Add implementation of dpnp.unique#1972
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antonwolfy merged 13 commits intomasterIntelPython/dpnp:masterfrom Aug 16, 2024
Merged
Add implementation of dpnp.unique#1972antonwolfy merged 13 commits intomasterIntelPython/dpnp:masterfrom
dpnp.unique#1972antonwolfy merged 13 commits intomasterIntelPython/dpnp:masterfrom
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vtavana
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Aug 14, 2024
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When axis is given NumPy list all rows with NaN at the bottom while dpnp does not.
import dpnp, numpy
import numpy as np
a = numpy.array([[1, 0, 0], [1, 0, 0], [np.nan, np.nan, np.nan], [2, 3, 4], [1, 0, 1], [np.nan, np.nan, np.nan]])
numpy.unique(a, axis=0)
# array([[ 1., 0., 0.],
# [ 1., 0., 1.],
# [ 2., 3., 4.],
# [nan, nan, nan],
# [nan, nan, nan]])
dpnp.unique(dpnp.asarray(a), axis=0)
#array([[ 1., 0., 0.],
# [nan, nan, nan],
# [ 1., 0., 1.],
# [ 2., 3., 4.],
# [nan, nan, nan]])In addition equal_nan=True is not working as expected when axis is given for both NumPy and dpnp. Is it the way it should be?
import dpnp, numpy
import numpy as np
a = numpy.array([[1, 0, 0], [1, 0, 0], [np.nan, np.nan, np.nan], [2, 3, 4], [1, 0, 1], [np.nan, np.nan, np.nan]])
numpy.unique(a, axis=0, equal_nan=True)
# array([[ 1., 0., 0.],
# [ 1., 0., 1.],
# [ 2., 3., 4.],
# [nan, nan, nan],
# [nan, nan, nan]])
dpnp.unique(dpnp.asarray(a), axis=0, equal_nan=True)
#array([[ 1., 0., 0.],
# [nan, nan, nan],
# [ 1., 0., 1.],
# [ 2., 3., 4.],
# [nan, nan, nan]])
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Thank you for noticing that. |
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The PR adds implementation of
dpnp.uniquefunction.The implementation leverages on dpctl.tensor implementation when axis is None. Otherwise it is implemented through python calls. The functionality is covered by new tests and enabled third party tests.