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Implement tensor redistribution for binary operations #167
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@Markus-Goetz I will try out these rules. However, what happens in 2) if none of the tensors is split among a minor axis? |
In this case you may simply add them locally as already implemented and working |
No, I mean if they both have a split > 1, but along different axes... or is that unrealistic? |
That would be rule 3.) if both have a minor axis, than the one with the larger minor axis will be redistributed |
Couple more things that came to my mind that have to be considered:
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Why was that closed? Issue is not fixed, PR #268 bumped due to issues with MPI communication and resplit |
My apologies. i think I saw that the PR was closed (at the time it was a month after the bump, and i think that you had closed the PR). I am not sure but I think that I had thought that the PR was merged and then it was a stay issue which was not closed at the time of merging. Sorry @Cdebus |
No worries ^^ |
Status? @coquelin77 @Markus-Goetz can we break this into smaller issues? |
Alright, here's the current status of binary operations
Reviewed within #1109 |
Branch 167-Implement_tensor_redistribution_for_binary_operations created! |
Stil active and ongoing work. (Reviewed within #1109 ) |
After PR #165 is merged, implement binary operators for two tensor with set, but different split axis (e.g. split=0 and split=1).
Think of a rule to decide which tensor should be resplit. Proposal (might require modification):
EDITED July 31st 2023 by @ClaudiaComito
Here's the current status of binary operations
heat.core._operations.__binary_op()
:lshape_maps
(e.g. as a result of indexing)Reviewed within #1109
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