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Source channel @githubtrending · Post #15271 · Nov 5

#cplusplus#arm#baidu#deep_learning#embedded#fpga#mali#mdl#mobile#mobile_deep_learning#neural_network Paddle Lite is a lightweight, high-performance deep learning inference framework designed to run AI models efficiently on mobile, embedded, and edge devices. It supports multiple platforms like Android, iOS, Linux, Windows, and macOS, and languages including C++, Java, and Python. You can easily convert models from other frameworks to PaddlePaddle format, optimize them for faster and smaller deployment, and run them with ready-made examples. This helps you deploy AI applications quickly on various devices with low memory use and fast speed, making it ideal for real-time, resource-limited environments. It also supports many hardware accelerators for better performance. https://github.com/PaddlePaddle/Paddle-Lite

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djangoproject

@djangoproject · Post #577 · 03/02/2018, 07:28 PM

http://www.django-rest-framework.org/api-guide/authentication/#tokenauthentication #Authentication is the mechanism of associating an incoming request with a set of identifying credentials, such as the user the request came from, or the token that it was signed with. The permission and throttling policies can then use those credentials to determine if the request should be permitted. #REST framework provides a number of authentication schemes out of the box, and also allows you to implement custom schemes. #Django_REST_Framework#Django#DRF

djangoproject

@djangoproject · Post #589 · 03/29/2018, 06:38 AM

http://books.agiliq.com/projects/django-api-polls-tutorial/en/latest/ Building #APIs with #Django and #Django_Rest_Framework(#DRF) Introductions Setup, Models and Admin A simple API with pure Django #Serializing and Deserializing Data Views and Generic Views More views and viewsets #Access_Control #Testing and Continuous Integeration Testing and Using API with Postman Documenting APIs (with Swagger and more)