phpstorm using xdebug 2017.3 on windows

totally speaking ,it's easy.
let's get started.
1st.you need to get xdebug extension.Im using phpstudy,so there's no need to download it.
2nd.you need to config it.open the corresponding php.ini config file,then write down the config below:
[XDebug]
xdebug.profiler_output_dir="C:\phpStudy\PHPTutorial\tmp\xdebug"
xdebug.trace_output_dir="C:\phpStudy\PHPTutorial\tmp\xdebug"
zend_extension = "C:\phpStudy\PHPTutorial\php\php-5.6.27-nts\ext\php_xdebug.dll"
xdebug.remote_enable = On
xdebug.remote_handler = dbgp
xdebug.remote_host= 127.0.0.1
xdebug.remote_port = 9000
xdebug.idekey = PHPSTORM
PS:it's useless of the org's config of phpstudy about xdebug,so just paste it and then change to what you like.
3rd.you need to config in phpstorm.since you config the xdebug in its own,so just emit the same config in phpstorm .All you need to do in phpstorm is as follows:
1).Ctrl+Alt+S:Language and Framework->PHP:PHP Language level:your level(mine is 5.6);CLI interpreter:5.6.xxx;(you can only set php executable).
2).set the server.your server ip port.debugger set to xdebug.
Done!!!Enjoy yourself!

NMT安装

CentOS7 安装pip 

Prerequest

yum -y install epel-release
yum -y install python-pip
pip install --upgrade pip
Alternative:
  pip install tensorflow
  pip install tensorflow-gpu
in python prompt:
  import tensorflow as tf
  hello = tf.constant('Hello, TensorFlow!')
  sess = tf.Session()
  print(sess.run(hello))
git clone https://github.com/tensorflow/nmt

Installation

Simple Trainning
nmt/scripts/download_iwslt15.sh /tmp/nmt_data
mkdir /tmp/nmt_model
python -m nmt.nmt \
    --src=vi --tgt=en \
    --vocab_prefix=/tmp/nmt_data/vocab  \
    --train_prefix=/tmp/nmt_data/train \
    --dev_prefix=/tmp/nmt_data/tst2012  \
    --test_prefix=/tmp/nmt_data/tst2013 \
    --out_dir=/tmp/nmt_model \
    --num_train_steps=12000 \
    --steps_per_stats=100 \
    --num_layers=2 \
    --num_units=128 \
    --dropout=0.2 \
    --metrics=bleu

Reference:

https://ehlxr.me/2017/01/07/CentOS-7-%E5%AE%89%E8%A3%85-Python3%E3%80%81pip3/
https://www.tensorflow.org/install/install_linux#ValidateYourInstallation
https://github.com/tensorflow/nmt

Qt5.9.2及QtWebEngine

毫无疑问,编译Qt总是麻烦的.
方便的是,Qt为我们提供了已经编译好的了.但是需要注意,在5.9.2版本中,Qt中的QtWebEngine只有在VS2015+中才能使用,原因是新版本的QtWenbEngine只有VS2015Update1+才能编译成功...
So,其他就可以不用考虑了...

111

chcon -R -t httpd_sys_rw_content_t schoolcms 已解决
chmod -R apache:apache YourDir

单片机1

单片机Keil安装后,明明卖家发来的demo是可以用的,竟然总是报错...0x800H .
换了原来写的小程序正常,再换大些的网上下载的程序,依然不能编译通过...
竟然是没有安装LIC...需要Administrator运行,注册机,ADD Lic 就好了(File->License Management).
当然,还要选型(再STC-ISP中添加型号,就会有STC_MCU)

编译wx版本

			编译状态	是否使用wx的dll	是否使用静态库	编译的调试版本还是发行版	UNICODE是否使用	命令行
				shared	monolithic	build	unicode
UNICODE	静态库版	使用dll	完成	1	1	调试版	1	mingw32-make -f makefile.gcc USE_XRC=1 SHARED=1 MONOLITHIC=1 BUILD=debug UNICODE=1 USE_OPENGL=1 VENDOR=cb CXXFLAGS="-fno-keep-inline-dllexport" >log.txt 2>&1
			完成	1	1	发行版	1	mingw32-make -f makefile.gcc USE_XRC=1 SHARED=1 MONOLITHIC=1 BUILD=release UNICODE=1 USE_OPENGL=1 VENDOR=cb CXXFLAGS="-fno-keep-inline-dllexport" >log.txt 2>&1
		不使用dll	完成	0	1	调试版	1	mingw32-make -f makefile.gcc USE_XRC=1 SHARED=0 MONOLITHIC=1 BUILD=debug UNICODE=1 USE_OPENGL=1 VENDOR=cb CXXFLAGS="-fno-keep-inline-dllexport" >log.txt 2>&1
			完成	0	1	发行版	1	mingw32-make -f makefile.gcc USE_XRC=1 SHARED=0 MONOLITHIC=1 BUILD=release UNICODE=1 USE_OPENGL=1 VENDOR=cb CXXFLAGS="-fno-keep-inline-dllexport" >log.txt 2>&1
	非静态库	使用dll	完成	1	0	调试版	1	mingw32-make -f makefile.gcc USE_XRC=1 SHARED=1 MONOLITHIC=0 BUILD=debug UNICODE=1 USE_OPENGL=1 VENDOR=cb CXXFLAGS="-fno-keep-inline-dllexport" >log.txt 2>&1
			完成	1	0	发行版	1	mingw32-make -f makefile.gcc USE_XRC=1 SHARED=1 MONOLITHIC=0 BUILD=release UNICODE=1 USE_OPENGL=1 VENDOR=cb CXXFLAGS="-fno-keep-inline-dllexport" >log.txt 2>&1
		不使用dll	正在	0	0	调试版	1	mingw32-make -f makefile.gcc USE_XRC=1 SHARED=0 MONOLITHIC=0 BUILD=debug UNICODE=1 USE_OPENGL=1 VENDOR=cb CXXFLAGS="-fno-keep-inline-dllexport" >log.txt 2>&1
			未完成	0	0	发行版	1	mingw32-make -f makefile.gcc USE_XRC=1 SHARED=0 MONOLITHIC=0 BUILD=release UNICODE=1 USE_OPENGL=1 VENDOR=cb CXXFLAGS="-fno-keep-inline-dllexport" >log.txt 2>&1
默认都不指定的是ANSI版本
ANSI	静态库版	使用dll	未完成	1	1	调试版	0	mingw32-make -f makefile.gcc USE_XRC=1 SHARED=1 MONOLITHIC=1 BUILD=debug UNICODE=0 USE_OPENGL=1 VENDOR=cb CXXFLAGS="-fno-keep-inline-dllexport" >log.txt 2>&1
			未完成	1	1	发行版	0	mingw32-make -f makefile.gcc USE_XRC=1 SHARED=1 MONOLITHIC=1 BUILD=release UNICODE=0 USE_OPENGL=1 VENDOR=cb CXXFLAGS="-fno-keep-inline-dllexport" >log.txt 2>&1
		不使用dll	未完成	0	1	调试版	0	mingw32-make -f makefile.gcc USE_XRC=1 SHARED=0 MONOLITHIC=1 BUILD=debug UNICODE=0 USE_OPENGL=1 VENDOR=cb CXXFLAGS="-fno-keep-inline-dllexport" >log.txt 2>&1
			未完成	0	1	发行版	0	mingw32-make -f makefile.gcc USE_XRC=1 SHARED=0 MONOLITHIC=1 BUILD=release UNICODE=0 USE_OPENGL=1 VENDOR=cb CXXFLAGS="-fno-keep-inline-dllexport" >log.txt 2>&1
	非静态库	使用dll	未完成	1	0	调试版	0	mingw32-make -f makefile.gcc USE_XRC=1 SHARED=1 MONOLITHIC=0 BUILD=debug UNICODE=0 USE_OPENGL=1 VENDOR=cb CXXFLAGS="-fno-keep-inline-dllexport" >log.txt 2>&1
			未完成	1	0	发行版	0	mingw32-make -f makefile.gcc USE_XRC=1 SHARED=1 MONOLITHIC=0 BUILD=release UNICODE=0 USE_OPENGL=1 VENDOR=cb CXXFLAGS="-fno-keep-inline-dllexport" >log.txt 2>&1
		不使用dll	未完成	0	0	调试版	0	mingw32-make -f makefile.gcc USE_XRC=1 SHARED=0 MONOLITHIC=0 BUILD=debug UNICODE=0 USE_OPENGL=1 VENDOR=cb CXXFLAGS="-fno-keep-inline-dllexport" >log.txt 2>&1
			未完成	0	0	发行版	0	mingw32-make -f makefile.gcc USE_XRC=1 SHARED=0 MONOLITHIC=0 BUILD=release UNICODE=0 USE_OPENGL=1 VENDOR=cb CXXFLAGS="-fno-keep-inline-dllexport" >log.txt 2>&1

高数公式2