+        dp_out = dpnp.empty(shape)
 
         with pytest.raises(ValueError):
             dpnp.cbrt(dp_array, out=dp_out)
 
+    @pytest.mark.parametrize(
+        "out",
+        [4, (), [], (3, 7), [2, 4]],
+        ids=["4", "()", "[]", "(3, 7)", "[2, 4]"],
+    )
+    def test_invalid_out(self, out):
+        a = dpnp.arange(10)
+        numpy.testing.assert_raises(TypeError, dpnp.cbrt, a, out)
+
 
 class TestRsqrt:
     @pytest.mark.usefixtures("suppress_divide_numpy_warnings")
@@ -448,245 +299,80 @@ def test_invalid_dtype(self, dtype):
         with pytest.raises(TypeError):
             dpnp.rsqrt(dp_array, out=dp_out)
 
-    @pytest.mark.parametrize("dtype", get_float_dtypes())
     @pytest.mark.parametrize(
         "shape", [(0,), (15,), (2, 2)], ids=["(0,)", "(15, )", "(2,2)"]
     )
-    def test_invalid_shape(self, shape, dtype):
-        dp_array = dpnp.arange(10, dtype=dtype)
-        dp_out = dpnp.empty(shape, dtype=dtype)
-
+    def test_invalid_shape(self, shape):
+        dp_array = dpnp.arange(10)
+        dp_out = dpnp.empty(shape)
         with pytest.raises(ValueError):
             dpnp.rsqrt(dp_array, out=dp_out)
 
-
-class TestArccos:
-    @pytest.mark.parametrize("dtype", get_all_dtypes())
-    def test_arccos(self, dtype):
-        np_array, expected = _get_numpy_arrays("arccos", dtype, [-1, 1, 10])
-
-        dp_array = dpnp.array(np_array)
-        out_dtype = _get_output_data_type(dtype)
-        dp_out = dpnp.empty(expected.shape, dtype=out_dtype)
-        result = dpnp.arccos(dp_array, out=dp_out)
-
-        assert result is dp_out
-        assert_dtype_allclose(result, expected)
-
     @pytest.mark.parametrize(
-        "dtype", get_all_dtypes(no_complex=True, no_none=True)[:-1]
-    )
-    def test_invalid_dtype(self, dtype):
-        dpnp_dtype = get_all_dtypes(no_complex=True, no_none=True)[-1]
-        dp_array = dpnp.arange(10, dtype=dpnp_dtype)
-        dp_out = dpnp.empty(10, dtype=dtype)
-
-        with pytest.raises(TypeError):
-            dpnp.arccos(dp_array, out=dp_out)
-
-    @pytest.mark.parametrize("dtype", get_float_dtypes())
-    @pytest.mark.parametrize(
-        "shape", [(0,), (15,), (2, 2)], ids=["(0,)", "(15, )", "(2,2)"]
-    )
-    def test_invalid_shape(self, shape, dtype):
-        dp_array = dpnp.arange(10, dtype=dtype)
-        dp_out = dpnp.empty(shape, dtype=dtype)
-
-        with pytest.raises(ValueError):
-            dpnp.arccos(dp_array, out=dp_out)
-
-
-class TestArccosh:
-    @pytest.mark.usefixtures("suppress_invalid_numpy_warnings")
-    @pytest.mark.parametrize("dtype", get_all_dtypes())
-    def test_arccosh(self, dtype):
-        np_array, expected = _get_numpy_arrays("arccosh", dtype, [1, 10, 10])
-
-        dp_array = dpnp.array(np_array)
-        out_dtype = _get_output_data_type(dtype)
-        dp_out = dpnp.empty(expected.shape, dtype=out_dtype)
-        result = dpnp.arccosh(dp_array, out=dp_out)
-
-        assert result is dp_out
-        assert_dtype_allclose(result, expected)
-
-    @pytest.mark.parametrize(
-        "dtype", get_all_dtypes(no_complex=True, no_none=True)[:-1]
-    )
-    def test_invalid_dtype(self, dtype):
-        dpnp_dtype = get_all_dtypes(no_complex=True, no_none=True)[-1]
-        dp_array = dpnp.arange(10, dtype=dpnp_dtype)
-        dp_out = dpnp.empty(10, dtype=dtype)
-
-        with pytest.raises(TypeError):
-            dpnp.arccosh(dp_array, out=dp_out)
-
-    @pytest.mark.parametrize("dtype", get_float_dtypes())
-    @pytest.mark.parametrize(
-        "shape", [(0,), (15,), (2, 2)], ids=["(0,)", "(15, )", "(2,2)"]
-    )
-    def test_invalid_shape(self, shape, dtype):
-        dp_array = dpnp.arange(10, dtype=dtype)
-        dp_out = dpnp.empty(shape, dtype=dtype)
-
-        with pytest.raises(ValueError):
-            dpnp.arccosh(dp_array, out=dp_out)
-
-
-class TestArcsin:
-    @pytest.mark.parametrize("dtype", get_all_dtypes())
-    def test_arcsin(self, dtype):
-        np_array, expected = _get_numpy_arrays("arcsin", dtype, [-1, 1, 10])
-
-        dp_array = dpnp.array(np_array)
-        out_dtype = _get_output_data_type(dtype)
-        dp_out = dpnp.empty(expected.shape, dtype=out_dtype)
-        result = dpnp.arcsin(dp_array, out=dp_out)
-
-        assert result is dp_out
-        assert_dtype_allclose(result, expected)
-
-    @pytest.mark.parametrize(
-        "dtype", get_all_dtypes(no_complex=True, no_none=True)[:-1]
-    )
-    def test_invalid_dtype(self, dtype):
-        dpnp_dtype = get_all_dtypes(no_complex=True, no_none=True)[-1]
-        dp_array = dpnp.arange(10, dtype=dpnp_dtype)
-        dp_out = dpnp.empty(10, dtype=dtype)
-
-        with pytest.raises(TypeError):
-            dpnp.arcsin(dp_array, out=dp_out)
-
-    @pytest.mark.parametrize("dtype", get_float_dtypes())
-    @pytest.mark.parametrize(
-        "shape", [(0,), (15,), (2, 2)], ids=["(0,)", "(15, )", "(2,2)"]
-    )
-    def test_invalid_shape(self, shape, dtype):
-        dp_array = dpnp.arange(10, dtype=dtype)
-        dp_out = dpnp.empty(shape, dtype=dtype)
-
-        with pytest.raises(ValueError):
-            dpnp.arcsin(dp_array, out=dp_out)
-
-
-class TestArcsinh:
-    @pytest.mark.parametrize("dtype", get_all_dtypes())
-    def test_arcsinh(self, dtype):
-        np_array, expected = _get_numpy_arrays("arcsinh", dtype, [-5, 5, 10])
-
-        dp_array = dpnp.array(np_array)
-        out_dtype = _get_output_data_type(dtype)
-        dp_out = dpnp.empty(expected.shape, dtype=out_dtype)
-        result = dpnp.arcsinh(dp_array, out=dp_out)
-
-        assert result is dp_out
-        assert_dtype_allclose(result, expected)
-
-    @pytest.mark.parametrize(
-        "dtype", get_all_dtypes(no_complex=True, no_none=True)[:-1]
-    )
-    def test_invalid_dtype(self, dtype):
-        dpnp_dtype = get_all_dtypes(no_complex=True, no_none=True)[-1]
-        dp_array = dpnp.arange(10, dtype=dpnp_dtype)
-        dp_out = dpnp.empty(10, dtype=dtype)
-
-        with pytest.raises(TypeError):
-            dpnp.arcsinh(dp_array, out=dp_out)
-
-    @pytest.mark.parametrize("dtype", get_float_dtypes())
-    @pytest.mark.parametrize(
-        "shape", [(0,), (15,), (2, 2)], ids=["(0,)", "(15, )", "(2,2)"]
+        "out",
+        [4, (), [], (3, 7), [2, 4]],
+        ids=["4", "()", "[]", "(3, 7)", "[2, 4]"],
     )
-    def test_invalid_shape(self, shape, dtype):
-        dp_array = dpnp.arange(10, dtype=dtype)
-        dp_out = dpnp.empty(shape, dtype=dtype)
-
-        with pytest.raises(ValueError):
-            dpnp.arcsinh(dp_array, out=dp_out)
+    def test_invalid_out(self, out):
+        a = dpnp.arange(10)
+        numpy.testing.assert_raises(TypeError, dpnp.rsqrt, a, out)
 
 
-class TestArctan:
+class TestSquare:
     @pytest.mark.parametrize("dtype", get_all_dtypes())
-    def test_arctan(self, dtype):
-        np_array, expected = _get_numpy_arrays("arctan", dtype, [-5, 5, 10])
+    def test_square(self, dtype):
+        np_array, expected = _get_numpy_arrays("square", dtype, [-5, 5, 10])
 
         dp_array = dpnp.array(np_array)
-        out_dtype = _get_output_data_type(dtype)
+        out_dtype = numpy.int8 if dtype == numpy.bool_ else dtype
         dp_out = dpnp.empty(expected.shape, dtype=out_dtype)
-        result = dpnp.arctan(dp_array, out=dp_out)
+        result = dpnp.square(dp_array, out=dp_out)
 
         assert result is dp_out
         assert_dtype_allclose(result, expected)
 
-    @pytest.mark.parametrize(
-        "dtype", get_all_dtypes(no_complex=True, no_none=True)[:-1]
-    )
+    @pytest.mark.parametrize("dtype", get_all_dtypes(no_none=True)[:-1])
     def test_invalid_dtype(self, dtype):
-        dpnp_dtype = get_all_dtypes(no_complex=True, no_none=True)[-1]
+        dpnp_dtype = get_all_dtypes(no_none=True)[-1]
         dp_array = dpnp.arange(10, dtype=dpnp_dtype)
         dp_out = dpnp.empty(10, dtype=dtype)
 
         with pytest.raises(TypeError):
-            dpnp.arctan(dp_array, out=dp_out)
+            dpnp.square(dp_array, out=dp_out)
 
-    @pytest.mark.parametrize("dtype", get_float_dtypes())
     @pytest.mark.parametrize(
         "shape", [(0,), (15,), (2, 2)], ids=["(0,)", "(15, )", "(2,2)"]
     )
-    def test_invalid_shape(self, shape, dtype):
-        dp_array = dpnp.arange(10, dtype=dtype)
-        dp_out = dpnp.empty(shape, dtype=dtype)
-
+    def test_invalid_shape(self, shape):
+        dp_array = dpnp.arange(10)
+        dp_out = dpnp.empty(shape)
         with pytest.raises(ValueError):
-            dpnp.arctan(dp_array, out=dp_out)
-
-
-class TestArctanh:
-    @pytest.mark.usefixtures("suppress_divide_numpy_warnings")
-    @pytest.mark.parametrize("dtype", get_all_dtypes())
-    def test_arctanh(self, dtype):
-        np_array, expected = _get_numpy_arrays("arctanh", dtype, [-1, 1, 10])
-
-        dp_array = dpnp.array(np_array)
-        out_dtype = _get_output_data_type(dtype)
-        dp_out = dpnp.empty(expected.shape, dtype=out_dtype)
-        result = dpnp.arctanh(dp_array, out=dp_out)
-
-        assert result is dp_out
-        assert_dtype_allclose(result, expected)
-
-    @pytest.mark.parametrize(
-        "dtype", get_all_dtypes(no_complex=True, no_none=True)[:-1]
-    )
-    def test_invalid_dtype(self, dtype):
-        dpnp_dtype = get_all_dtypes(no_complex=True, no_none=True)[-1]
-        dp_array = dpnp.arange(10, dtype=dpnp_dtype)
-        dp_out = dpnp.empty(10, dtype=dtype)
-
-        with pytest.raises(TypeError):
-            dpnp.arctanh(dp_array, out=dp_out)
+            dpnp.square(dp_array, out=dp_out)
 
-    @pytest.mark.parametrize("dtype", get_float_dtypes())
     @pytest.mark.parametrize(
-        "shape", [(0,), (15,), (2, 2)], ids=["(0,)", "(15, )", "(2,2)"]
+        "out",
+        [4, (), [], (3, 7), [2, 4]],
+        ids=["4", "()", "[]", "(3, 7)", "[2, 4]"],
     )
-    def test_invalid_shape(self, shape, dtype):
-        dp_array = dpnp.arange(10, dtype=dtype)
-        dp_out = dpnp.empty(shape, dtype=dtype)
+    def test_invalid_out(self, out):
+        a = dpnp.arange(10)
 
-        with pytest.raises(ValueError):
-            dpnp.arctanh(dp_array, out=dp_out)
+        numpy.testing.assert_raises(TypeError, dpnp.square, a, out)
+        numpy.testing.assert_raises(TypeError, numpy.square, a.asnumpy(), out)
 
 
-class TestTan:
-    @pytest.mark.parametrize("dtype", get_all_dtypes())
-    def test_tan(self, dtype):
-        np_array, expected = _get_numpy_arrays("tan", dtype, [-5, 5, 10])
+class TestArctan2:
+    @pytest.mark.parametrize("dtype", get_all_dtypes(no_complex=True))
+    def test_arctan2(self, dtype):
+        np_array1, _ = _get_numpy_arrays("array", dtype, [-5, 5, 10])
+        np_array2, _ = _get_numpy_arrays("array", dtype, [-5, 5, 10])
+        expected = numpy.arctan2(np_array1, np_array2)
 
-        dp_array = dpnp.array(np_array)
+        dp_array1 = dpnp.array(np_array1)
+        dp_array2 = dpnp.array(np_array2)
         out_dtype = _get_output_data_type(dtype)
         dp_out = dpnp.empty(expected.shape, dtype=out_dtype)
-        result = dpnp.tan(dp_array, out=dp_out)
+        result = dpnp.arctan2(dp_array1, dp_array2, out=dp_out)
 
         assert result is dp_out
         assert_dtype_allclose(result, expected)
@@ -700,44 +386,14 @@ def test_invalid_dtype(self, dtype):
         dp_out = dpnp.empty(10, dtype=dtype)
 
         with pytest.raises(TypeError):
-            dpnp.tan(dp_array, out=dp_out)
-
-    @pytest.mark.parametrize("dtype", get_float_dtypes())
-    @pytest.mark.parametrize(
-        "shape", [(0,), (15,), (2, 2)], ids=["(0,)", "(15, )", "(2,2)"]
-    )
-    def test_invalid_shape(self, shape, dtype):
-        dp_array = dpnp.arange(10, dtype=dtype)
-        dp_out = dpnp.empty(shape, dtype=dtype)
-
-        with pytest.raises(ValueError):
-            dpnp.tan(dp_array, out=dp_out)
-
-
-class TestArctan2:
-    @pytest.mark.parametrize("dtype", get_all_dtypes(no_complex=True))
-    def test_arctan2(self, dtype):
-        np_array1, _ = _get_numpy_arrays("array", dtype, [-5, 5, 10])
-        np_array2, _ = _get_numpy_arrays("array", dtype, [-5, 5, 10])
-        expected = numpy.arctan2(np_array1, np_array2)
-
-        dp_array1 = dpnp.array(np_array1)
-        dp_array2 = dpnp.array(np_array2)
-        out_dtype = _get_output_data_type(dtype)
-        dp_out = dpnp.empty(expected.shape, dtype=out_dtype)
-        result = dpnp.arctan2(dp_array1, dp_array2, out=dp_out)
-
-        assert result is dp_out
-        assert_dtype_allclose(result, expected)
+            dpnp.arctan2(dp_array, dp_array, out=dp_out)
 
-    @pytest.mark.parametrize("dtype", get_float_dtypes())
     @pytest.mark.parametrize(
         "shape", [(0,), (15,), (2, 2)], ids=["(0,)", "(15, )", "(2,2)"]
     )
-    def test_invalid_shape(self, shape, dtype):
-        dp_array = dpnp.arange(10, dtype=dtype)
-        dp_out = dpnp.empty(shape, dtype=dtype)
-
+    def test_invalid_shape(self, shape):
+        dp_array = dpnp.arange(10)
+        dp_out = dpnp.empty(shape)
         with pytest.raises(ValueError):
             dpnp.arctan2(dp_array, dp_array, out=dp_out)
 
@@ -758,103 +414,57 @@ def test_copysign(self, dtype):
         assert result is dp_out
         assert_dtype_allclose(result, expected)
 
-    @pytest.mark.parametrize("dtype", get_float_dtypes())
     @pytest.mark.parametrize(
-        "shape", [(0,), (15,), (2, 2)], ids=["(0,)", "(15, )", "(2,2)"]
-    )
-    def test_invalid_shape(self, shape, dtype):
-        dp_array = dpnp.arange(10, dtype=dtype)
-        dp_out = dpnp.empty(shape, dtype=dtype)
-
-        with pytest.raises(ValueError):
-            dpnp.copysign(dp_array, dp_array, out=dp_out)
-
-
-class TestSqrt:
-    @pytest.mark.parametrize("dtype", get_all_dtypes())
-    def test_sqrt(self, dtype):
-        np_array, expected = _get_numpy_arrays("sqrt", dtype, [0, 10, 10])
-
-        dp_array = dpnp.array(np_array)
-        out_dtype = _get_output_data_type(dtype)
-        dp_out = dpnp.empty(expected.shape, dtype=out_dtype)
-        result = dpnp.sqrt(dp_array, out=dp_out)
-
-        assert result is dp_out
-        assert_dtype_allclose(result, expected)
-
-    @pytest.mark.parametrize(
-        "dtype", [numpy.int64, numpy.int32], ids=["numpy.int64", "numpy.int32"]
+        "dtype", get_all_dtypes(no_complex=True, no_none=True)[:-1]
     )
     def test_invalid_dtype(self, dtype):
-        dp_array = dpnp.arange(10, dtype=dpnp.float32)
+        dpnp_dtype = get_all_dtypes(no_complex=True, no_none=True)[-1]
+        dp_array = dpnp.arange(10, dtype=dpnp_dtype)
         dp_out = dpnp.empty(10, dtype=dtype)
-
         with pytest.raises(TypeError):
-            dpnp.sqrt(dp_array, out=dp_out)
+            dpnp.copysign(dp_array, dp_array, out=dp_out)
 
     @pytest.mark.parametrize(
         "shape", [(0,), (15,), (2, 2)], ids=["(0,)", "(15, )", "(2,2)"]
     )
     def test_invalid_shape(self, shape):
-        dp_array = dpnp.arange(10, dtype=dpnp.float32)
-        dp_out = dpnp.empty(shape, dtype=dpnp.float32)
-
+        dp_array = dpnp.arange(10)
+        dp_out = dpnp.empty(shape)
         with pytest.raises(ValueError):
-            dpnp.sqrt(dp_array, out=dp_out)
-
-    @pytest.mark.parametrize(
-        "out",
-        [4, (), [], (3, 7), [2, 4]],
-        ids=["4", "()", "[]", "(3, 7)", "[2, 4]"],
-    )
-    def test_invalid_out(self, out):
-        a = dpnp.arange(10)
-
-        numpy.testing.assert_raises(TypeError, dpnp.sqrt, a, out)
-        numpy.testing.assert_raises(TypeError, numpy.sqrt, a.asnumpy(), out)
+            dpnp.copysign(dp_array, dp_array, out=dp_out)
 
 
-class TestSquare:
-    @pytest.mark.parametrize("dtype", get_all_dtypes())
-    def test_square(self, dtype):
-        np_array, expected = _get_numpy_arrays("square", dtype, [-5, 5, 10])
+class TestLogaddexp:
+    @pytest.mark.parametrize("dtype", get_all_dtypes(no_complex=True))
+    def test_logaddexp(self, dtype):
+        np_array1, _ = _get_numpy_arrays("array", dtype, [-5, 5, 10])
+        np_array2, _ = _get_numpy_arrays("array", dtype, [-5, 5, 10])
+        expected = numpy.logaddexp(np_array1, np_array2)
 
-        dp_array = dpnp.array(np_array)
-        out_dtype = numpy.int8 if dtype == numpy.bool_ else dtype
+        dp_array1 = dpnp.array(np_array1)
+        dp_array2 = dpnp.array(np_array2)
+        out_dtype = _get_output_data_type(dtype)
         dp_out = dpnp.empty(expected.shape, dtype=out_dtype)
-        result = dpnp.square(dp_array, out=dp_out)
+        result = dpnp.logaddexp(dp_array1, dp_array2, out=dp_out)
 
         assert result is dp_out
         assert_dtype_allclose(result, expected)
 
     @pytest.mark.parametrize(
-        "dtype", get_all_dtypes(no_bool=True, no_none=True)
+        "dtype", get_all_dtypes(no_complex=True, no_none=True)[:-1]
     )
     def test_invalid_dtype(self, dtype):
-        dp_array = dpnp.ones(10, dtype=dpnp.bool)
+        dpnp_dtype = get_all_dtypes(no_complex=True, no_none=True)[-1]
+        dp_array = dpnp.arange(10, dtype=dpnp_dtype)
         dp_out = dpnp.empty(10, dtype=dtype)
-
         with pytest.raises(TypeError):
-            dpnp.square(dp_array, out=dp_out)
+            dpnp.logaddexp(dp_array, dp_array, out=dp_out)
 
     @pytest.mark.parametrize(
         "shape", [(0,), (15,), (2, 2)], ids=["(0,)", "(15, )", "(2,2)"]
     )
     def test_invalid_shape(self, shape):
-        dp_array = dpnp.arange(10, dtype=dpnp.float32)
-        dp_out = dpnp.empty(shape, dtype=dpnp.float32)
-
+        dp_array = dpnp.arange(10)
+        dp_out = dpnp.empty(shape)
         with pytest.raises(ValueError):
-            dpnp.square(dp_array, out=dp_out)
-
-    @pytest.mark.parametrize(
-        "out",
-        [4, (), [], (3, 7), [2, 4]],
-        ids=["4", "()", "[]", "(3, 7)", "[2, 4]"],
-    )
-    def test_invalid_out(self, out):
-        a = dpnp.arange(10)
-
-        numpy.testing.assert_raises(TypeError, dpnp.square, a, out)
-        numpy.testing.assert_raises(TypeError, numpy.square, a.asnumpy(), out)
+            dpnp.logaddexp(dp_array, dp_array, out=dp_out)

From 50374ba904bd8cf6559b3fc6977aa6038ead688e Mon Sep 17 00:00:00 2001
From: Vahid Tavanashad <vahid.tavanashad@intel.com>
Date: Wed, 17 Jan 2024 08:06:03 -0600
Subject: [PATCH 3/3] address comments

---
 dpnp/dpnp_algo/dpnp_elementwise_common.py | 347 +++++-----------------
 1 file changed, 75 insertions(+), 272 deletions(-)

diff --git a/dpnp/dpnp_algo/dpnp_elementwise_common.py b/dpnp/dpnp_algo/dpnp_elementwise_common.py
index 5f1441f423a0..a3ac7a8f0a6c 100644
--- a/dpnp/dpnp_algo/dpnp_elementwise_common.py
+++ b/dpnp/dpnp_algo/dpnp_elementwise_common.py
@@ -177,6 +177,13 @@ def check_nd_call_func(
         )
 
 
+def _get_result(res_usm, out=None):
+    if out is None:
+        return dpnp_array._create_from_usm_ndarray(res_usm)
+    else:
+        return out
+
+
 def _make_unary_func(
     name, dpt_unary_fn, fn_docstring, mkl_fn_to_call=None, mkl_impl_fn=None
 ):
@@ -273,10 +280,7 @@ def dpnp_abs(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = abs_func(x1_usm, out=out_usm, order=order)
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _acos_docstring = """
@@ -317,10 +321,7 @@ def dpnp_acos(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = acos_func(x1_usm, out=out_usm, order=order)
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _acosh_docstring = """
@@ -361,10 +362,7 @@ def dpnp_acosh(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = acosh_func(x1_usm, out=out_usm, order=order)
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _add_docstring = """
@@ -410,10 +408,7 @@ def dpnp_add(x1, x2, out=None, order="K"):
     res_usm = add_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _asin_docstring = """
@@ -454,10 +449,7 @@ def dpnp_asin(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = asin_func(x1_usm, out=out_usm, order=order)
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _asinh_docstring = """
@@ -498,10 +490,7 @@ def dpnp_asinh(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = asinh_func(x1_usm, out=out_usm, order=order)
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _atan_docstring = """
@@ -542,10 +531,7 @@ def dpnp_atan(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = atan_func(x1_usm, out=out_usm, order=order)
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _atan2_docstring = """
@@ -595,10 +581,7 @@ def dpnp_atan2(x1, x2, out=None, order="K"):
     res_usm = atan2_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _atanh_docstring = """
@@ -639,10 +622,7 @@ def dpnp_atanh(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = atanh_func(x1_usm, out=out_usm, order=order)
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _bitwise_and_docstring = """
@@ -686,10 +666,7 @@ def dpnp_bitwise_and(x1, x2, out=None, order="K"):
     res_usm = bitwise_and_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _bitwise_or_docstring = """
@@ -733,10 +710,7 @@ def dpnp_bitwise_or(x1, x2, out=None, order="K"):
     res_usm = bitwise_or_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _bitwise_xor_docstring = """
@@ -780,10 +754,7 @@ def dpnp_bitwise_xor(x1, x2, out=None, order="K"):
     res_usm = bitwise_xor_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _cbrt_docstring = """
@@ -823,10 +794,7 @@ def dpnp_cbrt(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = cbrt_func(x1_usm, out=out_usm, order=order)
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _ceil_docstring = """
@@ -866,10 +834,7 @@ def dpnp_ceil(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = ceil_func(x1_usm, out=out_usm, order=order)
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _conj_docstring = """
@@ -908,10 +873,7 @@ def dpnp_conj(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = conj_func(x1_usm, out=out_usm, order=order)
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _copysign_docstring = """
@@ -952,10 +914,7 @@ def dpnp_copysign(x1, x2, out=None, order="K"):
     res_usm = copysign_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _cos_docstring = """
@@ -995,10 +954,7 @@ def dpnp_cos(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = cos_func(x1_usm, out=out_usm, order=order)
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _cosh_docstring = """
@@ -1038,10 +994,7 @@ def dpnp_cosh(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = cosh_func(x1_usm, out=out_usm, order=order)
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _divide_docstring = """
@@ -1087,10 +1040,7 @@ def dpnp_divide(x1, x2, out=None, order="K"):
     res_usm = divide_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _equal_docstring = """
@@ -1130,10 +1080,7 @@ def dpnp_equal(x1, x2, out=None, order="K"):
     res_usm = equal_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _exp_docstring = """
@@ -1174,10 +1121,7 @@ def dpnp_exp(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = exp_func(x1_usm, out=out_usm, order=order)
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _exp2_docstring = """
@@ -1218,10 +1162,7 @@ def dpnp_exp2(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = exp2_func(x1_usm, out=out_usm, order=order)
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _expm1_docstring = """
@@ -1264,10 +1205,7 @@ def dpnp_expm1(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = expm1_func(x1_usm, out=out_usm, order=order)
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _floor_docstring = """
@@ -1307,10 +1245,7 @@ def dpnp_floor(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = floor_func(x1_usm, out=out_usm, order=order)
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _floor_divide_docstring = """
@@ -1354,10 +1289,7 @@ def dpnp_floor_divide(x1, x2, out=None, order="K"):
     res_usm = floor_divide_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _greater_docstring = """
@@ -1397,10 +1329,7 @@ def dpnp_greater(x1, x2, out=None, order="K"):
     res_usm = greater_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _greater_equal_docstring = """
@@ -1442,10 +1371,7 @@ def dpnp_greater_equal(x1, x2, out=None, order="K"):
     res_usm = greater_equal_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _hypot_docstring = """
@@ -1491,10 +1417,7 @@ def dpnp_hypot(x1, x2, out=None, order="K"):
     res_usm = hypot_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _imag_docstring = """
@@ -1531,10 +1454,7 @@ def dpnp_imag(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = imag_func(x1_usm, out=out_usm, order=order)
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _invert_docstring = """
@@ -1569,10 +1489,7 @@ def dpnp_invert(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = invert_func(x_usm, out=out_usm, order=order)
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _isfinite_docstring = """
@@ -1607,10 +1524,7 @@ def dpnp_isfinite(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = isfinite_func(x1_usm, out=out_usm, order=order)
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _isinf_docstring = """
@@ -1644,10 +1558,7 @@ def dpnp_isinf(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = isinf_func(x1_usm, out=out_usm, order=order)
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _isnan_docstring = """
@@ -1681,10 +1592,7 @@ def dpnp_isnan(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = isnan_func(x1_usm, out=out_usm, order=order)
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _left_shift_docstring = """
@@ -1728,10 +1636,7 @@ def dpnp_left_shift(x1, x2, out=None, order="K"):
     res_usm = left_shift_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _less_docstring = """
@@ -1771,10 +1676,7 @@ def dpnp_less(x1, x2, out=None, order="K"):
     res_usm = less_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _less_equal_docstring = """
@@ -1816,10 +1718,7 @@ def dpnp_less_equal(x1, x2, out=None, order="K"):
     res_usm = less_equal_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _log_docstring = """
@@ -1860,10 +1759,7 @@ def dpnp_log(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = log_func(x1_usm, out=out_usm, order=order)
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _log10_docstring = """
@@ -1904,10 +1800,7 @@ def dpnp_log10(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = log10_func(x1_usm, out=out_usm, order=order)
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _log1p_docstring = """
@@ -1947,10 +1840,7 @@ def dpnp_log1p(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = log1p_func(x1_usm, out=out_usm, order=order)
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _log2_docstring = """
@@ -1991,10 +1881,7 @@ def dpnp_log2(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = log2_func(x1_usm, out=out_usm, order=order)
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _logaddexp_docstring = """
@@ -2042,10 +1929,7 @@ def dpnp_logaddexp(x1, x2, out=None, order="K"):
     res_usm = logaddexp_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _logical_and_docstring = """
@@ -2086,10 +1970,7 @@ def dpnp_logical_and(x1, x2, out=None, order="K"):
     res_usm = logical_and_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _logical_not_docstring = """
@@ -2124,10 +2005,7 @@ def dpnp_logical_not(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = logical_not_func(x_usm, out=out_usm, order=order)
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _logical_or_docstring = """
@@ -2168,10 +2046,7 @@ def dpnp_logical_or(x1, x2, out=None, order="K"):
     res_usm = logical_or_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _logical_xor_docstring = """
@@ -2212,10 +2087,7 @@ def dpnp_logical_xor(x1, x2, out=None, order="K"):
     res_usm = logical_xor_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _maximum_docstring = """
@@ -2255,10 +2127,7 @@ def dpnp_maximum(x1, x2, out=None, order="K"):
     res_usm = maximum_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _minimum_docstring = """
@@ -2298,10 +2167,7 @@ def dpnp_minimum(x1, x2, out=None, order="K"):
     res_usm = minimum_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _multiply_docstring = """
@@ -2351,10 +2217,7 @@ def dpnp_multiply(x1, x2, out=None, order="K"):
     res_usm = multiply_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _negative_docstring = """
@@ -2394,10 +2257,7 @@ def dpnp_negative(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = negative_func(x1_usm, out=out_usm, order=order)
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _not_equal_docstring = """
@@ -2439,10 +2299,7 @@ def dpnp_not_equal(x1, x2, out=None, order="K"):
     res_usm = not_equal_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _positive_docstring = """
@@ -2481,10 +2338,7 @@ def dpnp_positive(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = positive_func(x1_usm, out=out_usm, order=order)
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _power_docstring = """
@@ -2531,10 +2385,7 @@ def dpnp_power(x1, x2, out=None, order="K"):
     res_usm = power_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _proj_docstring = """
@@ -2568,10 +2419,7 @@ def dpnp_proj(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = proj_func(x1_usm, out=out_usm, order=order)
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _real_docstring = """
@@ -2608,10 +2456,7 @@ def dpnp_real(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = real_func(x1_usm, out=out_usm, order=order)
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _remainder_docstring = """
@@ -2652,10 +2497,7 @@ def dpnp_remainder(x1, x2, out=None, order="K"):
     res_usm = remainder_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _right_shift_docstring = """
@@ -2698,10 +2540,7 @@ def dpnp_right_shift(x1, x2, out=None, order="K"):
     res_usm = right_shift_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _round_docstring = """
@@ -2741,10 +2580,7 @@ def dpnp_round(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = round_func(x1_usm, out=out_usm, order=order)
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _rsqrt_docstring = """
@@ -2779,10 +2615,7 @@ def dpnp_rsqrt(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = rsqrt_func(x1_usm, out=out_usm, order=order)
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _sign_docstring = """
@@ -2824,10 +2657,7 @@ def dpnp_sign(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = sign_func(x1_usm, out=out_usm, order=order)
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _signbit_docstring = """
@@ -2862,10 +2692,7 @@ def dpnp_signbit(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = signbit_func(x1_usm, out=out_usm, order=order)
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _sin_docstring = """
@@ -2905,10 +2732,7 @@ def dpnp_sin(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = sin_func(x1_usm, out=out_usm, order=order)
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _sinh_docstring = """
@@ -2948,10 +2772,7 @@ def dpnp_sinh(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = sinh_func(x1_usm, out=out_usm, order=order)
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _sqrt_docstring = """
@@ -2990,10 +2811,7 @@ def dpnp_sqrt(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = sqrt_func(x_usm, out=out_usm, order=order)
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _square_docstring = """
@@ -3032,10 +2850,7 @@ def dpnp_square(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = square_func(x_usm, out=out_usm, order=order)
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _subtract_docstring = """
@@ -3096,10 +2911,7 @@ def dpnp_subtract(x1, x2, out=None, order="K"):
     res_usm = subtract_func(
         x1_usm_or_scalar, x2_usm_or_scalar, out=out_usm, order=order
     )
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _tan_docstring = """
@@ -3139,10 +2951,7 @@ def dpnp_tan(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = tan_func(x1_usm, out=out_usm, order=order)
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _tanh_docstring = """
@@ -3182,10 +2991,7 @@ def dpnp_tanh(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = tanh_func(x1_usm, out=out_usm, order=order)
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)
 
 
 _trunc_docstring = """
@@ -3227,7 +3033,4 @@ def dpnp_trunc(x, out=None, order="K"):
     out_usm = None if out is None else dpnp.get_usm_ndarray(out)
 
     res_usm = trunc_func(x1_usm, out=out_usm, order=order)
-    if out is None:
-        return dpnp_array._create_from_usm_ndarray(res_usm)
-    else:
-        return out
+    return _get_result(res_usm, out=out)