issue_comments

Table actions

2 rows where author_association = "NONE", issue = 1655290694 and user = 5534781 sorted by updated_at descending

✎ View and edit SQL

This data as json, CSV (advanced)

Suggested facets: created_at (date), updated_at (date)

user 1

  • leofang · 2 ✖

issue 1

  • `as_shared_dtype` converts scalars to 0d `numpy` arrays if chunked `cupy` is involved · 2 ✖

author_association 1

  • NONE · 2 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
1515600072 https://github.com/pydata/xarray/issues/7721#issuecomment-1515600072 https://api.github.com/repos/pydata/xarray/issues/7721 IC_kwDOAMm_X85aVjjI leofang 5534781 2023-04-20T01:50:58Z 2023-04-20T01:50:58Z NONE

Thanks, Justus, for expanding on this. It sounds to me the question is "how do we cast dtypes when multiple array libraries are participating in the same computation?" and I am not sure I am knowledgable enough to make any comment.

From the array API point of view, long long ago we decided that this is UB (undefined behavior), meaning it's completely up to each library to decide what to do. You can raise or come up with a special rule that you can make sense of.

It sounds like Xarray has some machinery to deal with this situation, but you'd rather prefer to not keep special-casing for a certain array library? Am I understanding it right?

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   `as_shared_dtype` converts scalars to 0d `numpy` arrays if chunked `cupy` is involved 1655290694
1510016072 https://github.com/pydata/xarray/issues/7721#issuecomment-1510016072 https://api.github.com/repos/pydata/xarray/issues/7721 IC_kwDOAMm_X85aAQRI leofang 5534781 2023-04-16T01:25:53Z 2023-04-16T01:25:53Z NONE

Sorry that I missed the ping, Jacob, but I'd need more context for making any suggestions/answers 😅 Is the question about why CuPy wouldn't return scalars?

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   `as_shared_dtype` converts scalars to 0d `numpy` arrays if chunked `cupy` is involved 1655290694

Advanced export

JSON shape: default, array, newline-delimited, object

CSV options: 

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]);