issue_comments
5 rows where author_association = "CONTRIBUTOR" and issue = 654135405 sorted by updated_at descending
This data as json, CSV (advanced)
Suggested facets: reactions, created_at (date), updated_at (date)
issue 1
- Add cupy support · 5 ✖
id | html_url | issue_url | node_id | user | created_at | updated_at ▲ | author_association | body | reactions | performed_via_github_app | issue |
---|---|---|---|---|---|---|---|---|---|---|---|
775284567 | https://github.com/pydata/xarray/issues/4212#issuecomment-775284567 | https://api.github.com/repos/pydata/xarray/issues/4212 | MDEyOklzc3VlQ29tbWVudDc3NTI4NDU2Nw== | tomchor 13205162 | 2021-02-08T16:50:38Z | 2021-02-08T16:50:38Z | CONTRIBUTOR | @jacobtomlinson Really glad someone's working on this! I'd be glad to help if I can (although I've never contributed to xarray and I don't know much about GPUs). I have some questions though. Do you have a specific purpose in mind for this? I ask because most other discussions I see related to this really just wanna do ML. However, there's a large user base (myself included) that would benefit immensely from just doing regular (non-machine-learning) operations with a GPU backend. Also, what's the status on the development? I see no comments after July 2020 and I'm hoping I can help get this back on track if needed! |
{ "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
Add cupy support 654135405 | |
660210572 | https://github.com/pydata/xarray/issues/4212#issuecomment-660210572 | https://api.github.com/repos/pydata/xarray/issues/4212 | MDEyOklzc3VlQ29tbWVudDY2MDIxMDU3Mg== | jacobtomlinson 1610850 | 2020-07-17T16:36:18Z | 2020-07-17T16:36:18Z | CONTRIBUTOR | I've written this comment a few times to try and not come across as confrontational. I'm not intending to be at all, so please don't take it that way 😅. Tone is hard in comments! I'm just trying to figure out how to proceed quickly. I've noticed a diverging theme that seems to be coming up in various conversations (see #3234 and #3245) around API design for alternative array implementations. It seems to boil down to whether an array implementation has 1st party or 3rd party support within xarray. For numpy and Dask they appear to be 1st party. They influence the main API of xarray and xarray contains baked in logic to create and work with them. The work on pint so far points towards it being 3rd party. While I'm sure some compatibility code has gone into xarray much of the logic lives out in an accessor library. Given that pint is extending the numpy API this makes sense. I initially started this work assuming that cupy would be added as 1st party type, given that it attempts to replicate the numpy API without addition. However I'm not sure this is the right stance. There are a few questions such as "should I think it would help with API design and speed here if a decision were to be made about cupy (and sparse) being 1st or 3rd party. Perhaps some core maintainers could weigh in here? |
{ "total_count": 1, "+1": 1, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
Add cupy support 654135405 | |
657151954 | https://github.com/pydata/xarray/issues/4212#issuecomment-657151954 | https://api.github.com/repos/pydata/xarray/issues/4212 | MDEyOklzc3VlQ29tbWVudDY1NzE1MTk1NA== | jthielen 3460034 | 2020-07-12T00:14:36Z | 2020-07-12T00:35:25Z | CONTRIBUTOR |
As far as I'd see it, the pieces to get this working are
and then finally testing xarray( pint( cupy )) works automatically from there. https://github.com/hgrecco/pint/issues/964 was deferred due to CI/testing concerns, so it will be great to see what @jacobtomlinson can come up with here for xarray, since hopefully at some point it would be transferable over to pint as well. |
{ "total_count": 1, "+1": 1, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
Add cupy support 654135405 | |
657135369 | https://github.com/pydata/xarray/issues/4212#issuecomment-657135369 | https://api.github.com/repos/pydata/xarray/issues/4212 | MDEyOklzc3VlQ29tbWVudDY1NzEzNTM2OQ== | dopplershift 221526 | 2020-07-11T21:48:17Z | 2020-07-11T21:48:17Z | CONTRIBUTOR | @jacobtomlinson Any idea how this would play with the work that's been going on for units here; I'm specifically wondering if xarray ( pint ( cupy )) would/could work. |
{ "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
Add cupy support 654135405 | |
656604704 | https://github.com/pydata/xarray/issues/4212#issuecomment-656604704 | https://api.github.com/repos/pydata/xarray/issues/4212 | MDEyOklzc3VlQ29tbWVudDY1NjYwNDcwNA== | jacobtomlinson 1610850 | 2020-07-10T10:27:29Z | 2020-07-10T10:27:29Z | CONTRIBUTOR | This PR for adding pint support is a useful reference. https://github.com/pydata/xarray/pull/3238 |
{ "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
Add cupy support 654135405 |
Advanced export
JSON shape: default, array, newline-delimited, object
CREATE TABLE [issue_comments] ( [html_url] TEXT, [issue_url] TEXT, [id] INTEGER PRIMARY KEY, [node_id] TEXT, [user] INTEGER REFERENCES [users]([id]), [created_at] TEXT, [updated_at] TEXT, [author_association] TEXT, [body] TEXT, [reactions] TEXT, [performed_via_github_app] TEXT, [issue] INTEGER REFERENCES [issues]([id]) ); CREATE INDEX [idx_issue_comments_issue] ON [issue_comments] ([issue]); CREATE INDEX [idx_issue_comments_user] ON [issue_comments] ([user]);
user 4