[GitHub] [incubator-mxnet] rgommers commented on issue #20898: mxnet.numpy and numpy differ regarding binary op result type with broadcast 0-dim array input

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rgommers commented on issue #20898:
URL: https://github.com/apache/incubator-mxnet/issues/20898#issuecomment-1048459723


   > @rgommers do you expect this to become a problem for API standard adoption on the numpy side?
   
   Type promotion in NumPy has a lot of weird corner cases. Right now there's an effort to get rid of those, including value-based casting. A draft NEP (Numpy Enhancement Proposal) was just posted: https://mail.python.org/archives/list/numpy-discussion@python.org/thread/RWOZYX2LN66T243C6II2BCXRWCPM3CV2/.
   
   Type casting issues are the most important reason for why we added array API support as a separate namespace (`numpy.array_api`), even though we initially aimed for the main namespace. I'm hoping we can resolve those, but with the deprecation policy that will take at least 2 more releases (and perhaps more, because it is hairy), so adding array API standard support to the main `numpy` namespace is still a long-term goal but not an easy fix.
   
   Many of the issues like the 0-D array special-casing brought up here continue to yield bug reports in NumPy itself and downstream libraries, and are design problems that shouldn't be emulated but needed fixing already before we designed the array API standard.


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