安装Docker
查看系统版本
liuhz@ubuntu-SYS-7049GP-TRTC-RI017:~$ lsb_release -a
No LSB modules are available.
Distributor ID: Ubuntu
Description: Ubuntu 20.04.3 LTS
Release: 20.04
Codename: focal
官网的安装方法 https://docs.docker.com/engine/install/ubuntu/
sudo apt-get update
sudo apt-get install \
ca-certificates \
curl \
gnupg \
lsb-release
sudo apt-get install \
apt-transport-https \
ca-certificates \
curl \
gnupg-agent \
software-properties-common
sudo apt-get install apt-transport-https ca-certificates curl gnupg-agent gnupg lsb-release software-properties-common
添加 docker 官方 GPG 密钥
curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add -
curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo gpg --dearmor -o /usr/share/keyrings/docker-archive-keyring.gpg
使用下面的命令来设置稳定版本库。要添加nightly 版本库或测试版本库，请在下面的命令中的 stable 后面加上 nightly 或 test （或两者）。了解nightly和test通道。
echo \
"deb [arch=$(dpkg --print-architecture) signed-by=/usr/share/keyrings/docker-archive-keyring.gpg] https://download.docker.com/linux/ubuntu \
$(lsb_release -cs) stable" | sudo tee /etc/apt/sources.list.d/docker.list > /dev/null
echo "deb [arch=$(dpkg --print-architecture) signed-by=/usr/share/keyrings/docker-archive-keyring.gpg] https://download.docker.com/linux/ubuntu $(lsb_release -cs) stable" | sudo tee /etc/apt/sources.list.d/docker.list > /dev/null
sudo add-apt-repository "deb [arch=amd64] https://download.docker.com/linux/ubuntu $(lsb_release -cs) stable"
安装Docker Engine
sudo apt-get update
sudo apt-get install docker-ce docker-ce-cli containerd.io docker-compose-plugin
sudo apt-get update
sudo apt-get install docker-ce docker-ce-cli containerd.io
验证Docker是否安装成功
liuhz@ubuntu-SYS-7049GP-TRTC-RI017:~$ sudo docker run hello-world
Unable to find image 'hello-world:latest' locally
latest: Pulling from library/hello-world
2db29710123e: Pull complete
Digest: sha256:10d7d58d5ebd2a652f4d93fdd86da8f265f5318c6a73cc5b6a9798ff6d2b2e67
Status: Downloaded newer image for hello-world:latest
Hello from Docker!
This message shows that your installation appears to be working correctly.
To generate this message, Docker took the following steps:
1. The Docker client contacted the Docker daemon.
2. The Docker daemon pulled the "hello-world" image from the Docker Hub.
(amd64)
3. The Docker daemon created a new container from that image which runs the
executable that produces the output you are currently reading.
4. The Docker daemon streamed that output to the Docker client, which sent it
to your terminal.
To try something more ambitious, you can run an Ubuntu container with:
$ docker run -it ubuntu bash
Share images, automate workflows, and more with a free Docker ID:
https://hub.docker.com/
For more examples and ideas, visit:
https://docs.docker.com/get-started/
liuhz@ubuntu-SYS-7049GP-TRTC-RI017:~$ docker
Usage: docker [OPTIONS] COMMAND
A self-sufficient runtime for containers
Options:
--config string Location of client config files (default "/home/liuhz/.docker")
-c, --context string Name of the context to use to connect to the daemon (overrides DOCKER_HOST env var and
default context set with "docker context use")
-D, --debug Enable debug mode
-H, --host list Daemon socket(s) to connect to
-l, --log-level string Set the logging level ("debug"|"info"|"warn"|"error"|"fatal") (default "info")
--tls Use TLS; implied by --tlsverify
--tlscacert string Trust certs signed only by this CA (default "/home/liuhz/.docker/ca.pem")
--tlscert string Path to TLS certificate file (default "/home/liuhz/.docker/cert.pem")
--tlskey string Path to TLS key file (default "/home/liuhz/.docker/key.pem")
--tlsverify Use TLS and verify the remote
-v, --version Print version information and quit
Management Commands:
app* Docker App (Docker Inc., v0.9.1-beta3)
builder Manage builds
buildx* Docker Buildx (Docker Inc., v0.8.1-docker)
compose* Docker Compose (Docker Inc., v2.3.3)
config Manage Docker configs
container Manage containers
context Manage contexts
image Manage images
manifest Manage Docker image manifests and manifest lists
network Manage networks
node Manage Swarm nodes
plugin Manage plugins
scan* Docker Scan (Docker Inc., v0.17.0)
secret Manage Docker secrets
service Manage services
stack Manage Docker stacks
swarm Manage Swarm
system Manage Docker
trust Manage trust on Docker images
volume Manage volumes
Commands:
attach Attach local standard input, output, and error streams to a running container
build Build an image from a Dockerfile
commit Create a new image from a container's changes
cp Copy files/folders between a container and the local filesystem
create Create a new container
diff Inspect changes to files or directories on a container's filesystem
events Get real time events from the server
exec Run a command in a running container
export Export a container's filesystem as a tar archive
history Show the history of an image
images List images
import Import the contents from a tarball to create a filesystem image
info Display system-wide information
inspect Return low-level information on Docker objects
kill Kill one or more running containers
load Load an image from a tar archive or STDIN
login Log in to a Docker registry
logout Log out from a Docker registry
logs Fetch the logs of a container
pause Pause all processes within one or more containers
port List port mappings or a specific mapping for the container
ps List containers
pull Pull an image or a repository from a registry
push Push an image or a repository to a registry
rename Rename a container
restart Restart one or more containers
rm Remove one or more containers
rmi Remove one or more images
run Run a command in a new container
save Save one or more images to a tar archive (streamed to STDOUT by default)
search Search the Docker Hub for images
start Start one or more stopped containers
stats Display a live stream of container(s) resource usage statistics
stop Stop one or more running containers
tag Create a tag TARGET_IMAGE that refers to SOURCE_IMAGE
top Display the running processes of a container
unpause Unpause all processes within one or more containers
update Update configuration of one or more containers
version Show the Docker version information
wait Block until one or more containers stop, then print their exit codes
Run 'docker COMMAND --help' for more information on a command.
To get more help with docker, check out our guides at https://docs.docker.com/go/guides/
查看Docker 版本
liuhz@ubuntu-SYS-7049GP-TRTC-RI017:~$ docker -v
Docker version 20.10.14, build a224086
安装nvidia-docker
https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/install-guide.html#docker
运行 NVIDIA Container Toolkit 的先决条件列表如下所述：
- 内核版本 > 3.10 的 GNU/Linux x86_64
liuhz@ubuntu-SYS-7049GP-TRTC-RI017:~$ cat /proc/version
Linux version 5.13.0-39-generic (buildd@lcy02-amd64-080) (gcc (Ubuntu 9.4.0-1ubuntu1~20.04.1) 9.4.0, GNU ld (GNU Binutils for Ubuntu) 2.34) #44~20.04.1-Ubuntu SMP Thu Mar 24 16:43:35 UTC 2022
liuhz@ubuntu-SYS-7049GP-TRTC-RI017:~$ uname -r
5.13.0-39-generic
- Docker >= 19.03（推荐，但某些发行版可能包含旧版本的 Docker。支持的最低版本为 1.12）
查看Docker 版本
liuhz@ubuntu-SYS-7049GP-TRTC-RI017:~$ docker -v
Docker version 20.10.14, build a224086
架构 >= Kepler（或计算能力 3.0）的 NVIDIA GPU
NVIDIA Linux 驱动程序>= 418.81.07（请注意，不支持较旧的驱动程序版本或分支。）
设置 Docker¶
Ubuntu 上的 Docker-CE 可以使用 Docker 的官方便利脚本进行设置：
curl https://get.docker.com | sh && sudo systemctl --now enable docker
设置 NVIDIA 容器工具包¶
设置包存储库和 GPG 密钥：
distribution=$(. /etc/os-release;echo $ID$VERSION_ID) \
&& curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg \
&& curl -s -L https://nvidia.github.io/libnvidia-container/$distribution/libnvidia-container.list | \
sed 's#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#g' | \
sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list
要访问experimental功能和访问候选版本，您可能需要将experimental分支添加到存储库列表中：
curl -s -L https://nvidia.github.io/libnvidia-container/experimental/$distribution/libnvidia-container.list | \
sed 's#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#g' | \
sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list
更新包列表后安装nvidia-docker2包（和依赖项）：
sudo apt-get update
sudo apt-get install -y nvidia-docker2
设置默认运行时后重启 Docker 守护进程完成安装：
sudo systemctl restart docker
此时，可以通过运行基本 CUDA 容器来测试工作设置：
sudo docker run --rm --gpus all nvidia/cuda:11.0-base nvidia-smi
liuhz@ubuntu-SYS-7049GP-TRTC-RI017:~$ sudo docker run --rm --gpus all nvidia/cuda:11.0-base nvidia-smi
Unable to find image 'nvidia/cuda:11.0-base' locally
11.0-base: Pulling from nvidia/cuda
54ee1f796a1e: Pull complete
f7bfea53ad12: Pull complete
46d371e02073: Pull complete
b66c17bbf772: Pull complete
3642f1a6dfb3: Pull complete
e5ce55b8b4b9: Pull complete
155bc0332b0a: Pull complete
Digest: sha256:774ca3d612de15213102c2dbbba55df44dc5cf9870ca2be6c6e9c627fa63d67a
Status: Downloaded newer image for nvidia/cuda:11.0-base
Wed Apr 27 12:49:08 2022
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 470.103.01 Driver Version: 470.103.01 CUDA Version: 11.4 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 NVIDIA GeForce ... Off | 00000000:18:00.0 Off | N/A |
| 81% 73C P2 334W / 350W | 23868MiB / 24268MiB | 100% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 1 NVIDIA GeForce ... Off | 00000000:3B:00.0 Off | N/A |
| 73% 70C P2 232W / 350W | 23631MiB / 24268MiB | 100% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 2 NVIDIA GeForce ... Off | 00000000:5E:00.0 Off | N/A |
| 59% 63C P2 262W / 350W | 22753MiB / 24268MiB | 99% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 3 NVIDIA GeForce ... Off | 00000000:86:00.0 Off | N/A |
| 59% 62C P2 198W / 350W | 15465MiB / 24268MiB | 48% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
+-----------------------------------------------------------------------------+
下载自定义的Docker
liuhz@ubuntu-SYS-7049GP-TRTC-RI017:~$ sudo docker pull pytorch/pytorch:1.7.0-cuda11.0-cudnn8-devel
[sudo] liuhz 的密码：
1.7.0-cuda11.0-cudnn8-devel: Pulling from pytorch/pytorch
171857c49d0f: Already exists
419640447d26: Already exists
61e52f862619: Already exists
2a93278deddf: Already exists
c9f080049843: Already exists
8189556b2329: Already exists c306a0c97a55: Pull complete
4a9478bd0b24: Pull complete
19a76c31766d: Pull complete
1d18e0f6b7f6: Pull complete
d8015a90b67c: Pull complete
211a7eed3486: Pull complete
Digest: sha256:837e6964e5db6e5b35f4d5e98e9cac073ab757766039b9503f39c14beafb0e98
Status: Downloaded newer image for pytorch/pytorch:1.7.0-cuda11.0-cudnn8-devel
docker.io/pytorch/pytorch:1.7.0-cuda11.0-cudnn8-devel
修改Docker路径
创建或修改 /etc/docker/daemon.json
{
"runtimes": {
"nvidia": {
"path": "nvidia-container-runtime",
"runtimeArgs": []
}
},
"registry-mirrors": [
"https://1nj0zren.mirror.aliyuncs.com",
"https://docker.mirrors.ustc.edu.cn",
"http://f1361db2.m.daocloud.io",
"https://registry.docker-cn.com"],
"data-root": "/home/liuhz/Docker/docker"
}
sudo systemctl daemon-reload
sudo systemctl restart docker
权限问题加入docker用户组
liuhz@ubuntu-SYS-7049GP-TRTC-RI017:~$ docker images
Got permission denied while trying to connect to the Docker daemon socket at unix:///var/run/docker.sock: Get "http://%2Fvar%2Frun%2Fdocker.sock/v1.24/images/json": dial unix /var/run/docker.sock: connect: permission denied
liuhz@ubuntu-SYS-7049GP-TRTC-RI017:~$ sudo docker images
[sudo] liuhz 的密码：
REPOSITORY TAG IMAGE ID CREATED SIZE
hello-world latest feb5d9fea6a5 7 months ago 13.3kB
nvidia/cuda 11.0-base 2ec708416bb8 20 months ago 122MB
liuhz@ubuntu-SYS-7049GP-TRTC-RI017:~$ sudo groupadd docker
groupadd：“docker”组已存在
liuhz@ubuntu-SYS-7049GP-TRTC-RI017:~$ sudo gpasswd -a liuhz docker
正在将用户“liuhz”加入到“docker”组中
liuhz@ubuntu-SYS-7049GP-TRTC-RI017:~$ newgrp docker
liuhz@ubuntu-SYS-7049GP-TRTC-RI017:~$ docker ps
CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
liuhz@ubuntu-SYS-7049GP-TRTC-RI017:~$ docker images
REPOSITORY TAG IMAGE ID CREATED SIZE
hello-world latest feb5d9fea6a5 7 months ago 13.3kB
nvidia/cuda 11.0-base 2ec708416bb8 20 months ago 122MB
liuhz@ubuntu-SYS-7049GP-TRTC-RI017:~$
在Docker中运行nnUNet
在dockerhub上查询nvidia/cuda:10.2-cudnn8-devel-ubuntu18.04 ，版本号对应项目运行环境的需求
将其拉下来，sudo docker pull nvidia/cuda:10.2-cudnn8-devel-ubuntu18.04 ，成功后会有一个容器ID
liuhz@ubuntu-SYS-7049GP-TRTC-RI017:~$ sudo docker pull nvidia/cuda:11.4.0-cudnn8-devel-ubuntu20.04
liuhz@ubuntu-SYS-7049GP-TRTC-RI017:~$ sudo docker pull pytorch/pytorch:1.7.0-cuda11.0-cudnn8-devel
在dockerhub上pytorch
https://hub.docker.com/r/pytorch/pytorch/tags?page=1&ordering=last_updated
在dockerhub上ubuntu
https://hub.docker.com/r/nvidia/cuda/
https://gitlab.com/nvidia/container-images/cuda/blob/master/doc/supported-tags.md
查看镜像和运行镜像
查看本地库中的镜像
sudo docker images -a
liuhz@ubuntu-SYS-7049GP-TRTC-RI017:~/Docker$ sudo docker images -a
REPOSITORY TAG IMAGE ID CREATED SIZE
nvidia/cuda 10.2-cudnn8-devel-ubuntu18.04 0dd9ea953585 3 weeks ago 4.46GB
查看 正在运行的 容器
sudo docker ps -a
liuhz@ubuntu-SYS-7049GP-TRTC-RI017:~/Docker$ sudo docker ps -a
CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
为库中镜像改名
sudo docker tag {imageID} {repository}:{tag}
liuhz@ubuntu-SYS-7049GP-TRTC-RI017:~/Docker$ sudo docker tag 0dd9ea953585 ubuntu:cuda10-ubuntu18
liuhz@ubuntu-SYS-7049GP-TRTC-RI017:~/Docker$ sudo docker images -a
REPOSITORY TAG IMAGE ID CREATED SIZE
ubuntu cuda10-ubuntu18 0dd9ea953585 3 weeks ago 4.46GB
nvidia/cuda 10.2-cudnn8-devel-ubuntu18.04 0dd9ea953585 3 weeks ago 4.46GB
删除多余的镜像
liuhz@ubuntu-SYS-7049GP-TRTC-RI017:~$ sudo docker images
REPOSITORY TAG IMAGE ID CREATED SIZE
newubuntu cuda10-ubuntu18 0dd9ea953585 3 weeks ago 4.46GB
ubuntu cuda10-ubuntu18 0dd9ea953585 3 weeks ago 4.46GB
nvidia/cuda 10.2-cudnn8-devel-ubuntu18.04 0dd9ea953585 3 weeks ago 4.46GB
pytorch/pytorch 1.6.0-cuda10.1-cudnn7-devel bb833e4d631f 21 months ago 7.04GB
liuhz@ubuntu-SYS-7049GP-TRTC-RI017:~$ sudo docker rmi ubuntu:cuda10-ubuntu18
Untagged: ubuntu:cuda10-ubuntu18
liuhz@ubuntu-SYS-7049GP-TRTC-RI017:~$ sudo docker rmi ubuntu:cuda10-ubuntu18
Error: No such image: ubuntu:cuda10-ubuntu18
liuhz@ubuntu-SYS-7049GP-TRTC-RI017:~$ sudo docker images
REPOSITORY TAG IMAGE ID CREATED SIZE
nvidia/cuda 10.2-cudnn8-devel-ubuntu18.04 0dd9ea953585 3 weeks ago 4.46GB
newubuntu cuda10-ubuntu18 0dd9ea953585 3 weeks ago 4.46GB
pytorch/pytorch 1.6.0-cuda10.1-cudnn7-devel bb833e4d631f 21 months ago 7.04GB
pytorch镜像测试
liuhz@ubuntu-SYS-7049GP-TRTC-RI017:~$ sudo docker images -a
[sudo] liuhz 的密码：
REPOSITORY TAG IMAGE ID CREATED SIZE
newubuntu cuda10-ubuntu18 0dd9ea953585 3 weeks ago 4.46GB
nvidia/cuda 10.2-cudnn8-devel-ubuntu18.04 0dd9ea953585 3 weeks ago 4.46GB
nvidia/cuda 11.4.0-cudnn8-devel-ubuntu20.04 1885dcefbe89 7 months ago 9.01GB
pytorch/pytorch 1.6.0-cuda10.1-cudnn7-devel bb833e4d631f 21 months ago 7.04GB
liuhz@ubuntu-SYS-7049GP-TRTC-RI017:~$ sudo docker run -it --rm --name test --gpus all pytorch/pytorch:1.6.0-cuda10.1-cudnn7-devel
root@1f8ac7edb753:/workspace# import torch
bash: import: command not found
root@1f8ac7edb753:/workspace# nvidia-smi
Wed Apr 27 16:42:45 2022
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 470.103.01 Driver Version: 470.103.01 CUDA Version: 11.4 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 NVIDIA GeForce ... Off | 00000000:18:00.0 Off | N/A |
| 81% 74C P2 332W / 350W | 23868MiB / 24268MiB | 100% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 1 NVIDIA GeForce ... Off | 00000000:3B:00.0 Off | N/A |
| 73% 70C P2 250W / 350W | 23631MiB / 24268MiB | 100% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 2 NVIDIA GeForce ... Off | 00000000:5E:00.0 Off | N/A |
| 58% 63C P2 268W / 350W | 22753MiB / 24268MiB | 100% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 3 NVIDIA GeForce ... Off | 00000000:86:00.0 Off | N/A |
| 58% 62C P2 209W / 350W | 15465MiB / 24268MiB | 85% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
+-----------------------------------------------------------------------------+
root@1f8ac7edb753:/# conda list
conda-package-handling 1.6.1 py37h7b6447c_0
cryptography 2.9.2 py37h1ba5d50_0
cudatoolkit 10.1.243 h6bb024c_0
decorator 4.4.2 py_0
filelock 3.0.12 py_0
freetype 2.10.2 h5ab3b9f_0
glob2 0.7 py_0
icu 58.2 he6710b0_3
idna 2.9 py_1
intel-openmp 2020.1 217
ipython 7.16.1 py37h5ca1d4c_0
ipython_genutils 0.2.0 py37_0
jedi 0.17.1 py37_0
jinja2 2.11.2 py_0
jpeg 9b h024ee3a_2
lcms2 2.11 h396b838_0
ld_impl_linux-64 2.33.1 h53a641e_7
libarchive 3.4.2 h62408e4_0
libedit 3.1.20181209 hc058e9b_0
libffi 3.3 he6710b0_1
libgcc-ng 9.1.0 hdf63c60_0
libgfortran-ng 7.3.0 hdf63c60_0
liblief 0.10.1 he6710b0_0
libpng 1.6.37 hbc83047_0
libstdcxx-ng 9.1.0 hdf63c60_0
libtiff 4.1.0 h2733197_1
libxml2 2.9.10 he19cac6_1
lz4-c 1.9.2 he6710b0_0
markupsafe 1.1.1 py37h14c3975_1
mkl 2020.1 217
mkl-service 2.3.0 py37he904b0f_0
mkl_fft 1.1.0 py37h23d657b_0
mkl_random 1.1.1 py37h0573a6f_0
ncurses 6.2 he6710b0_1
ninja 1.9.0 py37hfd86e86_0
numpy 1.18.5 py37ha1c710e_0
numpy-base 1.18.5 py37hde5b4d6_0
olefile 0.46 py37_0
openssl 1.1.1g h7b6447c_0
parso 0.7.0 py_0
patchelf 0.11 he6710b0_0
pexpect 4.8.0 py37_1
pickleshare 0.7.5 py37_1001
pillow 7.2.0 py37hb39fc2d_0
pip 20.0.2 py37_3
pkginfo 1.5.0.1 py37_0
prompt-toolkit 3.0.5 py_0
psutil 5.7.0 py37h7b6447c_0
ptyprocess 0.6.0 py37_0
py-lief 0.10.1 py37h403a769_0
pycosat 0.6.3 py37h7b6447c_0
pycparser 2.20 py_0
pygments 2.6.1 py_0
pyopenssl 19.1.0 py37_0
pysocks 1.7.1 py37_0
python 3.7.7 hcff3b4d_5
python-libarchive-c 2.9 py_0
pytorch 1.6.0 py3.7_cuda10.1.243_cudnn7.6.3_0 pytorch
pytz 2020.1 py_0
pyyaml 5.3.1 py37h7b6447c_0
readline 8.0 h7b6447c_0
requests 2.23.0 py37_0
ripgrep 11.0.2 he32d670_0
ruamel_yaml 0.15.87 py37h7b6447c_0
setuptools 46.4.0 py37_0
six 1.14.0 py37_0
soupsieve 2.0.1 py_0
sqlite 3.31.1 h62c20be_1
tk 8.6.10 hbc83047_0
torchvision 0.7.0 py37_cu101 pytorch
tqdm 4.46.0 py_0
traitlets 4.3.3 py37_0
urllib3 1.25.8 py37_0
wcwidth 0.2.5 py_0
wheel 0.34.2 py37_0
xz 5.2.5 h7b6447c_0
yaml 0.1.7 had09818_2
zlib 1.2.11 h7b6447c_3
zstd 1.4.5 h0b5b093_0
root@1f8ac7edb753:/# python
Python 3.7.7 (default, May 7 2020, 21:25:33)
[GCC 7.3.0] :: Anaconda, Inc. on linux
Type "help", "copyright", "credits" or "license" for more information.
>>>
root@1f8ac7edb753:/# ls
bin dev home lib64 mnt proc run srv tmp var
boot etc lib media opt root sbin sys usr workspace
root@1f8ac7edb753:/# python
Python 3.7.7 (default, May 7 2020, 21:25:33)
[GCC 7.3.0] :: Anaconda, Inc. on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import torch
>>> torch.cuda.is_available()
True
>>>
root@1f8ac7edb753:/# exit
liuhz@ubuntu-SYS-7049GP-TRTC-RI017:~$
退出时ctrl+D或者exit