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import unittest
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- import numpy
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import pytest
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- import dpnp as cupy
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from dpnp .tests .helper import has_support_aspect64
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from dpnp .tests .third_party .cupy import testing
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from dpnp .tests .third_party .cupy .testing ._loops import (
@@ -316,7 +314,6 @@ def test_unique_equal_nan(self, xp, dtype, equal_nan):
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)
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return xp .unique (a , axis = 1 , equal_nan = equal_nan )
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- @pytest .mark .skip ("unique_all() is not supported yet" )
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@testing .with_requires ("numpy>=2.0" )
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@pytest .mark .parametrize (
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"attr" , ["values" , "indices" , "inverse_indices" , "counts" ]
@@ -327,7 +324,6 @@ def test_unique_all(self, xp, dtype, attr):
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a = testing .shaped_random ((100 , 100 ), xp , dtype )
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return getattr (xp .unique_all (a ), attr )
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- @pytest .mark .skip ("unique_counts() is not supported yet" )
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@testing .with_requires ("numpy>=2.0" )
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@pytest .mark .parametrize ("attr" , ["values" , "counts" ])
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@testing .for_all_dtypes (no_float16 = True , no_bool = True , no_complex = True )
@@ -336,7 +332,6 @@ def test_unique_counts(self, xp, dtype, attr):
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a = testing .shaped_random ((100 , 100 ), xp , dtype )
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return getattr (xp .unique_counts (a ), attr )
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- @pytest .mark .skip ("unique_inverse() is not supported yet" )
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@testing .with_requires ("numpy>=2.0" )
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@pytest .mark .parametrize ("attr" , ["values" , "inverse_indices" ])
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@testing .for_all_dtypes (no_float16 = True , no_bool = True , no_complex = True )
@@ -345,7 +340,6 @@ def test_unique_inverse(self, xp, dtype, attr):
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a = testing .shaped_random ((100 , 100 ), xp , dtype )
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return getattr (xp .unique_inverse (a ), attr )
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- @pytest .mark .skip ("unique_values() is not supported yet" )
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@testing .with_requires ("numpy>=2.0" )
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@testing .for_all_dtypes (no_float16 = True , no_bool = True , no_complex = True )
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@testing .numpy_cupy_array_equal ()
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