Shypd.aiThe largest open index of AI toolswincnn is an Open Source & Models tool that generates Winograd minimal convolution algorithms for convolutional neural networks. It is a Python module designed to compute these algorithms efficiently.
Trending
About
wincnn is a Python module specifically designed to generate minimal Winograd convolution algorithms, which are crucial for optimizing convolutional neural networks. This tool implements the algorithms proposed in the research paper "Fast Algorithms for Convolutional Neural Networks" by Lavin and Gray (CVPR 2016). It provides symbolic computation capabilities, ensuring exact results for the transforms. Users can compute transforms for various F(m,r) configurations, including examples like F(2,3), F(4,3), and F(6,3), and also generate algorithms for linear convolution. The module requires Python 3.8 or higher and SymPy 1.9 or higher for its operation, making it a valuable resource for developers and researchers working on neural network optimization.
Capabilities
Pricing & Plans
Open Source
Free
FAQs
Trending
