Unique() inconsistencies

[ClaudiaComito]

Description While looking into #564, I found a number of inconsistencies in ht.unique().

• #564 is no documentation issue.

  • The kwarg sorted is set to False by default for ht.unique(), but it's True by default for torch.unique(). Currently, ht.unique(a) results in a sorted DNDarray if a.split=None (pure torch implementation: ht.unique(a) = torch.unique(a._DNDarray__array)), whereas if a.split is not None, the result will not be sorted (heat implementation).
  • Replacing ht.unique(a) = torch.unique(a._DNDarray__array) with ht.unique(a) = torch.unique(a._DNDarray__array, sorted=sorted) doesn't help, because sorted=False means different things for heat and torch:
    • heat interpretation: leave result unsorted;
    • torch interpretation: leave result REVERSE SORTED. See discussion on #564 for an example. I propose setting sorted=True by default in ht.unique() as at the moment it's the only way to prevent inconsistencies with torch, although I'm aware that the sorting comes with significant overhead. Incidentally, numpy.unique() returns the "sorted unique elements of an array" and not sorting is not even an option.

• if return_inverse=True, ht.unique() by design returns a list of one DNDarray (the unique elements) and one torch tensor (the inverse indices). Should be two DNDarrays.

• it is currently not possible to run ht.unique(a, sorted=True, axis=axis) if axis != split. Error message:

  Sorting with axis != split is not supported yet. See https://github.com/helmholtz-analytics/heat/issues/363

  This needs to be followed up.

To Reproduce Steps to reproduce the behavior:

1. Which module/class/function is affected? manipulations.unique()

2. What are the circumstances under which the bug appears? see above

3. What is the exact error message / erroneous behavior? see above

Version Info current main branch

[ClaudiaComito]

Still open and will be fixed with #749

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Reviewed within #1109

[github-actions[bot]]

Branch bugs/621-Unique_inconsistencies created!