Training a machine learning model in Python is straightforward. Deploying it to production with low latency and no Python dependency is a different challenge.
ONNX (Open Neural Network Exchange) solves this: a standard format for trained models, with ONNX Runtime as the high-performance inference engine supporting C, C++, Java, JavaScript, and Python.
The workflow: train in PyTorch or scikit-learn, export to ONNX, deploy with ONNX Runtime. The same model runs in any language runtime without re-training.
ONNX Runtime's graph optimisations fuse operations, eliminate redundant computations, and apply hardware-specific optimisations automatically. This reduced our inference latency by 35%.
— Dick Bassey | DevDick | 2025