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少年们在船上气得大骂，看得人跺脚大笑，岸边、湖里都是乱糟糟的，不成个样子。两位情投意合的青年阿超和佳佳由热恋到谈婚论嫁，为此阿超的父亲老吴特地从香港赶到北京，与未来的亲家、儿媳相会。不料，佳佳的母亲雪莹与老吴在儿女婚后留京与去港的问题上发生了争执，双方不欢而散。为了儿子的婚事，老吴被迫二次登门进行情感磨合……这一切又都被深爱着雪莹的邻居老黄看在眼里，他误以为老吴频频出入雪莹家，是对雪莹有意、是想“横刀夺爱”，于是“醋劲儿”大发，先是与佳佳合计为老吴介绍对象，接着又乔装成雪莹的东北老乡，编排有关雪莹的谣言，几乎将老吴吓跑。而雪莹为留住女儿，也自做主张欲给佳佳找寻新男友……虽然冲突不断，但结局则是皆大欢喜：佳佳与阿超由误解到谅解更加情深意长，老吴、老黄和雪莹也彼此袒露胸怀尽释前嫌。新春佳节到来之际，在佳佳和阿超、雪莹与老黄一同举行的婚礼上，老吴也带着自己中意的女友从香港赶到。三对有情人在除夕的喜宴上举杯畅饮，共祝新春。所以，月下写了删，删了又写，再删再写再删……，在死劲折腾自己。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 ~所以他选用了全部的骑兵，这样速度上能够有保证。19. Code: Attention.