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[WIP] apply_gufunc #119
[WIP] apply_gufunc #119
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Awesome - thanks for starting on this @TomNicholas!
I don't think it necessarily is an issue, but we should provide attribution, much like Dask does for NumPy for example: https://github.com/dask/dask/blob/cf7781bcf2c7b478b701fd848e78d51c5a9c6e8f/dask/array/core.py#L4071-L4073. Longer-term it would be interesting to see if it's possible to share code, perhaps by taking advantage of Dask's HLG work - but I'm not very familiar with that.
There's one in https://github.com/tomwhite/cubed/blob/main/cubed/array_api/creation_functions.py
There's no meta in Cubed, and so far it's been OK to pass dtype, shape, chunks etc around directly. Would that work here?
I think we use toolz in other places already, so that's not a problem.
It might be helpful to see how it was implemented before HLGs were introduced, just to help get some understanding. |
It would be useful to add support for gufuncs for the Pangeo examples. Is this PR something you would like to continue working on @TomNicholas? I could look at it in the new year if not. |
Hey Tom,
Sorry, as much as I would love to be working on this, realistically I'm not
going to get to it for another month at least. Don't let me stop you
pushing things forward in the meantime!
…On Mon, Dec 19, 2022, 7:57 AM Tom White ***@***.***> wrote:
It would be useful to add support for gufuncs for the Pangeo examples. Is
this PR something you would like to continue working on @TomNicholas
<https://github.com/TomNicholas>? I could look at it in the new year if
not.
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I plan to work on this soon. |
I'm going to close this now, as this was superseded by #149. Thanks for starting this @TomNicholas - it really helped me with the work in #149. |
WIP - all I've really done so far is copy across the relevant dask code from
dask/array/gufunc.py
. It's really just copied verbatim, but not importable as it's not factored out into smaller functions in dask.Comments:
asarray
functionmeta
thing?blockwise
will needconcatenate
kwargdask.array.apply_gufunc
is doing, the highlevel graph construction. I need to look through that more closely.