🚨🚨🚨 Replace DataLoader logic for Accelerate in Trainer, remove unneeded tests 🚨🚨🚨
# What does this PR do?

This PR:
- Guts the internals for the `DataLoader` in all basic distributed fashions (replacing `pl.Loader` for TPU coming in a follow-up PR) to replace it with `accelerator.prepare`
- Removes **two** tests that were deemed unnecessary
  - Test 1 removed: `tests/trainer/test_trainer.py::TrainerIntegrationTest::test_sampler_seed`, deemed to no longer be necessary to reset the seed, as Accelerate's dataloader setup doesn't need any extra help when iterating/loading back in the seed, regardless of the torch version
  - Test 2 removed: `tests/trainer/test_trainer.py::TrainerIntegrationTest::test_training_finite_iterable_dataset`, as with Accelerate's new sampler for `IterableDataset` we'll actually catch if it's `None` and raise an error, a new test will be made + clear error message on the `Accelerate` side, with a test added to `Trainer` afterwards. 
- Modifies two tests to use the proper attribute: Accelerator's `DataLoaders` all have `total_batch_size` rather than `batch_size`
  - `test_train_and_eval_dataloaders` and `test_data_is_not_parallelized_when_model_is_parallel`


Fixes # (issue)


## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
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- [ ] Did you write any new necessary tests?


## Who can review?

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@sgugger @pacman100 
_The documentation is not available anymore as the PR was closed or merged._<|||||>Great PR, currently this is breaking my custom collate_fn in the dataloader, still trying to understand why that is. First assumption might be due to multiprocessing?<|||||>@franz101 please open an issue with a reproducer of what you are trying to do so we can help :)