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import pytest
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- from .helper import get_all_dtypes
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+ from .helper import (
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+ get_all_dtypes ,
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+ is_cpu_device ,
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+ is_win_platform
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+ )
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import dpnp
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@@ -206,8 +210,12 @@ def test_op_with_scalar(array, val, func, data_type, val_type):
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dpnp_a = dpnp .array (array , dtype = data_type )
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val_ = val_type (val )
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- if func == 'power' and val_ == 0 and numpy .issubdtype (data_type , numpy .complexfloating ):
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- pytest .skip ("(0j ** 0) is different: (NaN + NaNj) in dpnp and (1 + 0j) in numpy" )
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+ if func == 'power' :
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+ if val_ == 0 and numpy .issubdtype (data_type , numpy .complexfloating ):
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+ pytest .skip ("(0j ** 0) is different: (NaN + NaNj) in dpnp and (1 + 0j) in numpy" )
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+ elif is_cpu_device () and data_type == dpnp .complex128 :
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+ # TODO: discuss the bahavior with OneMKL team
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+ pytest .skip ("(0j ** 5) is different: (NaN + NaNj) in dpnp and (0j) in numpy" )
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if func == 'subtract' and val_type == bool and data_type == dpnp .bool :
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with pytest .raises (TypeError ):
@@ -219,11 +227,11 @@ def test_op_with_scalar(array, val, func, data_type, val_type):
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else :
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result = getattr (dpnp , func )(dpnp_a , val_ )
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expected = getattr (numpy , func )(np_a , val_ )
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- assert_allclose (result , expected )
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+ assert_allclose (result , expected , rtol = 1e-6 )
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result = getattr (dpnp , func )(val_ , dpnp_a )
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expected = getattr (numpy , func )(val_ , np_a )
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- assert_allclose (result , expected )
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+ assert_allclose (result , expected , rtol = 1e-6 )
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@pytest .mark .parametrize ("shape" ,
@@ -355,6 +363,10 @@ def test_power(array, val, data_type, val_type):
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dpnp_a = dpnp .array (array , dtype = data_type )
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val_ = val_type (val )
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+ if is_cpu_device () and dpnp .complex128 in (data_type , val_type ):
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+ # TODO: discuss the behavior with OneMKL team
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+ pytest .skip ("(0j ** 5) is different: (NaN + NaNj) in dpnp and (0j) in numpy" )
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+
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result = dpnp .power (dpnp_a , val_ )
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expected = numpy .power (np_a , val_ )
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assert_allclose (expected , result , rtol = 1e-6 )
@@ -673,11 +685,17 @@ def test_invalid_out(self, out):
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@pytest .mark .usefixtures ("suppress_invalid_numpy_warnings" )
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def test_complex_values (self ):
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- np_arr = numpy .array ([0j , 1 + 1j , 0 + 2j , 1 + 2j , numpy .inf , numpy .nan ])
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+ np_arr = numpy .array ([0j , 1 + 1j , 0 + 2j , 1 + 2j , numpy .nan , numpy .inf ])
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dp_arr = dpnp .array (np_arr )
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func = lambda x : x ** 2
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- assert_allclose (func (np_arr ), func (dp_arr ).asnumpy ())
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+ # Linux: ((inf + 0j) ** 2) == (Inf + NaNj) in dpnp and == (NaN + NaNj) in numpy
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+ # Win: ((inf + 0j) ** 2) == (Inf + 0j) in dpnp and == (Inf + NaNj) in numpy
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+ if is_win_platform ():
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+ assert_equal (func (dp_arr )[5 ], numpy .inf )
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+ else :
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+ assert_equal (func (dp_arr )[5 ], (numpy .inf + 0j ) * 1 )
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+ assert_allclose (func (np_arr )[:5 ], func (dp_arr ).asnumpy ()[:5 ], rtol = 1e-6 )
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@pytest .mark .parametrize ("val" , [0 , 1 ], ids = ['0' , '1' ])
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@pytest .mark .parametrize ("dtype" , [dpnp .int32 , dpnp .int64 ])
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