fix: overfit_batches uses same batch for train and val

[ved1beta]

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What does this PR do?

This PR fixes the issue where overfit_batches=1 uses different batches for training and validation. It ensures that the same batch is used for both training and validation steps when overfitting.

Fixes #15021

Key Changes:

• Modified _resolve_overfit_batches to use the same batch for both training and validation
• Added comprehensive test to verify identical batches are used
• Added TensorFlow and TPU-related environment variables to test allowlist
• Fixed test failures related to environment variable leaks

Before submitting

• Was this discussed/agreed via a GitHub issue? (not for typos and docs)
  • Yes, discussed in Overfit batches parameter gives a validation batch #15021
• 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)
  • No documentation changes needed as this fixes a bug in existing functionality
• Did you write any new necessary tests? (not for typos and docs)
  • Yes, added test to verify identical batches are used
• Did you verify new and existing tests pass locally with your changes?
• Did you list all the breaking changes introduced by this pull request?
  • No breaking changes
• Did you update the CHANGELOG? (not for typos, docs, test updates, or minor internal changes/refactors)
  • Yes, will add entry for overfit_batches fix

PR review

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📚 Documentation preview 📚: https://pytorch-lightning--20731.org.readthedocs.build/en/20731/