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bet365体育在线uo“坐下吧!馨儿

2016-03-10 来源: 作者:陈延鹏 责任编辑:田艳敏

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 bet365体育在线uo“坐下吧!馨儿

有bet365体育在线uo“坐下吧!馨儿 明白的也可以给我留言打个广告:加微信neihanrukou摘要 bet365体育在线uo“坐下吧!馨儿 的基础功能已经完成,可以查看,可以发表,可以bet365体育在线uo“坐下吧!馨儿 ,但还有很多的细节可以进行优化,如在主页中显示概要而bet365体育在线uo“坐下吧!馨儿 全显示内容,对bet365体育在线uo“坐下吧!馨儿 的分页显示,对标签的分类显示等,这一bet365体育在线uo“坐下吧!馨儿 来谈谈bet365体育在线uo“坐下吧!馨儿 之功能优化 django blog paginator python url 当在主页上看bet365体育在线uo“坐下吧!馨儿 时,一般bet365体育在线uo“坐下吧!馨儿 会看到文bet365体育在线uo“坐下吧!馨儿 的正文,而是看一个摘要,如果没有摘要就看前面一小段,看正文则要在单独的bet365体育在线uo“坐下吧!馨儿 页面上进行查看,因此有必要做一个链接可以链到单独bet365体育在线uo“坐下吧!馨儿 页以进行continue reading... 适当修改index.html #/myblog/blog/templates/index.html 1 {% extends "base.html" %} 2 {% block content %} 3 <div class = "posts"> 4 {% for blog in blog_list %} 5 <section class="post"> 6 <header class="post-header"> 7 <h2 class= "post-title"><a href="{% url 'detail' id=blog.id %}">{{blog.title}}</a><h2> 8 <p class = "post-meta"> 9 Time: <a class="post-author" href="#">{{blog.date_time | date:'Y M d'}}</a>&nbsp10 Tag:11 {% for tag in blog.tags.all %}12 <a class="post-category" href="#">{{tag.tag_name|title}}</a>13 {% endfor %}14 </p>15 </header>16 17 <div class="post-description">18 <p>19 {{blog.content|safe|truncatewords:15}} #正文只显示15个字20 <a class="pure-button" href={% url 'detail' id=blog.id %}>Continue Reading...</a> #continue reading链接到bet365体育在线uo“坐下吧!馨儿 细节21 </p>22 </div>23 </section>24 {% endfor %} 当bet365体育在线uo“坐下吧!馨儿 数量很多时有必要对页面进行分页,值得庆幸的是django本身自带分页的功能Paginator #/myblog/blog/views.py#重写index方法,使得支持分页功能 8 from django.core.paginator import Paginator,EmptyPage,PageNotAnInteger11 def index(request): 12 blogs = Blog.objects.all() 13 tags = Tag.objects.all()14 paginator = Paginator(blogs,3) #每页显示3篇blog进行分页 15 page = request.GET.get('page') #获取当前页的数字16 try: 17 current_page = paginator.page(page) #获取当前页18 except PageNotAnInteger: #如果系统从0开始,就赋初值为119 current_page = paginator.page(1) 20 blog_list = current_page.object_list #获得当前页的blog21 22 23 return render_to_response('index.html',{'blog_list':blog_list, 24 'tags': tags,25 'current_page':current_page}) 新增index.html中适配分页 #/myblog/blog/templates/index.html25 {% if blog_list and current_page.paginator.num_pages > 1 %} #bet365体育在线uo“坐下吧!馨儿 数和总页数大于126 <div>27 <ul class="post">28 {% if current_page.has_previous %} #前一页29 <li><a href="?page={{current_page.previous_page_number }}">previous page</a></li>30 {% endif %}31 {% if current_page.has_next %} #后一页32 <li><a href="?page={{current_page.next_page_number }}">next page</a></li>33 {% endif %}34 </ul>35 </div> 36 {% endif %} 标签分类,把标签放到左边,然后以标签来搜索相应标签的文bet365体育在线uo“坐下吧!馨儿 step 1 新建url匹配归档的方法 #/myblog/blog/urls.py 1 from django.conf.urls import patterns, include, url 2 3 from django.contrib import admin 4 5 from blog import views 6 7 urlpatterns =[ 8 url(r'^$', views.index, name='index'), 9 url(r'^(?P<id>(\d+))/$', views.detail, name='detail'), 10 url(r'^post/$', views.post, name='post'), 11 url(r'^blog_add/$', views.blog_add, name='blog_add'), 12 url(r'^uploadImg/$', views.uploadImg,name='uploadImg'), 13 url(r'^sub_comment/$', views.sub_comment,name='sub_comment'), 14 url(r'^tag_blog(?P<id>(\d+))/$', views.tag_blog,name='tag_blog'), #根据id来查找相应的标签 15 ] step 2 新建 views方法来显示归档后的文bet365体育在线uo“坐下吧!馨儿 ,这个页面与index页面是相同的,只是返回的blog_listbet365体育在线uo“坐下吧!馨儿 同,一个是全部bet365体育在线uo“坐下吧!馨儿 ,一个是相应标签的bet365体育在线uo“坐下吧!馨儿 104 def tag_blog(request,id):105 tag = Tag.objects.get(id=id) #根据id获取当前tag 106 blogs = tag.blog_set.all() #由于tag与blog是多对多关系,可以根据tag查找相应的blog107 paginator = Paginator(blogs,3)108 page = request.GET.get('page')109 try:110 current_page = paginator.page(page)111 except PageNotAnInteger:112 current_page = paginator.page(1)113 blog_list = current_page.object_list114 return render_to_response('index.html',{'blog_list':blog_list,115 'tag': tag,116 'current_page':current_page}) step 3 修改base.html也就是主页中把标签放到左边,找到去归档的标签入口 12 <div class="sidebar pure-u-md-1-4"> 13 <div class="header"> 14 <h1 class="brand-title">terry ding blog</h1> 15 <h2 class="brand-tagline">Welcome to this Blog</h2> 16 <nav class="nav"> 17 <ul class="nav-list"> 18 <li class="nav-item"> 19 <a class="pure-button" href="{% url 'index'%}">Blog</a> 20 </li> 21 <li class="nav-item"> 22 <a class="pure-button" href="{% url 'post' %}">Post</a> 23 </li> 24 </ul> 25 <ul class="nav-list"> 26 {% for tag in tags %} 27 <li class="nav-item"> 28 <a class="pure-button" href="{% url 'tag_blog' id=tag.id %}">{{tag.tag_name|title}}</a>&nb #根据标签自身归档 sp;&nbsp; 29 </li> 30 {% endfor %} 31 </ul> 32 </nav> 33 </div> 34 </div> bet365体育在线uo“坐下吧!馨儿 已初俱功能了,界面还非常丑陋,这也bet365体育在线uo“坐下吧!馨儿 是一时半会儿就会好的,先将就着吧,以后有机会再优化摘要 How to define a function that takes a variable number of parameters? Java Variable number of parameters Autoboxing There are two types in Java, the primitive type and the compound type (or the objects). 233.getClass();//NOOOOOOOOOO!newInteger(233).getClass();//GOOD:) In the first line of the code block above, the compiler will not automatically wrap 233 as an Integer object and we have to do it manually as the second line shows. At other times, the compiler will do the autoboxing for us (since JDK 5.0). We will see autoboxing in the following example of variable parameters. publicclassJavaApplication{publicstaticvoidtypeDetect(Object...args){System.out.println(args.length+"argumentsintotal.");for(Objectobj:args){System.out.println(obj.getClass());}}publicstaticvoidmain(String[]args){typeDetect(1,"one",'1',2.33);}} Output 4argumentsintotal.classjava.lang.Integerclassjava.lang.Stringclassjava.lang.Characterclassjava.lang.Double So as you see, it is easy to deal with variable number of parameters. All the parameters are collected in the array args. This is possible because all classes in Java are subclasses of Object and the compiler will do the autoboxing job for the primitive types just as the output suggests. The python counterpart is like this: deffunc(a,b,c,*rest):pass摘要 Drawable 着色的后向兼容方案 http://www.race604.com/tint-drawable/ 考虑着色方案主要目的是更方便支持多主题,减轻UI工作量,减少工程里一大堆selector文件等,然后才是,顺便的减小一下apk大小 这里也有人说是建立 CPU“核心数量 * 2 +2”个线程,我想这个应该没有什么太大的区别,我就是按照我bet365体育在线uo“坐下吧!馨儿 的习惯来了 凯时娱乐城培养成我们的奴隶

caffe的输出中也有包含这块的内容日志,详情如下:I0721 10:38:15.326920 4692 net.cpp:125] Top shape: 256 3 227 227 (39574272)I0721 10:38:15.326971 4692 net.cpp:125] Top shape: 256 1 1 1 (256)I0721 10:38:15.326982 4692 net.cpp:156] data does not need backward computation.I0721 10:38:15.327003 4692 net.cpp:74] Creating Layer conv1I0721 10:38:15.327011 4692 net.cpp:84] conv1 <- dataI0721 10:38:15.327033 4692 net.cpp:110] conv1 -> conv1I0721 10:38:16.721956 4692 net.cpp:125] Top shape: 256 96 55 55 (74342400)I0721 10:38:16.722030 4692 net.cpp:151] conv1 needs backward computation.I0721 10:38:16.722059 4692 net.cpp:74] Creating Layer relu1I0721 10:38:16.722070 4692 net.cpp:84] relu1 <- conv1I0721 10:38:16.722082 4692 net.cpp:98] relu1 -> conv1 (in-place)I0721 10:38:16.722096 4692 net.cpp:125] Top shape: 256 96 55 55 (74342400)I0721 10:38:16.722105 4692 net.cpp:151] relu1 needs backward computation.I0721 10:38:16.722116 4692 net.cpp:74] Creating Layer pool1I0721 10:38:16.722125 4692 net.cpp:84] pool1 <- conv1I0721 10:38:16.722133 4692 net.cpp:110] pool1 -> pool1I0721 10:38:16.722167 4692 net.cpp:125] Top shape: 256 96 27 27 (17915904)I0721 10:38:16.722187 4692 net.cpp:151] pool1 needs backward computation.I0721 10:38:16.722205 4692 net.cpp:74] Creating Layer norm1I0721 10:38:16.722221 4692 net.cpp:84] norm1 <- pool1I0721 10:38:16.722234 4692 net.cpp:110] norm1 -> norm1I0721 10:38:16.722251 4692 net.cpp:125] Top shape: 256 96 27 27 (17915904)I0721 10:38:16.722260 4692 net.cpp:151] norm1 needs backward computation.I0721 10:38:16.722272 4692 net.cpp:74] Creating Layer conv2I0721 10:38:16.722280 4692 net.cpp:84] conv2 <- norm1I0721 10:38:16.722290 4692 net.cpp:110] conv2 -> conv2I0721 10:38:16.725225 4692 net.cpp:125] Top shape: 256 256 27 27 (47775744)I0721 10:38:16.725242 4692 net.cpp:151] conv2 needs backward computation.I0721 10:38:16.725253 4692 net.cpp:74] Creating Layer relu2I0721 10:38:16.725261 4692 net.cpp:84] relu2 <- conv2I0721 10:38:16.725270 4692 net.cpp:98] relu2 -> conv2 (in-place)I0721 10:38:16.725280 4692 net.cpp:125] Top shape: 256 256 27 27 (47775744)I0721 10:38:16.725288 4692 net.cpp:151] relu2 needs backward computation.I0721 10:38:16.725298 4692 net.cpp:74] Creating Layer pool2I0721 10:38:16.725307 4692 net.cpp:84] pool2 <- conv2I0721 10:38:16.725317 4692 net.cpp:110] pool2 -> pool2I0721 10:38:16.725329 4692 net.cpp:125] Top shape: 256 256 13 13 (11075584)I0721 10:38:16.725338 4692 net.cpp:151] pool2 needs backward computation.I0721 10:38:16.725358 4692 net.cpp:74] Creating Layer norm2I0721 10:38:16.725368 4692 net.cpp:84] norm2 <- pool2I0721 10:38:16.725378 4692 net.cpp:110] norm2 -> norm2I0721 10:38:16.725389 4692 net.cpp:125] Top shape: 256 256 13 13 (11075584)I0721 10:38:16.725399 4692 net.cpp:151] norm2 needs backward computation.I0721 10:38:16.725409 4692 net.cpp:74] Creating Layer conv3I0721 10:38:16.725419 4692 net.cpp:84] conv3 <- norm2I0721 10:38:16.725427 4692 net.cpp:110] conv3 -> conv3I0721 10:38:16.735193 4692 net.cpp:125] Top shape: 256 384 13 13 (16613376)I0721 10:38:16.735213 4692 net.cpp:151] conv3 needs backward computation.I0721 10:38:16.735224 4692 net.cpp:74] Creating Layer relu3I0721 10:38:16.735234 4692 net.cpp:84] relu3 <- conv3I0721 10:38:16.735242 4692 net.cpp:98] relu3 -> conv3 (in-place)I0721 10:38:16.735250 4692 net.cpp:125] Top shape: 256 384 13 13 (16613376)I0721 10:38:16.735258 4692 net.cpp:151] relu3 needs backward computation.I0721 10:38:16.735302 4692 net.cpp:74] Creating Layer conv4I0721 10:38:16.735312 4692 net.cpp:84] conv4 <- conv3I0721 10:38:16.735321 4692 net.cpp:110] conv4 -> conv4I0721 10:38:16.743952 4692 net.cpp:125] Top shape: 256 384 13 13 (16613376)I0721 10:38:16.743988 4692 net.cpp:151] conv4 needs backward computation.I0721 10:38:16.744000 4692 net.cpp:74] Creating Layer relu4I0721 10:38:16.744010 4692 net.cpp:84] relu4 <- conv4I0721 10:38:16.744020 4692 net.cpp:98] relu4 -> conv4 (in-place)I0721 10:38:16.744030 4692 net.cpp:125] Top shape: 256 384 13 13 (16613376)I0721 10:38:16.744038 4692 net.cpp:151] relu4 needs backward computation.I0721 10:38:16.744050 4692 net.cpp:74] Creating Layer conv5I0721 10:38:16.744057 4692 net.cpp:84] conv5 <- conv4I0721 10:38:16.744067 4692 net.cpp:110] conv5 -> conv5I0721 10:38:16.748935 4692 net.cpp:125] Top shape: 256 256 13 13 (11075584)I0721 10:38:16.748955 4692 net.cpp:151] conv5 needs backward computation.I0721 10:38:16.748965 4692 net.cpp:74] Creating Layer relu5I0721 10:38:16.748975 4692 net.cpp:84] relu5 <- conv5I0721 10:38:16.748983 4692 net.cpp:98] relu5 -> conv5 (in-place)I0721 10:38:16.748998 4692 net.cpp:125] Top shape: 256 256 13 13 (11075584)I0721 10:38:16.749011 4692 net.cpp:151] relu5 needs backward computation.I0721 10:38:16.749022 4692 net.cpp:74] Creating Layer pool5I0721 10:38:16.749030 4692 net.cpp:84] pool5 <- conv5I0721 10:38:16.749039 4692 net.cpp:110] pool5 -> pool5I0721 10:38:16.749050 4692 net.cpp:125] Top shape: 256 256 6 6 (2359296)I0721 10:38:16.749058 4692 net.cpp:151] pool5 needs backward computation.I0721 10:38:16.749074 4692 net.cpp:74] Creating Layer fc6I0721 10:38:16.749083 4692 net.cpp:84] fc6 <- pool5I0721 10:38:16.749091 4692 net.cpp:110] fc6 -> fc6I0721 10:38:17.160079 4692 net.cpp:125] Top shape: 256 4096 1 1 (1048576)I0721 10:38:17.160148 4692 net.cpp:151] fc6 needs backward computation.I0721 10:38:17.160166 4692 net.cpp:74] Creating Layer relu6I0721 10:38:17.160177 4692 net.cpp:84] relu6 <- fc6I0721 10:38:17.160190 4692 net.cpp:98] relu6 -> fc6 (in-place)I0721 10:38:17.160202 4692 net.cpp:125] Top shape: 256 4096 1 1 (1048576)I0721 10:38:17.160212 4692 net.cpp:151] relu6 needs backward computation.I0721 10:38:17.160222 4692 net.cpp:74] Creating Layer drop6I0721 10:38:17.160230 4692 net.cpp:84] drop6 <- fc6I0721 10:38:17.160238 4692 net.cpp:98] drop6 -> fc6 (in-place)I0721 10:38:17.160258 4692 net.cpp:125] Top shape: 256 4096 1 1 (1048576)I0721 10:38:17.160265 4692 net.cpp:151] drop6 needs backward computation.I0721 10:38:17.160277 4692 net.cpp:74] Creating Layer fc7I0721 10:38:17.160286 4692 net.cpp:84] fc7 <- fc6I0721 10:38:17.160295 4692 net.cpp:110] fc7 -> fc7I0721 10:38:17.342094 4692 net.cpp:125] Top shape: 256 4096 1 1 (1048576)I0721 10:38:17.342157 4692 net.cpp:151] fc7 needs backward computation.I0721 10:38:17.342175 4692 net.cpp:74] Creating Layer relu7I0721 10:38:17.342185 4692 net.cpp:84] relu7 <- fc7I0721 10:38:17.342198 4692 net.cpp:98] relu7 -> fc7 (in-place)I0721 10:38:17.342208 4692 net.cpp:125] Top shape: 256 4096 1 1 (1048576)I0721 10:38:17.342217 4692 net.cpp:151] relu7 needs backward computation.I0721 10:38:17.342228 4692 net.cpp:74] Creating Layer drop7I0721 10:38:17.342236 4692 net.cpp:84] drop7 <- fc7I0721 10:38:17.342245 4692 net.cpp:98] drop7 -> fc7 (in-place)I0721 10:38:17.342254 4692 net.cpp:125] Top shape: 256 4096 1 1 (1048576)I0721 10:38:17.342262 4692 net.cpp:151] drop7 needs backward computation.I0721 10:38:17.342274 4692 net.cpp:74] Creating Layer fc8I0721 10:38:17.342283 4692 net.cpp:84] fc8 <- fc7I0721 10:38:17.342291 4692 net.cpp:110] fc8 -> fc8I0721 10:38:17.343199 4692 net.cpp:125] Top shape: 256 22 1 1 (5632)I0721 10:38:17.343214 4692 net.cpp:151] fc8 needs backward computation.I0721 10:38:17.343231 4692 net.cpp:74] Creating Layer lossI0721 10:38:17.343240 4692 net.cpp:84] loss <- fc8I0721 10:38:17.343250 4692 net.cpp:84] loss <- labelI0721 10:38:17.343264 4692 net.cpp:151] loss needs backward computation.I0721 10:38:17.343305 4692 net.cpp:173] Collecting Learning Rate and Weight Decay.I0721 10:38:17.343327 4692 net.cpp:166] Network initialization done.I0721 10:38:17.343335 4692 net.cpp:167] Memory required for Data 1073760256

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