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阿泽（黄成麟 饰）陷入一场追杀危机，为躲避神秘组织的追捕，慌不择路的阿泽逃上了去往彭水的旅游巴士，并“邂逅”了女主角阿娇（南笙 饰）。一段时日后，正当他渐渐爱上阿娇的时候，却发现这一切都是个“阴谋”，而这场“阴谋”在彭水这个爱情治愈圣地却奇妙地发生着令人意想不 到的变化…《丹程》以朱丹的旅程为线索，通过对泰国多位人物的深度访谈和生活体验，呈现差异文化下平凡卓越的人生故事，与观众一起从全新的角度探讨生命的意义。节目中选择了以普通人为探访对象，展现给观众的是陌生文化下熟悉且亲切的普通人的日常生活。节目全程无台本设定，全部内容皆取自朱丹与探访对象共同生活过程中的真实呈现。《犬爱》致那些不曾被发现的爱。男主人公陈如风家境殷实，却因着父母终日的忙碌而缺失“陪伴”，从小感受不到家庭的温暖和父母的爱。内心空虚、混沌的他，决定去寻找他心中盼望的那份“爱”。而被主人驱逐门外的流浪狗“小家伙”，在独自流浪中遇到了陈如风。在给予小家伙关爱和保护的过程中，陈如风却感受到了“爱”的温度 。他该如何踏上回家的路？什么是犬爱，他又是否寻找到了心中盼望的那份爱？1948年秋，上海。一份中共地下党名单，被递交到国民党军情第八局局长谭忠恕的办公桌上，供出名单的犯人，被安排住进了和平饭店，等候谭忠恕读过口供后再做指示。此人自称还有更为重大的机密，只能面告谭忠恕——他能指认一个人，一个隐藏在第八局多年的中共特工。就在谭忠恕展开名单的一瞬间，他身边服务数年之久的女机要秘书，突然拿起墨汁泼在名单上。那灯谜一般的名单，已经难以辨认，谭立刻派人去和平饭店，却发现那变节者也已被神秘杀死。谭忠恕端详着残缺的金字塔形的名单，塔尖是个他熟悉代号——水手，那是他的夙敌。谭根据名单上残存的三个名字布置搜捕，中共地下党在上海的网络，即将被撕开一个口子。他要迅速撕开这口子，顺藤摸瓜把水手找出来。还有另一个模糊的影子在谭的脑海里挥之不去，那个变节者曾自称能指认一个中共打进来的卧底。而现在变节者死了，留下一个谜：究竟是否存在这个卧底，如果存在的话——会是谁？这一整天，第八局机关一片忙乱。特务们在集合，准备听候谭忠恕的命令开始搜捕。总务处是最忙的部门，公事堆积如山。和平饭店的房费、Sorry to force a wave of chicken soup. Originally, I planned to write a machine learning series last year, but after writing three articles for work and physical reasons, there was no more. In the first half of this year, I was tired to death after doing a big project. In the second half of this year, I just took a breath of relief, so the follow-up that I owed before will definitely continue to be even more. In order not to let everyone worship blindly, I decided to write a series of in-depth study, one article per week, which will end in about three months. Teach Xiaobai how to get started. And finished! All! No! Fei! ! It is not simply to write demo and tuning parameters that are available on the Internet. Reject demo, start with me! If you don't understand, please leave a message under my article. I will try my best to reply when I see it. This series will mainly adopt the in-depth learning framework of PaddlaPaddle, and will compare the advantages and disadvantages of Keras, TensorFlow and MXNET (because I have only used these four frameworks, there are too many people writing TensorFlow, and I am using PaddlePaddle well at present, so I decided to start with this). All codes will be put on github (link: https://github.com/huxiaoman7/PaddlePaddle_code). Welcome to mention issue and star. At present, only the first article () has been written, and there will be more in-depth explanation and code later. At present, I have made a simple outline. If you are interested in the direction, you can leave me a message, and I will refer to the addition ~