AssertionError: The dataloader must be a `torch_xla.distributed.parallel_loader.MpDeviceLoader`
Author: moficodes
Pull request: no

### System Info

`transformer`: `v4.39.3`
`torch`: `2.3.0`
`torch_xla`: `2.3.0+gite385c2f`
`peft`: `0.10.0`
`trl`: `0.8.1`

Following the discussion from https://github.com/huggingface/transformers/issues/29659 where @shub-kris provided a script in comment https://github.com/huggingface/transformers/issues/29659#issuecomment-2006524634 

Ran into this issue 

```bash
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
I0000 00:00:1712436980.191572       7 pjrt_api.cc:100] GetPjrtApi was found for tpu at /usr/local/lib/python3.10/site-packages/torch_xla/lib/libtpu.so
I0000 00:00:1712436980.191657       7 pjrt_api.cc:79] PJRT_Api is set for device type tpu
I0000 00:00:1712436980.191663       7 pjrt_api.cc:146] The PJRT plugin has PJRT API version 0.40. The framework PJRT API version is 0.40.
/usr/local/lib/python3.10/site-packages/torch_xla/core/xla_model.py:104: UserWarning: `devkind` argument is deprecated and will be removed in a future release.
  warnings.warn("`devkind` argument is deprecated and will be removed in a "
Generating train split: 102 examples [00:00, 452.42 examples/s]
/usr/local/lib/python3.10/site-packages/trl/trainer/sft_trainer.py:317: UserWarning: You passed a tokenizer with `padding_side` not equal to `right` to the SFTTrainer. This might lead to some unexpected behaviour due to overflow issues when training a model in half-precision. You might consider adding `tokenizer.padding_side = 'right'` to your code.
  warnings.warn(
/usr/local/lib/python3.10/site-packages/accelerate/accelerator.py:436: FutureWarning: Passing the following arguments to `Accelerator` is deprecated and will be removed in version 1.0 of Accelerate: dict_keys(['dispatch_batches', 'split_batches', 'even_batches', 'use_seedable_sampler']). Please pass an `accelerate.DataLoaderConfiguration` instead: 
dataloader_config = DataLoaderConfiguration(dispatch_batches=None, split_batches=False, even_batches=True, use_seedable_sampler=True)
  warnings.warn(
Traceback (most recent call last):
  File "//demo.py", line 81, in <module>
    train()
  File "//demo.py", line 63, in train
    trainer.train()
  File "/usr/local/lib/python3.10/site-packages/trl/trainer/sft_trainer.py", line 360, in train
    output = super().train(*args, **kwargs)
  File "/usr/local/lib/python3.10/site-packages/transformers/trainer.py", line 1780, in train
    return inner_training_loop(
  File "/usr/local/lib/python3.10/site-packages/transformers/trainer.py", line 1811, in _inner_training_loop
    train_dataloader = tpu_spmd_dataloader(train_dataloader)
  File "/usr/local/lib/python3.10/site-packages/transformers/integrations/tpu.py", line 24, in tpu_spmd_dataloader
    assert isinstance(
AssertionError: The dataloader must be a `torch_xla.distributed.parallel_loader.MpDeviceLoader`.
```

It asks to pass a `accelerate.DataLoaderConfiguration` but I am not sure where to do it. Accelerate is being called internally by transformers somewhere. 

### Who can help?

@ArthurZucker 
@muellerz 
@shub-kris 

### Information

- [ ] The official example scripts
- [X] My own modified scripts

### Tasks

- [ ] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [ ] My own task or dataset (give details below)

### Reproduction

I ran the example in TPU V4 on Kubernetes. It was 2x2x4 TPU Device.

The `Dockerfile` to build the image is as follows where `demo.py` was the script from the issue-comment.

```
FROM us-central1-docker.pkg.dev/tpu-pytorch-releases/docker/xla:nightly_3.10_tpuvm_20240229

RUN pip install -U transformers trl datasets peft

COPY . .

CMD python demo.py
```

### Expected behavior

Model finetunes and prints output.

Comments:
Hi @moficodes, thanks for raising this issue! 

I think you've tagged the wrong Mu(e)ller - cc'ing in @muellerzr @pacman100 

I have encountered a similar issue. I think it is caused by accelerate

 https://github.com/huggingface/accelerate/blob/b8c85839531ded28efb77c32e0ad85af2062b27a/src/accelerate/state.py#L257
 
 This code resets self.distributed_type to DistributedType.NO and as a result MpDeviceLoader is not returned by Accelerate
 
 https://github.com/huggingface/accelerate/blob/b8c85839531ded28efb77c32e0ad85af2062b27a/src/accelerate/data_loader.py#L976

 
 

Yes indeed, this should be fixed by the patch release we just made. Can you try upgrading accelerate and see? (0.29.2)

This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

Please note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md) are likely to be ignored.