issue_comments: 522824210

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https://github.com/pydata/xarray/issues/3232#issuecomment-522824210 https://api.github.com/repos/pydata/xarray/issues/3232 522824210 MDEyOklzc3VlQ29tbWVudDUyMjgyNDIxMA== 98330 2019-08-20T02:16:32Z 2019-08-20T02:16:32Z NONE

I think there has been some discussion about this, but I don't know the current status (CC @rgommers).

The PyTorch team is definitely receptive to the idea of adding __array_function__ and __array_ufunc__, as well as expanding the API for better NumPy compatibility.

Also, they want a Tensor.__torch_function__ styled after __array_function__ so they can make their own API overridable.

The tracking issue for all of this is https://github.com/pytorch/pytorch/issues/22402

The biggest challenge for pytorch would be defining the translation layer that implements NumPy's API.

Agreed. No one is working on __array_function__ at the moment. Implementing it has some backwards compat concerns as well, because people may be relying on np.somefunc(some_torch_tensor) to be coerced to ndarray. It's not a small project, but implementing a prototype with a few function in the torch namespace that are not exactly matching the NumPy API would be a useful way to start pushing this forward.

 
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