OneFlow is a deep learning framework and distributed execution engine designed for building, training, and deploying neural network architectures. It functions as a scalable neural network library that allows for the development of deep learning models and their execution across distributed hardware.
The project includes a machine learning graph compiler used to optimize neural network execution graphs. This allows for the acceleration of model performance and the reduction of latency during both training and inference.
The framework covers broad capability areas including large-scale model training, deep learning performance optimization, and the deployment of machine learning models to production environments. It provides a high-level interface for rapid prototyping and the ability to scale model execution across parallel environments.
