Hessian AWare Quantization HAWQ is an advanced quantization library written for PyTorch. HAWQ enables low-precision and mixed-precision uniform quantization, with direct hardware implementation through TVM. Installation PyTorch version >= 1.4.0 Python version >= 3.6 For training new models, you’ll also need NVIDIA GPUs and NCCL To install HAWQ and develop locally: git clone https://github.com/Zhen-Dong/HAWQ.git cd HAWQ pip install -r requirements.txt Getting Started Quantization-Aware Training An example to run uniform 8-bit quantization for resnet50 on ImageNet. export CUDA_VISIBLE_DEVICES=0 python quant_train.py -a […]

AALpy AALpy is a light-weight active automata learning library written in pure Python. By implementing a single method and a few lines of configuration, you can start learning automata. Whether you work with regular languages or you would like to learn models of reactive systems, AALpy supports a wide range of modeling formalisms, including deterministic, non-deterministic, and stochastic automata. You can use it to learn deterministic finite automata, Moore machines, and Mealy machines of deterministic systems. If the system that […]

Robotics Toolbox for Python. Synopsis This toolbox brings robotics-specific functionality to Python, and leveragesPython’s advantages of portability, ubiquity and support, and the capability ofthe open-source ecosystem for linear algebra (numpy, scipy), graphics(matplotlib, three.js, WebGL), interactive development (jupyter, jupyterlab,mybinder.org), and documentation (sphinx). The Toolbox provides tools for representing the kinematics and dynamics ofserial-link manipulators – you can easily create your own in Denavit-Hartenbergform, import a URDF file, or use over 30 supplied models for well-knowncontemporary robots from Franka-Emika, Kinova, Universal Robotics, […]