Profile dataloader initialization in FitLoop and update outdated docs

[yuxin00j]

What does this PR do?

Fixes #21771
This PR addresses the issue where the PyTorch Lightning profiler fails to capture the latency spike during dataloader worker initialization and early prefetching.

Specifically, this PR:

1. Adds a profiling hook: Wraps iter(self._data_fetcher) in _FitLoop.setup_data() with the action name "setup_train_dataloader". This ensures that worker spawn and initialization times appear in the standard Fit Profiler Report.
2. Updates documentation: Removes the outdated reference to get_train_batch (which was deprecated during the 2021 loops refactor) in the AdvancedProfiler documentation and replaces it with setup_train_dataloader.
3. Adds unit tests: Includes a new test test_setup_train_dataloader_profiled_actions using BoringModel to assert that the "setup_train_dataloader" action is correctly recorded in profiler.profiled_actions.

• Was this discussed/agreed 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 list all the breaking changes introduced by this pull request?
• Did you update the CHANGELOG? (not for typos, docs, test updates, or minor internal changes/refactors)

PR review

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

Reviewer checklist

• 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