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support multiple batch dimensions in Dense layer #1405
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Is this doing the correct thing here? |
+1, this seems like the obvious behaviour. I'd be tempted to make the existing method |
yeah, I didn't do it because the performance impact is negligible in any case, but we could. Anyway, as you said not a big deal |
bors r+ |
1405: support multiple batch dimensions in Dense layer r=DhairyaLGandhi a=CarloLucibello Since most deep learning frameworks support it, we also should. I can't find a corresponding issue. #282 is slightly related. After this, we should close #708 ### PR Checklist - [x] Tests are added - [x] Entry in NEWS.md - [x] Documentation, if applicable - [ ] Final review from `@dhairyagandhi96` (for API changes). Co-authored-by: Carlo Lucibello <[email protected]> Co-authored-by: Dhairya Gandhi <[email protected]>
If we want to strictly adhere to ColPrac (and maybe we don't ), you should just approve Prs from collaborators with merge rights, then they merge by themselves: Reviewing, Approving and Merging PRs
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you should be able to use bors like usual |
sure, but I think that you need to hit Approve in Github's review (according to ColPrac) |
bors r+ |
Build succeeded: |
Since most deep learning frameworks support it, we also should.
I can't find a corresponding issue. #282 is slightly related.
After this, we should close #708
PR Checklist
@dhairyagandhi96
(for API changes).