move device-specific teardown logic from training loop to accelerator

[awaelchli]

What does this PR do?

Follow up to #5743

on_train_end device-specific teardown should be handled by accelerator.
Makes training loop device agnostic

Before submitting

• Was this discussed/approved via a GitHub issue? (not for typos and docs)
• Did you read the contributor guideline, Pull Request section?
• Did you make sure your PR does only one thing, instead of bundling different changes together?
• Did you make sure to update the documentation with your changes? (if necessary)
• Did you write any new necessary tests? (not for typos and docs)
• Did you verify new and existing tests pass locally with your changes?
• Did you update the CHANGELOG? (not for typos, docs, test updates, or internal minor changes/refactorings)

PR review

Anyone in the community is free to review the PR once the tests have passed.
Before you start reviewing make sure you have read Review guidelines. In short, see the following bullet-list:

• Is this pull request ready for review? (if not, please submit in draft mode)
• Check that all items from Before submitting are resolved
• Make sure the title is self-explanatory and the description concisely explains the PR
• Add labels and milestones (and optionally projects) to the PR so it can be classified
• Check that target branch and milestone match!

Did you have fun?

Make sure you had fun coding 🙃

[codecov]

Codecov Report

Merging #5973 (b6e2fbd) into master (ae4dca9) will decrease coverage by 0%.
The diff coverage is 100%.

@@          Coverage Diff           @@
##           master   #5973   +/-   ##
======================================
- Coverage      90%     90%   -0%     
======================================
  Files         170     170           
  Lines       11789   11786    -3     
======================================
- Hits        10669   10637   -32     
- Misses       1120    1149   +29     

[tchaton]

LGTM !

[tchaton]

Should we do this for TPU too ?

[tchaton]

Nice cleaning !