2121 get_float_dtypes ,
2222 get_integer_dtypes ,
2323 has_support_aspect64 ,
24+ numpy_version ,
2425)
2526from .third_party .cupy import testing
2627
@@ -1822,10 +1823,7 @@ def test_2d_axis_nans(self, dt, axis_kwd, return_kwds, row):
18221823 if len (return_kwds ) == 0 :
18231824 assert_array_equal (result , expected )
18241825 else :
1825- if (
1826- len (axis_kwd ) == 0
1827- and numpy .lib .NumpyVersion (numpy .__version__ ) < "2.0.1"
1828- ):
1826+ if len (axis_kwd ) == 0 and numpy_version () < "2.0.1" :
18291827 # gh-26961: numpy.unique(..., return_inverse=True, axis=None)
18301828 # returned flatten unique_inverse till 2.0.1 version
18311829 expected = (
@@ -1836,6 +1834,20 @@ def test_2d_axis_nans(self, dt, axis_kwd, return_kwds, row):
18361834 for iv , v in zip (result , expected ):
18371835 assert_array_equal (iv , v )
18381836
1837+ @testing .with_requires ("numpy>=2.0" )
1838+ @pytest .mark .parametrize (
1839+ "func" ,
1840+ ["unique_all" , "unique_counts" , "unique_inverse" , "unique_values" ],
1841+ )
1842+ def test_array_api_functions (self , func ):
1843+ a = numpy .array ([numpy .nan , 1 , 4 , 1 , 3 , 4 , numpy .nan , 5 , 1 ])
1844+ ia = dpnp .array (a )
1845+
1846+ result = getattr (dpnp , func )(ia )
1847+ expected = getattr (numpy , func )(a )
1848+ for iv , v in zip (result , expected ):
1849+ assert_array_equal (iv , v )
1850+
18391851
18401852class TestVsplit :
18411853 @pytest .mark .parametrize ("xp" , [numpy , dpnp ])
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