PocketFlow | Automatic Model Compression framework | Machine Learning library

PocketFlow is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch, Tensorflow applications. PocketFlow has no bugs, it has no vulnerabilities and it has medium support. However PocketFlow build file is not available and it has a Non-SPDX License. You can download it from GitHub.

PocketFlow is an open-source framework for compressing and accelerating deep learning models with minimal human effort. Deep learning is widely used in various areas, such as computer vision, speech recognition, and natural language translation. However, deep learning models are often computational expensive, which limits further applications on mobile devices with limited computational resources. PocketFlow aims at providing an easy-to-use toolkit for developers to improve the inference efficiency with little or no performance degradation. Developers only needs to specify the desired compression and/or acceleration ratios and then PocketFlow will automatically choose proper hyper-parameters to generate a highly efficient compressed model for deployment. PocketFlow was originally developed by researchers and engineers working on machine learning team within Tencent AI Lab for the purposes of compacting deep neural networks with industrial applications. For full documentation, please refer to PocketFlow's GitHub Pages. To start with, you may be interested in the installation guide and the tutorial on how to train a compressed model and deploy it on mobile devices. For general discussions about PocketFlow development and directions please refer to PocketFlow Google Group. If you need a general help, please direct to Stack Overflow. You can report issues, bug reports, and feature requests on GitHub Issue Page.