Split pandas pytests to prepare for GPU vs CPU metrics reporting

[galipremsagar]

Description

This PR splits the pandas tests job into 3 groups using pytest-split. The purpose of this PR is to reduce the runtime and avoid hangs being faced in running all the tests in one job along with profiling that will detect and extract metrics of GPU vs CPU execution in: #16754

As part of splitting the tests into separate groups we need .test_durations file which is 25 MB, hence I've added this file using git lfs.

Checklist

• I am familiar with the Contributing Guidelines.
• New or existing tests cover these changes.
• The documentation is up to date with these changes.

[bdice]

There's no PR description or linked issue so I can't tell what you aim to accomplish in this. We should find a solution that does not require git LFS.

[bdice]

Is this change intentional? Why? I strongly oppose introducing LFS requirements to this repository.

[galipremsagar]

Responded here: #16743 (comment)

[galipremsagar]

There's no PR description or linked issue so I can't tell what you aim to accomplish in this. We should find a solution that does not require git LFS.

@bdice I just updated the PR title. My apologies for hitting ready for review when it isn't. Now it is :)

The reason for using git LFS is the file size. I can move the file to s3 but this file will require future updates if the test suite changes drastically and I wanted to avoid having to ask ops to upload a file manually. Do you see any downsides for using GIT LFS ? I followed instructions from ops as mentioned here: https://docs.rapids.ai/resources/git/#large-files-and-git

[bdice]

Please remove pytest-split if we are using pytest-shard instead.

Please run all shards in one worker (serially) to avoid paying for the job setup cost on multiple GPU workers (scarce resources). Then we don't need any LFS, S3, or .gitattributes changes.

[galipremsagar]

@bdice This PR is not needed anymore as #16739 has all the necessary changes needed.