#Vnc viewer for mac 教学 install#
#Vnc viewer for mac 教学 drivers#
#Vnc viewer for mac 教学 windows#

Volume drivers allow you to store volumes on remote hosts or cloud providers, to encrypt the contents of volumes, or to add other functionality.Ī new volume’s contents can be pre-populated by a container. Volumes can be more safely shared among multiple containers.

#Vnc viewer for mac 教学 windows#

Volumes work on both Linux and Windows containers. You can manage volumes using Docker CLI commands or the Docker API. Volumes are easier to back up or migrate than bind mounts. $ docker rm container-id # docker rmi imageĬtl-d or exit to quit container. $ docker run –gpus all -it ufoym/deepo:p圓6-cu100 bash # -it means interactive -rm means quit container after exit $ docker run –gpus all nvidia/cuda:10.0-base nvidia-smi Hello-world latest fce289e99eb9 14 months ago 1.84kB Ufoym/deepo all-jupyter-p圓6-cu100 cf60a305ba7b 6 months ago 10.9GB

Nvidia/cuda latest 9e47e9dfcb9a 3 months ago 2.83GB Ufoym/deepo latest 69b30aa9ad32 5 weeks ago 12.8GB Issue: File “mnist.py”, line 15, in from import input_data ModuleNotFoundError: No module named ‘’ Issue: File “/usr/local/lib/python3.6/dist-packages/torchvision/models/inception.py”, line 168, in module ‘torch.jit’ has no attribute ‘unused’ $ th (for torch 7) => deprecated, no use. Use pip list to check the framework version > import sonnet (AttributeError: module ‘tensorflow’ has no attribute ‘GraphKeys’) $ sudo docker run –gpus all -it -v /host/data:/data -v /hsot/config:/config ufoym/deepo:p圓6-cu100 bashĬreate a bash of the nvidia/deepo docker and check the framework is installed and version $ sudo docker run –gpus all -it ufoym/deepo:p圓6-cu100 bashĬreate a bash of the nvidia/deepo docker 並 mount host directory to docker (-v) $ sudo docker run –gpus all –rm ufoym/deepo:p圓6-cu100 nvidia-smi # -rm means remove container after exit $ sudo docker pull ufoym/deepo:all-jupyter-p圓6-cu100 If use old version (10.0), if 10.1 version ignoring the :p圓6-cu100 $ sudo docker run –gpus all nvidia/cuda:10.0-base nvidia-smiĭeepo 是一個含有許多Deep Learning Framework的docker image，使用這個image，可以讓我們快速的建置一個虛擬環境。 # Test nvidia-smi with the latest official CUDA image

#Vnc viewer for mac 教学 install#

$ sudo apt-get update & sudo apt-get install -y nvidia-container-toolkit $ curl -s -L $distribution/nvidia-docker.list | sudo tee /etc/apt//nvidia-docker.list $ sudo docker run hello-world 安裝 nvidia-docker $ sudo apt-get install docker-ce docker-ce-cli containerd.io

Dennis TS, Medium, “ 使用Docker來建置Deep Learning環境”.