Add repartition(!)(::AbstractTensorMap)

[lkdvos]

No description provided.

[lkdvos]

@Jutho, I am not actually sure how to make repartition(t, N1, N2 inferrable. I've tried Base.@constprop :aggressive, which does not seem to help, and without resorting to val(N) type things, I don't think I can make it work. So maybe the next question is, does it matter? In principle, this is just a wrapper around transpose, so in important cases you can use that instead?

[Jutho]

Can you try with @constinferred repartition(t, $k) (but maybe first locally)? Constant propagation can only work if the argument is really a constant. So either you need to explicitly have @constinferred repartition(t, 3) or something, or you need to splice in the value using $k.

[lkdvos]

Can you try with @constinferred repartition(t, $k) (but maybe first locally)? Constant propagation can only work if the argument is really a constant. So either you need to explicitly have @constinferred repartition(t, 3) or something, or you need to splice in the value using $k.

Thanks! Indeed, combining the @constprop and the corrected @constinferred fixes everything, at least on my machine. I can't seem to find a way of doing this in julia v1.6 though...

[lkdvos]

So now, for Julia v1.6, there is a slight type-instability for repartition, but everything else should be fine. I think if the tests pass, this is ready to go.

[codecov]

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 81.46%. Comparing base (fe3c9c2) to head (4dc1fd0).
Report is 3 commits behind head on master.

Additional details and impacted files

@@            Coverage Diff             @@
##           master     #116      +/-   ##
==========================================
+ Coverage   81.29%   81.46%   +0.16%     
==========================================
  Files          42       42              
  Lines        5575     5588      +13     
==========================================
+ Hits         4532     4552      +20     
+ Misses       1043     1036       -7     

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[Jutho]

Ok I will merge. Given that this is an addition to the public interface, I guess this should become TensorKit v0.13? Let's hope this doesn't bring bad luck :-).

[lkdvos]

We might want to tag the latest version (v0.12.3) before this then, I think this didn't happen yet.

[Jutho]

That's a nice improvement!