Json Formatter

test.json

{ "stuff": { "that": [1,2,3], "isin": true, "json": "end"}}

jq

在命令行运行

jq . <<< '{ "stuff": { "that": [1,2,3], "isin": true, "json": "end"}}'

jq . test.json

在vim的命令模式下运行

%!jq .

python json.tool

在命令行运行

python -m json.tool <<< '{ "stuff": { "that": [1,2,3], "isin": true, "json": "end"}}'

python -m json.tool test.json

在vim的命令模式下运行

%!python -m json.tool

在线格式化 Format JSON JSON Formatter JSON Formatter, Validator, Vi

jsonjqpythonvimcommand-lineshelltools

命令tr 

$ df -h
Filesystem      Size  Used Avail Use% Mounted on
udev            126G     0  126G   0% /dev
tmpfs            26G  4.0M   26G   1% /run
/dev/sda2       548G   50G  471G  10% /
tmpfs           126G     0  126G   0% /sys/fs/cgroup
/dev/sda1       511M  7.9M  504M   2% /boot/efi
/dev/sdb1       2.0T  4.7G  1.9T   1% /data

字母小写转大写

$ df -h | tr [:lower:] [:upper:]

FILESYSTEM      SIZE  USED AVAIL USE% MOUNTED ON
UDEV            126G     0  126G   0% /DEV
TMPFS            26G  4.0M   26G   1% /RUN
/DEV/SDA2       548G   50G  471G  10% /
TMPFS           126G     0  126G   0% /SYS/FS/CGROUP
/DEV/SDA1       511M  7.9M  504M   2% /BOOT/EFI
/DEV/SDB1       2.0T  4.7G  1.9T   1% /DATA

$ df -h | tr a-z A-Z

字母大写转小写

$ df -h | tr [:upper:] [:lower:]
$ df -h | tr A-Z a-z
trlinuxcommand-lineshelltext-processing

OpenResty 内执行 Lua 脚本

OpenResty 是一款基于 NGINX 和 LuaJIT 的 Web 平台。

拉取 OpenResty 镜像

  • Ubuntu
sudo docker pull openresty/openresty:xenial
  • CentOS
sudo docker pull openresty/openresty:centos

查看镜像的标签 $ sudo docker inspect openresty/openresty:centos | jq '.[].Config.Labels' { "maintainer": "Evan Wies <evan@neomantra.net>", "org.label-schema.build-date": "20210915", "org.label-schema.license": "GPLv2", "org.label-schema.name": "CentOS Base Image", "org.label-schema.schema-version": "1.0", "org.label-schema.

openrestynginxluadockercurljqshell

逻辑卷管理(Logical Volume Management)

查看 LVM 的相关命令

man lvm

lvm --help

查看系统的块设备 $ lsblk NAME MAJ:MIN RM SIZE RO TYPE MOUNTPOINT loop0 7:0 0 43.4M 1 loop /snap/snapd/14549 loop1 7:1 0 43.3M 1 loop /snap/snapd/14295 loop2 7:2 0 76.3M 1 loop /snap/lxd/22407 loop3 7:3 0 61.9M 1 loop /snap/core20/1328 loop4 7:4 0 55.5M 1 loop /snap/core18/2253 loop5 7:5 0 55.5M 1 loop /snap/core18/2284 loop7 7:7 0 94.5M 1 loop /snap/go/9028 loop8 7:8 0 94.5M 1 loop /snap/go/8839 loop9 7:9 0 76.3M 1 loop /snap/lxd/22358 loop10 7:10 0 61.9M 1 loop /snap/core20/1270 sda 8:0 0 558.9G 0 disk ├─sda1 8:1 0 512M 0 part /boot/efi └─sda2 8:2 0 558.

lvmlinuxfilesystemmountstoragepartitionsysadmin

构建基于 ONNXRuntime 的推理服务

构建 ONNXRuntime-GPU 镜像

编写 requirements.txt

$ vim requirements.txt

flask
connexion[swagger-ui]
connexion
gunicorn
numpy
opencv-python
scikit-image
psutil
pynvml
onnxruntime-gpu

编写 Dockerfile 需要带 cudnn 库的 CUDA 作为基镜像 $ vim Dockerfile FROM nvidia/cuda:11.4.0-cudnn8-runtime-ubuntu20.04 LABEL maintainer="wang-junjian@qq.com" RUN rm /etc/apt/sources.list.d/cuda.list /etc/apt/sources.list.d/nvidia-ml.list && \ sed -i 's/archive.ubuntu.com/mirrors.aliyun.com/g' /etc/apt/sources.

onnxruntimeonnxgpucudadockerdockerfileinference-servingcudnnpython

在Linux上安装CUDA Toolkit

安装 CUDA Toolkit

下载

wget https://developer.download.nvidia.com/compute/cuda/11.6.0/local_installers/cuda_11.6.0_510.39.01_linux.run

安装 $ sudo sh cuda_11.5.1_495.29.05_linux.run =========== = Summary = =========== Driver: Installed Toolkit: Installed in /usr/local/cuda-11.5/ Samples: Installed in /home/lnsoft/, but missing recommended libraries Please make sure that - PATH includes /usr/local/cuda-11.5/bin - LD_LIBRARY_PATH includes /usr/local/cuda-11.5/lib64, or, add /usr/local/cuda-11.5/lib64 to /etc/ld.so.

linuxcudanvidiadriverinstallationnvidia-smigpuubuntu