[BUG] CUDA Out of Memory when eval model.

[Crystalxd]

Required prerequisites

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System information

conda environment torch=2.0.1 transformers=4.29.2 ...

Problem description

I used A100(80G) to run the evaluate_zh.py script for evaluating baichuan model, but it occupied abundant GPU memory up to overflow. Then I found the model loaded without eval mode, meanwhile, it inferred without no_grad.

Reproducible example code

The Python snippets:

[https://github.com/baichuan-inc/Baichuan-7B/blob/6f3ef4633a90c2d8a3e0763d0dec1b8dc11588f5/evaluation/evaluate_zh.py#L97C13-L97C13](url)
self.model = model.eval()

https://github.com/baichuan-inc/Baichuan-7B/blob/6f3ef4633a90c2d8a3e0763d0dec1b8dc11588f5/evaluation/evaluate_zh.py#L103
Add on this line:
@torch.inference_mode()

Command lines:

Extra dependencies:

Steps to reproduce:

1. 2. 3.

Traceback

No response

Expected behavior

No response

Additional context

No response

Checklist

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[Guanze-Chen]

Thank you. It works!!!

[ICanFlyGFC]

Thanks!

[Guanze-Chen]

您的邮件已经收到，会尽快回复您

[Young-X]

我在训练模型过程中，脚本默认使用gpu0，怎么调换到gpu1上面？

[Guanze-Chen]

您的邮件已经收到，会尽快回复您