InternalError:cudnn poolforward launch failed
weihua04 opened this issue · 12 comments
Hi, What kind of GPU are you using?-------- 原始邮件 --------发件人: weihua04 notifications@github.com日期: 2020年9月18日周五 08:12收件人: RenYang-home/OpenDVC OpenDVC@noreply.github.com抄送: Subscribed subscribed@noreply.github.com主 题: [RenYang-home/OpenDVC] InternalError:cudnn poolforward launch failed (#5)
i have installed tf-gpu 12.0, cuda9, tf-compression 10.0 , and when used the code below for test:
python OpenDVC_test_video.py --path BasketballPass --model PSNR --metric PSNR --l 1024
the information is :
![Uploading 5074244104368395475.jpg…]
does anyone has good idea to solve it?—You are receiving this because you are subscribed to this thread.Reply to this email directly, view it on GitHub, or unsubscribe.
GeForce RTX 2080
I am not sure whether it is because of insufficient memory. Is there an
error if running on CPU?
…
CPU is ok, I have tried tf 12.0, but tf-gpu12.0 have problem
Maybe try on a GPU with larger memory (e.g., 12GB or more).
I haven't met that problem, so I am not sure what's wrong it is.
Maybe try on a GPU with larger memory (e.g., 12GB or more).
I haven't met that problem, so I am not sure what's wrong it is.
you run the test.py in docker or the host machine?
thanks for reply. I think maybe it's the version problem, Could u tell me what's your minor version of CUDNN CUDA, and tensorflow? thank u very much.
mine:
CUDA: 9.0.176_384.81
CUDNN: V7.1.4
tensorflow: 1.12.0
I meet the same problem.
thanks for reply. I think maybe it's the version problem, Could u tell me what's your minor version of CUDNN CUDA, and tensorflow? thank u very much.
mine:
CUDA: 9.0.176_384.81
CUDNN: V7.1.4
tensorflow: 1.12.0
Mine is:
CUDA: 9.0, V9.0.176
CUDNN:
#define CUDNN_MAJOR 7
#define CUDNN_MINOR 6
#define CUDNN_PATCHLEVEL 0
#define CUDNN_VERSION (CUDNN_MAJOR * 1000 + CUDNN_MINOR * 100 + CUDNN_PATCHLEVEL)
tensorflow: 1.12.0
I meet the same problem.
I solved the problem by change version of cudnn,my environment is in docker ,
the environment of docker is :
CUDA: 9
CUDNN: 10.0 V7.4.2
I meet the same problem.
I solved the problem by change version of cudnn,my environment is in docker ,
the environment of docker is :
CUDA: 9
CUDNN: 10.0 V7.4.2
Happy to hear that :-)