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required, but we don't yet have a clean way to disable only those tests (see https://github.com/data-apis/array-api-tests/issues/25).
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"""
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- # TODO: test with complex dtypes where appropiate
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+ # TODO: test with complex dtypes where appropriate
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import pytest
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from hypothesis import assume , given
@@ -558,9 +558,6 @@ def _x2_shapes(draw):
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def test_solve (x1 , x2 ):
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res = linalg .solve (x1 , x2 )
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- # TODO: This requires an upstream fix to ndindex
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- # (https://github.com/Quansight-Labs/ndindex/pull/131)
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-
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if x2 .ndim == 1 :
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_test_stacks (linalg .solve , x1 , x2 , res = res , dims = 1 ,
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matrix_axes = [(- 2 , - 1 ), (0 ,)], res_axes = [- 1 ])
@@ -714,7 +711,6 @@ def _test_tensordot_stacks(x1, x2, kw, res):
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tensordot_kw ,
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)
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def test_tensordot (x1 , x2 , kw ):
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- # TODO: vary shapes, vary contracted axes, test different axes arguments
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res = xp .tensordot (x1 , x2 , ** kw )
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ph .assert_dtype ("tensordot" , in_dtype = [x1 .dtype , x2 .dtype ],
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result_shape = _shape1 + _shape2
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ph .assert_result_shape ('tensordot' , [x1 .shape , x2 .shape ], res .shape ,
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expected = result_shape )
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- # TODO: assert stacking and elements
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_test_tensordot_stacks (x1 , x2 , kw , res )
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@pytest .mark .xp_extension ('linalg' )
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data (),
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)
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def test_vecdot (x1 , x2 , data ):
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- # TODO: vary shapes, test different axis arguments
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broadcasted_shape = sh .broadcast_shapes (x1 .shape , x2 .shape )
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min_ndim = min (x1 .ndim , x2 .ndim )
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ndim = len (broadcasted_shape )
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