MNN
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MNN
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[D][R] Deploying deep models on memory constrained devices
However, I am looking on this subject through the problem of training/finetuning deep models on the edge devices, being increasingly available thing to do. Looking at tflite, alibaba's MNN, mit-han-lab's tinyengine etc..
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What’s New in TensorFlow 2.10?
There are a ton of mobile deployment options that support PyTorch+TF models. It's hard to argue TFLite is the best.
https://github.com/alibaba/MNN
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Newbie having error code of cannot build selected target abi x86 no suitable splits configured
I found a solution on GitHub check your app's build.gradle, defaultConfig section - you need to add x86 to your ndk abiFilters ndk.abiFilters 'armeabi-v7a','arm64-v8a', 'x86' GitHub Hope it will help. You have to find that file and edit it as given here
signatory
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[R] Authors Claim to Have "Solved" MNIST and CIFAR
As it happens, I know quite a lot about signatures. I spent half my PhD working on them. For example I am the author of the most popular library for computing signatures, which involved coming up with some new asymptotically optimal algorithms for computing them. So that's my credentials out the way.
What are some alternatives?
tensorflow - An Open Source Machine Learning Framework for Everyone
oneflow - OneFlow is a deep learning framework designed to be user-friendly, scalable and efficient.
TNN - TNN: developed by Tencent Youtu Lab and Guangying Lab, a uniform deep learning inference framework for mobile、desktop and server. TNN is distinguished by several outstanding features, including its cross-platform capability, high performance, model compression and code pruning. Based on ncnn and Rapidnet, TNN further strengthens the support and performance optimization for mobile devices, and also draws on the advantages of good extensibility and high performance from existed open source efforts. TNN has been deployed in multiple Apps from Tencent, such as Mobile QQ, Weishi, Pitu, etc. Contributions are welcome to work in collaborative with us and make TNN a better framework.
serving - A flexible, high-performance serving system for machine learning models
ncnn - ncnn is a high-performance neural network inference framework optimized for the mobile platform
ML-examples - Arm Machine Learning tutorials and examples
CNTK - Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit
NeuralCDE - Code for "Neural Controlled Differential Equations for Irregular Time Series" (Neurips 2020 Spotlight)
learning_with_signatures - Learning with Signatures