[fix] adaptive_{avg, max}_pool variants : cuda & cpu
#88906
Conversation
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/88906
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit 9f5f72b: This comment was automatically generated by Dr. CI and updates every 15 minutes. |
khushi-411
changed the title
adaptive_{avg, max}_pool variants : cuda & cpu
H-Huang
added
the
triaged
There was a problem hiding this comment.
Good start, @khushi-411, but see some comments/questions about the tests inline!
|
Hi, Gentle ping, @mruberry! |
|
Hi, @mruberry, Gentle ping :) |
|
Thanks for the informative comments @mruberry @kshitij12345! Merging this now... @pytorchbot merge |
Merge startedYour change will be merged once all checks pass (ETA 0-4 Hours). Learn more about merging in the wiki. Questions? Feedback? Please reach out to the PyTorch DevX Team |
Merge failedReason: This PR is too stale; the last push date was more than 3 days ago. Please rebase and try again. You can rebase by leaving the following comment on this PR: Details for Dev Infra teamRaised by workflow job |
|
@pytorchmergebot merge |
Merge startedYour change will be merged once all checks pass (ETA 0-4 Hours). Learn more about merging in the wiki. Questions? Feedback? Please reach out to the PyTorch DevX Team |
Ref: #88906 (comment) Covers: - [x] adaptive_avg_pool1d - [x] adaptive_avg_pool2d - [x] adaptive_avg_pool3d - [x] adaptive_max_pool1d - [x] adaptive_max_pool2d - [x] adaptive_max_pool3d Pull Request resolved: #90924 Approved by: https://github.com/mruberry
Add bfloat16 support in `adaptive_{max, avg}_pool3d` as discussed in #88906 (comment).
Pull Request resolved: #89754
Approved by: https://github.com/jgong5, https://github.com/kit1980
Fixes #78868
TODO
cc: @kshitij12345 @ngimel