Support set non_blocking=True when move data from cpu to gpu
Author: Hukongtao
Pull request: yes

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Fixes [36384](https://github.com/huggingface/transformers/issues/36384)

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Comments:
cc @muellerzr @SunMarc 

Could you try to set `non_blocking` using `accelerator_config` in `TrainingArguments` ? This should be the dataloader job to put the data on the right device. 

> Could you try to set `non_blocking` using `accelerator_config` in `TrainingArguments` ? This should be the dataloader job to put the data on the right device.

Done. can you review it again?

I mean to try your script with `non_blocking=True` using `accelerator_config` when you create the `TrainingArguments` object, not use modify the kwargs. 

> I mean to try your script with `non_blocking=True` using `accelerator_config` when you create the `TrainingArguments` object, not use modify the kwargs.

But there is no way to pass non_blocking parameters to **kwargs here?
https://github.com/huggingface/transformers/blob/v4.49.0/src/transformers/trainer.py#L3625-L3631

I'm just suggesting for now to set the `accelerator_config` attribute in `TrainingArguments` when you set the trainer. In the AcceleratorConfig class, you can set `non_blocking` to `True`. https://github.com/huggingface/transformers/blob/222505c7e4d08da9095d12ddb72fb653f4b6da33/src/transformers/trainer_pt_utils.py#L1212

Just wanted to check if this could potentially solve your issue without having to modify the **kwargs

LMK if you had time to check, otherwise, i'll add a tag to the issue so that someone else could take a look