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Source channel @githubtrending · Post #14916 · Jul 5

#haxe#cne#codename_engine#fnf#fnf_engine#fnf_team#fridaynightfunkin Codename Engine is a new, easy-to-use engine for Friday Night Funkin' that makes modding simpler and more flexible. It is still in beta, so some features are missing, but it supports creating and playing mods, modpacks, and even making your own sub-engines with proper credit. You can build it on Windows, Linux, or Mac by following specific steps. The engine is optimized and allows source-like editing without constant recompiling, making it great for both beginners and advanced modders. Using Codename Engine helps you customize your Friday Night Funkin' experience more easily and creatively[1][3][5]. https://github.com/CodenameCrew/CodenameEngine

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djangoproject

@djangoproject · Post #274 · 03/18/2017, 01:48 AM

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https://github.com/riga/tfdeploy Google's TensorFlow framework is taking off big-time now that it's at a full 1.0 release. One common question about it: How can I make use of the models I train in TensorFlow without using TensorFlow itself? #Tfdeploy is a partial answer to that question. It exports a trained TensorFlow model to "a simple #NumPy-based callable," meaning the model can be used in Python with Tfdeploy and the the NumPy math-and-stats library as the only dependencies. Most of the operations you can perform in TensorFlow can also be performed in Tfdeploy, and you can extend the behaviors of the library by way of standard Python metaphors (such as overloading a class). Now the bad news: Tfdeploy doesn't support GPU acceleration, if only because NumPy doesn't do that. Tfdeploy's creator suggests using the gNumPy project as a possible replacement. #Machine_learning

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