Microsoft is announcing the support for PyTorch 1.0 in Azure Machine Learning Services and Data Science Virtual Machine.
PyTorch 1.0 takes the modular, production-oriented capabilities from Caffe2 and ONNX and combines them with PyTorch's existing flexible, research-focused design to provide a fast, seamless path from research prototyping to production deployment for a broad range of AI projects. With PyTorch 1.0, AI developers can both experiment rapidly and optimize performance through a hybrid front end that seamlessly transitions between imperative and declarative execution modes. Data Scientists can develop models in PyTorch 1.0, which are saved in ONNX as the native format and directly use them in applications built on Windows ML and other platforms that support ONNX.
Read about it in the Azure blog.