Linux的安装

1.下载Anaconda 4.4.0,最牛B的机器学习库、
  wget https://repo.continuum.io/archive/Anaconda2-4.4.0-Linux-x86_64.sh

2.bash Anaconda2-4.4.0-Linux-x86_64.sh  //会自动安装python2.7的版本
中文版：https://repo.continuum.io/archive/Anaconda3-4.4.0-Windows-x86_64.exe，python3.6

3.conda create -n tensorflow python=2.7，创建新的环境
conda remove -b tensorflow --all，删除环境

4.source activate tensorflow 激活新环境
source deactivate tensorflow 禁用环境

5.安装tensorflow
pip install --trusted-host pypi.douban.com --ignore-installed --upgrade https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.2.1-cp27-none-linux_x86_64.whl

中文
pip install --trusted-host pypi.douban.com --ignore-installed --upgrade https://storage.googleapis.com/tensorflow/windows/cpu/tensorflow-1.2.1-cp36-cp36m-win_amd64.whl
pip install --trusted-host pypi.douban.com --ignore-installed --upgrade https://storage.googleapis.com/tensorflow/windows/cpu/tensorflow_gpu-1.2.1-cp36-cp36m-win_amd64.whl

注：--trusted-host pypi.douban.com，在失败时，根据提示增加或修改该项
----------------
注：https://storage.googleapis.com/tensorflow/在该页面搜索“-cp27-none-linux_x86_64.whl”的最新版本
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报错：/lib64/libc.so.6: version `GLIBC_2.14'版本时，请到http://www.gnu.org/software/libc/中查找相应的版本进行安装

Window的安装

Installing with Anaconda

The Anaconda installation is community supported, not officially supported.

Take the following steps to install TensorFlow in an Anaconda environment:

Follow the instructions on the Anaconda download site to download and install Anaconda.
Create a conda environment named tensorflow by invoking the following command:

C:> conda create -n tensorflow python=3.5 
Activate the conda environment by issuing the following command:

C:> activate tensorflow
 (tensorflow)C:>  # Your prompt should change 
Issue the appropriate command to install TensorFlow inside your conda environment. To install the CPU-only version of TensorFlow, enter the following command:

(tensorflow)C:> pip install --ignore-installed --upgrade https://storage.googleapis.com/tensorflow/windows/cpu/tensorflow-1.2.1-cp35-cp35m-win_amd64.whl 
To install the GPU version of TensorFlow, enter the following command (on a single line):

(tensorflow)C:> pip install --ignore-installed --upgrade https://storage.googleapis.com/tensorflow/windows/gpu/tensorflow_gpu-1.2.1-cp35-cp35m-win_amd64.whl 
Validate your installation

Start a terminal.

If you installed through Anaconda, activate your Anaconda environment.

Invoke python from your shell as follows:

$ python
Enter the following short program inside the python interactive shell:

>>> import tensorflow as tf
>>> hello = tf.constant('Hello, TensorFlow!')
>>> sess = tf.Session()
>>> print(sess.run(hello))
If the system outputs the following, then you are ready to begin writing TensorFlow programs:

Hello, TensorFlow!
If you are new to TensorFlow, see Getting Started with TensorFlow.

If the system outputs an error message instead of a greeting, see Common installation problems.

在使用LNMP包安装PHP时，发现直接修改php.ini的配置是无法生效的，其原因竟然是因为nginx的配置文件，覆盖了php.ini的配置。
——————————————————————–
LNMP 1.4上如果不想用防跨目录还需要将 /usr/local/nginx/conf/fastcgi.conf 里面的fastcgi_param PHP_ADMIN_VALUE “open_basedir=$document_root/:/tmp/:/proc/”; 删除，需要重启nginx。
LNMP 1.4上也可以直接使用lnmp1.4/tools/ 目录下的 ./remove_open_basedir_restriction.sh 进行移除。

本地文件同步：
rsync -av /home/ /waypal
在指定复制源时，路径是否有最后的 “/” 有不同的含义，例如：
/home ： 表示将整个 /home 目录复制到目标目录
/home/ ： 表示将 /home 目录中的所有内容复制到目标目录
跨服务器同步：
rsync+sshd方式，需要输入密码，如下。
a. 增量同步
rsync -av --progress -e ssh root@kxtry.com:/alidata/www/kxtry.com ./kxtry.com
b. 镜像同步
rsync -av --progress -e ssh --delete root@kxtry.com:/alidata/www/kxtry.com ./kxtry.com

在处理后端协议时，时常需要将外域bean对象转换成当前域的bean对象，这时就需要对两个bean进行内容复制，如果觉得手动编码效率低，可以试试Orika开源库。
https://github.com/orika-mapper/orika
http://orika-mapper.github.io/orika-docs/

MapperFactory mapperFactory = new DefaultMapperFactory.Builder().build();
mapperFactory.classMap(PersonDTO.class, Person.class) //A ClassMapBuilder
        .field("lastNames", "surnames") //Register field mappings
        .field("streetAddress", "address.street")
        .field("city", "address.city")
        .field("postalCode", "address.zipCode")
        .byDefault() //the remaining fields on both classes should be mapped matching the fields by name
        .register(); //register the mapping with the MapperFactory.