Finish dataloader integration
# What does this PR do?

Follow up to https://github.com/huggingface/transformers/pull/24028, which removes the TPU-specific dataloader bits.

The `MpDeviceLoader` does already what `Trainer` was doing before, it's just wrapped:

```python
class MpDeviceLoader(object):
  """Wraps an existing PyTorch DataLoader with background data upload.

  This class should only be using with multi-processing data parallelism.

  Args:
    loader (:class:`torch.utils.data.DataLoader`): The PyTorch DataLoader to be
      wrapped.
    device (`torch.device`...): The device where the data has to be sent.
    kwargs: Named arguments for the `ParallelLoader` constructor.
  """

  def __init__(self, loader, device, **kwargs):
    self._loader = loader
    self._device = device
    self._parallel_loader_kwargs = kwargs

  def __iter__(self):
    parallel_loader = ParallelLoader(self._loader, [self._device],
                                     **self._parallel_loader_kwargs)
    return parallel_loader.per_device_loader(self._device)

  def __len__(self):
    return len(self._loader)
```

So the native Accelerate integration will work just fine

Fixes # (issue)


## Before submitting
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      Pull Request section?
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      to it if that's the case.
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      [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and
      [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?


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@sgugger
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