MNN
CNTK
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| MNN | CNTK | |
|---|---|---|
| 3 | 1 | |
| 8,293 | 17,435 | |
| 1.3% | 0.0% | |
| 8.1 | 0.0 | |
| 3 days ago | about 1 year ago | |
| C++ | C++ | |
| - | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
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
CNTK
What are some alternatives?
tensorflow - An Open Source Machine Learning Framework for Everyone
Theano - Theano was a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. It is being continued as PyTensor: www.github.com/pymc-devs/pytensor
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.
ncnn - ncnn is a high-performance neural network inference framework optimized for the mobile platform
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
ML-examples - Arm Machine Learning tutorials and examples
Caffe - Caffe: a fast open framework for deep learning.
oneflow - OneFlow is a deep learning framework designed to be user-friendly, scalable and efficient.
Keras - Deep Learning for humans
serving - A flexible, high-performance serving system for machine learning models
scikit-learn - scikit-learn: machine learning in Python