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License: MIT License
Dockerfiles for dockerhub automated build.
License: MIT License
I have successfully installed this docker image on my computer which has a Titan X GPU. Also I have installed CUDA toolkit.
➜ ~ ls -la /dev | grep nvidia
crw-rw-rw- 1 root root 195, 0 7月 15 22:06 nvidia0
crw-rw-rw- 1 root root 195, 255 7月 15 22:06 nvidiactl
crw-rw-rw- 1 root root 246, 0 7月 20 11:14 nvidia-uvm
I run this image by the command given.
sudo docker run --name caffe -v /media/ksnzh/DATA/caffe-lstm:/workspace -p 8888:8888 -d --device /dev/nvidia0:/dev/nvidia0 --device /dev/nvidiactl:/dev/nvidiactl --device /dev/nvidia-uvm:/dev/nvidia-uvm drunkar/cuda-caffe-lstm-anaconda /bin/bash
sudo docker exec -it caffe bash
But when I try the coco_caption example, it had some errors.
I0720 12:28:20.358991 47 caffe.cpp:113] Use GPU with device ID 0
F0720 12:28:20.365886 47 common.cpp:131] Check failed: error == cudaSuccess (38 vs. 0) no CUDA-capable device is detected
*** Check failure stack trace: ***
@ 0x7f752f8819fd google::LogMessage::Fail()
@ 0x7f752f88389d google::LogMessage::SendToLog()
@ 0x7f752f8815ec google::LogMessage::Flush()
@ 0x7f752f8841be google::LogMessageFatal::~LogMessageFatal()
@ 0x7f752fd01596 caffe::Caffe::SetDevice()
@ 0x4066b2 train()
@ 0x404bd1 main
@ 0x7f752efb8ec5 (unknown)
@ 0x40524c (unknown)
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