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过年在即，龙门镖局的各位伙计准备回家过年，三金和秋月带着糊糊回广东，璎珞受八斗的邀请回东北老家过年，敬琪和青橙则各自回家，恭叔独自留下看家。大家走后，恭叔在院里耍枪，围墙上有人叫好，没等恭叔反应过来，一群蒙面人已经将他包围。不仅是恭叔，其与众人也在返家路上或被埋伏或被各个击破，最终被胁迫回了镖局。众人又在镖局碰头了，这次来的人，声名显赫，他交给大家的任务看似简单，实则充满了杀机，一旦接手，三金随时有可能身败名裂、倾家荡产。三金为了镖局的未来和大家安的危，毅然接受了挑战。这一镖的终点，是三金的家，平安票号的总部，七天之内必须送到，此时，离家还有三千里。三金独自一人，赶着镖车踏上未知的旅程。《最后的格格》主要讲了清朝末年，裕王府的云香格格和戏子温良玉相爱，二人私奔那一晚，正好隆裕太后宣布退位共和，被乱民冲散，云香为王府的仇人方天羽所救，良玉流落街头，二人九死一生，再重逢却因为天羽对云香的爱而几次分离，结果云香为了照顾发疯的母亲而堕落，良玉放弃好不容易得来的工作，一直相随，最后把云香拉出泥藻，没想到那一晚，天羽居然制造了一场阴谋，将良玉扔入河中，云香得知良玉已死，刺杀天羽，结果被抓进牢里成了死囚，大亨沈世豪一直喜欢云香，买通了狱官，以死囚换人，将她救出，这时云香发现自己怀了良玉的孩子，为了报答世豪的救命之恩，她成了他的二姨太，十八年后，良玉回来了，他摇身一变成为北京城最大的黑帮老大，前夫有情后夫有意，云香该如何抉择？而此时，云香的儿子沈梓康已经长大，不明身世的他成了巡捕房的大队长，他的目标就是抓到良玉，更加巧的是，梓康爱上了天羽的女儿语嫣，而叛逆的语嫣却一心喜欢比她大二十多岁的良玉，所有的爱、恨、情、仇在一刹那全部爆发了……这是一部经典的诙谐浪漫喜剧，也可以看作是农村版的花样少男少女。女主Taddao是父亲的私生女，父亲过世后，她的家族身份不能得到正式承认。为了找到父亲的遗嘱证明自己是Bussaya家族的人，她女扮男装变成Tad回到大宅，寻找可以证明自己身份的证据，而男主Por则是她的守护天使，在她遇到困难和危难时，总是第一个帮助她，拯救她，爱意渐渐萌芽，究竟最后Todda能找到遗嘱证明自己的身份吗？她和守护天使的爱情会圆满结局吗？月明如水，青竹摇曳，刀客轻柔的抱起东方姑娘，一步步走下黑木崖。　　当温厚的盾面对卑劣的矛，当父亲是那个盾儿子是那个矛，会怎样？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 ~So far, the two methods for iPhone and iPad to enter the recovery mode have been introduced.