[
https://issues.apache.org/jira/browse/BEAM-14353?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17526101#comment-17526101
]
Andy Ye commented on BEAM-14353:
--------------------------------
Upon initial investigation, Pytorch has a 90-day release cycle, but it doesn't
seem that their changes really touch on the APIs that we use. (we do relatively
basic API calls to do basic reshaping of input data, passing input to the
model).
Maybe we can test the most recent release (pytorch 1.11.0), along with the last
minor version of the last X major versions (pytorch 1.10.2, pytorch 1.9.1,
pytorch 1.8.2, ...).
> Explore versions of pytorch to test in Tox
> ------------------------------------------
>
> Key: BEAM-14353
> URL: https://issues.apache.org/jira/browse/BEAM-14353
> Project: Beam
> Issue Type: Sub-task
> Components: sdk-py-core
> Reporter: Andy Ye
> Assignee: Andy Ye
> Priority: P2
> Labels: run-inference
>
> We test different minor versions for pandas because our special usage of
> pandas in the DataFrame API leads to breakages even between minor versions.
> In the case of pyarrow, every release is a major version, which is meant to
> communicate that the API can change
> ([https://arrow.apache.org/docs/format/Versioning.html]).
> We need to investigate if pytorch commonly make changes that will break us
> between minor versions.
> How will we keep this up to date as new version of pytorch come out?
--
This message was sent by Atlassian Jira
(v8.20.7#820007)
