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

Pretrained Model Information #6

Open
fabr0d opened this issue Jul 20, 2020 · 1 comment
Open

Pretrained Model Information #6

fabr0d opened this issue Jul 20, 2020 · 1 comment

Comments

@fabr0d
Copy link

fabr0d commented Jul 20, 2020

Dear author, could you provide us with information about the training that was done to obtain the pretrained model(ResidualGRUNet), such as the configuration used, the hardware, etc.
Thanks in advance.

@heromanba
Copy link
Owner

heromanba commented Jul 22, 2020

Hi, sorry to reply late.

For configuration,
you can refer to this file https://github.com/heromanba/3D-R2N2-PyTorch/blob/master/experiments/scripts/res_gru_net.sh

For hardware,

+-----------------------------------------------------------------------------+
| NVIDIA-SMI 430.50       Driver Version: 430.50       CUDA Version: 10.1     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|===============================+======================+======================|
| 0  GeForce RTX 2060super  Off | 00000000:01:00.0  On |                  N/A |
|  0%   44C    P8    13W / 175W |    141MiB /  7977MiB |      3%      Default |
+-------------------------------+----------------------+----------------------+

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

2 participants