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adb install -r 替换已存在的应用程序，也就是说强制安装

adb install -l 锁定该应用程序

adb install -t 允许测试包

adb install -s 把应用程序安装到sd卡上

adb install -d 允许进行将见状，也就是安装的比手机上带的版本低

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start bluestack or emulator install app on it start the app

connect adb to emulator

$ adb connect localhost:5555

get 'pid' of your app .Dont forget to run it first in emulator

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Extracting Existing Kernel + Ramfs

Enter the machine using adb shell

Run cat /proc/partitions

  #  Path                     Purpose        Size
  0 /dev/block/mmcblk0                       7761920
  1 /dev/block/mmcblk0p1      data           6085631

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3 Virtual Machines Kubernetes cluster

Dependencies

You should install VirtualBox and Vagrant before you start.

Creating the cluster

You should create a Vagrantfile in an empty directory with the following content:

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key通常指私钥

CSR 是Certificate Signing Request的缩写，即证书签名申请，这不是证书，这是要求CA给证书签名的一种正是申请，该申请包含申请证书的实体的公钥及该实体店某些信息。该数据将成为证书的一部分。CSR始终使用它携带的公钥所对应的私钥进行签名。

CRT 即 certificate的缩写，即证书

TLS：传输层安全协议 Transport Layer Security的缩写

SSL：安全套接字层 Secure Socket Layer的缩写

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sudo su

杀死进程

ps -ef | grep LVS
kill -9 $PID

删除文件夹

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自签名ssl证书生成

生成CA私钥

# 创建文件夹 ca 保存Ca相关
mkdir ca
cd ca
#创建私钥 (建议设置密码)
openssl genrsa -des3 -out myCA.key 2048

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from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals

import argparse
import h5py
import json
import os
import scipy.misc

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#
# this gist can be used to list all targets, or - more correctly - rules,
# that are defined in a Makefile (and possibly other included Makefiles)
# and is inspired by Jack Kelly's reply to a StackOverflow question:
#
#   http://stackoverflow.com/questions/3063507/list-goals-targets-in-gnu-make/3632592#3632592
#
# I also found this script - http://www.shelldorado.com/scripts/cmds/targets - which does
# something similar using awk, but it extracts targets from the "static" rules from a single
# Makefile, meaning it ignores any included Makefiles, as well as targets from "dynamic" rules

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import tensorflow as tf
from tensorflow.python.platform import gfile
with tf.Session() as sess:
    model_filename ='PATH_TO_PB.pb'
    with gfile.FastGFile(model_filename, 'rb') as f:
        graph_def = tf.GraphDef()
        graph_def.ParseFromString(f.read())
        g_in = tf.import_graph_def(graph_def)
LOGDIR='/logs/tests/1/'
train_writer = tf.summary.FileWriter(LOGDIR)