aimet
qkeras
| aimet | qkeras | |
|---|---|---|
| 2 | 3 | |
| 1,911 | 522 | |
| 2.5% | 1.1% | |
| 9.6 | 6.6 | |
| 1 day ago | about 1 month ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | Apache License 2.0 |
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aimet
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I was looking for some great quantization open-source libraries that could actually be applied in production (both edge or cloud CPU/GPU). Do you know if I am missing any good libraries?
Qualcomm AIMET | Advanced quantization and compression techniques for trained neural network models
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Model/Tool to use on Jetson for efficient Quantization/Pruning
Qualcomm AIMET may help you
qkeras
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How to build FPGA-based ML accelerator?
I would check out hls4ml. It's an open source project made by/for people at CERN to convert neural networks created in Python using QKeras (a quantization extension of Keras) into HLS, with Vivado HLS being the most well supported. There are some caveats though, and a fellow student and I have had trouble getting the generated HLS to match the Keras model and be feasible to synthesize, but it seems to work well for smaller neural networks.
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FPGA Neural Network
For quantization-aware training, there's also a tool we integrate with called qkeras: https://github.com/google/qkeras/tree/master/qkeras
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[D] How to Quantize a CNN; And how to deal with a professor...
Brevitas appears to be what you're looking for. I haven't used that but developed something similar myself for a previous project. You could take a look at https://github.com/google/qkeras too
What are some alternatives?
tkDNN - Deep neural network library and toolkit to do high performace inference on NVIDIA jetson platforms
model-optimization - A toolkit to optimize ML models for deployment for Keras and TensorFlow, including quantization and pruning.
ludwig - Low-code framework for building custom LLMs, neural networks, and other AI models
hls4ml - Machine learning on FPGAs using HLS
open-lpr - Open Source and Free License Plate Recognition Software
conifer - Collect and revisit web pages.
horovod - Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
TensorRT - NVIDIA® TensorRT™ is an SDK for high-performance deep learning inference on NVIDIA GPUs. This repository contains the open source components of TensorRT.
d2l-en - Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
distiller - Neural Network Distiller by Intel AI Lab: a Python package for neural network compression research. https://intellabs.github.io/distiller
Keras - Deep Learning for humans