# Minimal changes for using DataParallel?

**URL:** <https://discuss.huggingface.co/t/minimal-changes-for-using-dataparallel/86379>\
**Category:** Beginners\
**Created:** [May 12, 2024, 7:56pm UTC](https://discuss.huggingface.co/t/minimal-changes-for-using-dataparallel/86379 "2024-05-12T19:56:28Z")\
**Posts on this page:** 2\
**Page:** 1

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**Author:** ![gpjt](https://avatars.discourse-cdn.com/v4/letter/g/9de053/32.png) [@gpjt](https://discuss.huggingface.co/u/gpjt)\
**Post date:** [May 12, 2024, 7:56pm UTC](https://discuss.huggingface.co/t/minimal-changes-for-using-dataparallel/86379/1 "2024-05-12T19:56:28Z")

</div>

Hi all! I’m playing around with a bit of fine-tuning, just to get a basic understanding of how it works. I’ve successfully done some simple single-GPU tunes, and my next step is to try multi-GPU training. I’ve read [the help page on efficient training on multiple GPUs](https://huggingface.co/docs/transformers/en/perf_train_gpu_many), and was originally planning to do the train using Distributed DataParallel, but at this stage I want to run the training in a notebook, so I can’t easily use the launcher for that. A ChatGPT conversation gave me the belief that I could stay in the notebook (at the loss of some efficiency) by using DataParallel.

From the same ChatGPT session, I got the impression that using DP was as simple as wrapping my model in `DataParallel`:

```auto
from torch.nn import DataParallel

parallel_model = DataParallel(model).cuda()

```

…and then passing `parallel_model` into the trainer. However, that leads to an `IndexError` suggesting that somehow the dataset isn’t getting through to the trainer. You can see the full code and the error in [this notebook](https://github.com/gpjt/fine-tune-2024-04/blob/main/third-0.5b-fine-tune-with-dp.ipynb). The same code successfully runs the training if `model` is passed in to the `Trainer` instead of `parallel_model`.

Is there a simple way to use DataParallel in a notebook like this? Or is this a blind alley I should abandon, and focus on DDP instead?

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<div class="post-metadata">

**Author:** ![gpjt](https://avatars.discourse-cdn.com/v4/letter/g/9de053/32.png) [@gpjt](https://discuss.huggingface.co/u/gpjt)\
**Post date:** [June 17, 2024, 7:22pm UTC](https://discuss.huggingface.co/t/minimal-changes-for-using-dataparallel/86379/2 "2024-06-17T19:22:26Z")

</div>

Update for anyone else with the same problems; I’m now 99% sure it was a ChatGPT hallucination. After much digging, it doesn’t appear to be possible to simply wrap a model in `DataParallel` and then use it with the `Trainer`.

I wound up changing the notebook so that it was a regular script, then running it with

```
torchrun --nproc_per_node=2 script.py

```

…and it worked fine.

My takeaway is that it doesn’t seem possible to do multi-GPU training inside a notebook, which is fine! I can build a simple model in a notebook then switch to using a script when I want to scale it up.