docker下最新搭建anaconda3/cuda(cudnn)/tensorflow

1.create container

docker run --name tf12 -it ubuntu /bin/bash

2.install anaconda

[260254@localhost download]$ sudo docker cp Anaconda3-5.3.1-Linux-x86_64.sh 0d5:/root
root@0d580c903134:/# bash Anaconda3-5.3.1-Linux-x86_64.sh 

install opencv

3.inquire gpu

[260254@localhost ~]$ lspci | grep -i vga
01:00.0 VGA compatible controller: NVIDIA Corporation GM107GL [Quadro K620] (rev a2)
[260254@localhost ~]$ lspci -v -s 01:00.0
01:00.0 VGA compatible controller: NVIDIA Corporation GM107GL [Quadro K620] (rev a2) (prog-if 00 [VGA controller])
	Subsystem: NVIDIA Corporation Device 1098
	Physical Slot: 1
	Flags: bus master, fast devsel, latency 0, IRQ 125
	Memory at de000000 (32-bit, non-prefetchable) [size=16M]
	Memory at c0000000 (64-bit, prefetchable) [size=256M]
	Memory at d0000000 (64-bit, prefetchable) [size=32M]
	I/O ports at e000 [size=128]
	Expansion ROM at df000000 [disabled] [size=512K]
	Capabilities: <access denied>
	Kernel driver in use: nouveau
	Kernel modules: nouveau

4.install cuda(cudnn)

root@0d580c903134:~# apt-get update && apt-get install wget -y --no-install-recommends
root@0d580c903134:~# wget "http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-repo-ubuntu1804_10.0.130-1_amd64.deb"
root@0d580c903134:~# dpkg -i cuda-repo-ubuntu1804_10.0.130-1_amd64.deb
root@0d580c903134:~# apt-get install gnupg
root@0d580c903134:~# apt-key adv --fetch-keys http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/7fa2af80.pub
root@0d580c903134:~# apt-get update
root@0d580c903134:~# CUDNN_URL="http://developer.download.nvidia.com/compute/redist/cudnn/v7.4/cudnn-10.0-linux-x64-v7.4.2.24.tgz"
root@0d580c903134:~# wget ${CUDNN_URL}
root@0d580c903134:~# tar -xzf cudnn-10.0-linux-x64-v7.4.2.24.tgz -C /usr/local
root@0d580c903134:~# rm cudnn-10.0-linux-x64-v7.4.2.24.tgz && ldconfig

5.install tensorflow

root@0d580c903134:~# pip install tensorflow-gpu