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Metro Exodus在外打工的绿叶和立秋接到电报，说是立秋娘得了重病，他们立刻坐上了回家的火车。进家门，却发现老太太身子骨好好的。立秋娘亲自给绿叶洗脚，并在立秋爹坟前把家里的钥匙交给了绿叶。讲述因为28年后现身的亲生父亲，人生开始转变的女人，和她一直隐藏真实面貌的父亲之间的故事。《狼烟》以鄂西山区“红军抗日、解放剿匪”的革命斗争历程为载体，讲述了有着不共戴天之仇的土匪与地主双方，在我党的引导下逐渐从生死对抗转为互伸援手直至冰释前嫌，最终弃暗投明联手粉碎国民党反攻大陆阴谋的故事。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 ~田上酒家菜肴很便宜，每碟最贵不超过五文，但只有很少的量。/sit (sit)