Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

GPU 使用率低 #20

Open
zhangxiann opened this issue Oct 29, 2021 · 7 comments
Open

GPU 使用率低 #20

zhangxiann opened this issue Oct 29, 2021 · 7 comments

Comments

@zhangxiann
Copy link

zhangxiann commented Oct 29, 2021

Hello,很感谢您实现的 3 个 Transformer。
我想提个小小的建议:您这里实现的 HengShuang 的 PointTransformer,内存占用率很高,但是 GPU 使用率太低了,每个 iteration 也很慢。请问可以提高吗?
image

@lvhuanhuan123
Copy link

请问,你有遇到过这个问题吗?怎么解决的?

omegaconf.errors.ConfigAttributeError: Missing key pretty
full_key: pretty
object_type=dict

Set the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.

@zhangxiann
Copy link
Author

请问,你有遇到过这个问题吗?怎么解决的?

omegaconf.errors.ConfigAttributeError: Missing key pretty full_key: pretty object_type=dict

Set the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.

这个一般是 Hydra 版本不对,请查看说明文档的 Hydra 版本进行安装

@18827555809
Copy link

我也是看到gpu的使用率很低 请问您解决了吗

@zhangxiann
Copy link
Author

我也是看到gpu的使用率很低 请问您解决了吗

已解决。
pointnet_util.py 中的所有 torch.cuda.empty_cache() 注释即可。
image

@18827555809
Copy link

18827555809 commented Nov 16, 2021 via email

@sw778
Copy link

sw778 commented Nov 12, 2022

你好,请问解决这个问题了吗?安装哪个版本的Hydra呢?

@tengfeixue-victor
Copy link

请问,你有遇到过这个问题吗?怎么解决的?

omegaconf.errors.ConfigAttributeError: Missing key pretty full_key: pretty object_type=dict

Set the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.

Run this export HYDRA_FULL_ERROR=1 command and then run .py files.
https://stackoverflow.com/questions/65376556/how-to-set-hydras-parameter-hydra-full-error

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

5 participants