Nvidia Theano码头码头图像不可用 [英] Nvidia Theano docker image not available
问题描述
尝试运行docker命令：
Trying to run docker command :
nvidia-docker run -d -p 8888:8888 -e PASSWORD="123abcChangeThis" theano_secure start-notebook.sh
# Then open your browser at http://HOST:8888
取自 https://github.com/nouiz/Theano-Docker
返回错误：
Error: image library/theano_secure:latest not found
显示theano_secure图像目前不可用？
Appears the theano_secure image is not currently available ?
搜索theano_secure：
Searching for theano_secure :
$ nvidia-docker search theano_secure:latest
NAME DESCRIPTION STARS OFFICIAL AUTOMATED
此命令的返回为空，因此图像不可用？
如果还有另外一种来自nvidia的Theano码头工作人员的图像？
The return of this command is empty so image is not available ? If so is there an alternative Theano docker image from nvidia ?
更新：
来源：
docker build -t theano_secure -f Dockerfile.0.8.X.jupyter.cuda.secure .
返回：
Err http://developer.download.nvidia.com Release.gpg
Unable to connect to developer.download.nvidia.com:http: [IP: 184.24.98.231 80]
和：
W: Failed to fetch http://archive.ubuntu.com/ubuntu/dists/trusty/InRelease
手动检查网址： http://developer.download.nvidia.com & http://archive.ubuntu.com/ubuntu/dists/trusty/InRelease都不可用。我应该用替代码头文件建立？
Manually checking URL's : http://developer.download.nvidia.com & http://archive.ubuntu.com/ubuntu/dists/trusty/InRelease are both not available. Should I build with alternative docker file ?
更新2：
我认为这个错误发生在 http://archive.ubuntu.com/ubuntu/dists/trusty/InRelease 不存在。不过 http://archive.ubuntu.com/ubuntu/dists/trusty/Release确实存在。
I think this error is occurring as http://archive.ubuntu.com/ubuntu/dists/trusty/InRelease does not exist. However http://archive.ubuntu.com/ubuntu/dists/trusty/Release does exist.
可以将docker修改为使用 http://archive.ubuntu.com/ubuntu/dists/trusty/Release ，而不是 http://archive.ubuntu.com/ubuntu/dists/trusty/InRelease ？
Can docker be modified to use http://archive.ubuntu.com/ubuntu/dists/trusty/Release instead of http://archive.ubuntu.com/ubuntu/dists/trusty/InRelease ?
操作系统版本：
lsb_release -a
No LSB modules are available.
Distributor ID: Ubuntu
Description: Ubuntu 14.04.4 LTS
Release: 14.04
Codename: trusty
更新3：
你应该首先建立docker，在nvidia-docker运行 / p>
"you are supposed to docker build first", before nvidia-docker run" I did try
docker build -t theano_secure -f Dockerfile.0.8.X.jupyter.cuda.secure .
返回：
Err http://developer.download.nvidia.com Release.gpg Unable to connect to developer.download.nvidia.com:http: [IP: 184.24.98.231 80]
我可以拉图像 docker pull kaixhin / theano 但是这不像Jupyter笔记本一样运行， c $ c> nvidia-docker run -it -p 8888：8888 tensorflow / tensorflow：latest-gpu 记录在 https://hub.docker.com/r/tensorflow/tensorflow/ 。似乎没有Docker Jupyter Th eano容器可用。
I can pull image docker pull kaixhin/theano but this does not run via Jupyter notebook in same way as nvidia-docker run -it -p 8888:8888 tensorflow/tensorflow:latest-gpu documented at https://hub.docker.com/r/tensorflow/tensorflow/ . There does not appear to be a docker Jupyter Theano container available.
如何通过Jupyter笔记本显示Docker实例kaixhin / theano？
How to expose the docker instance kaixhin/theano via Jupyter notebook ?
我试过： nvidia-docker run -d -p 8893：8893 -v --name theano2 kaixhin / theano start-notebook.sh 但收到错误：
docker: Error response from daemon: invalid header field value "oci runtime error: container_linux.go:247:
starting container process caused \"exec: \\\"start-notebook.sh\\\": executable file not found in $PATH\"\n".
修改 kaixhin / theano docker容器订单通过Jupyter笔记本曝光？
Modification of kaixhin/theano docker container in order expose it via Jupyter notebook ?
推荐答案
Error: image library/theano_secure:latest not found
因为 theano_secure 不喜欢 ubuntu ， centos ，它不是docker中心的官方存储库，所以你需要自己构建它。 >
Because theano_secure doesn't like ubuntu,centos, it is not official repository on docker hub, so you need to build it by yourself.
Err http://developer.download.nvidia.com Release.gpg Unable to connect to developer.download.nvidia.com:http: [IP: 184.24.98.231 80]
请先查看您的互联网连接， telnet 184.24.98.231 80 。
Please check your internet connection first, telnet 184.24.98.231 80.
也许你在一个有限的网络位置，尝试后面的代理这样做。您可能需要查看如何在代理服务器后构建映像。
Maybe you are in a limited network place, try behind a proxy to do this again. You may want take a look about how to build image behind a proxy.
这篇关于Nvidia Theano码头码头图像不可用的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！
