PyTorch adds new dev tools as it hits production scale

Stanford, UC Berkeley, Caltech, and other universities are using PyTorch as a fundamental tool for their machine learning (ML) courses; new ecosystem projects have launched to support development on PyTorch; and major cloud platforms have expanded their integration with PyTorch. Everyone in the AI community — including those new to ML development as well as researchers and engineers looking for ways to accelerate their end-to-end workflows — can experiment with PyTorch instantly by visiting pytorch.org and launching a tutorial in Colab. With a hybrid front end that enables tracing and scripting models from eager mode into graph mode, along with a growing set of tools and resources such as PyTorch-BigGraph, BoTorch and Ax, and Tensorboard support, PyTorch is a powerful framework for taking breakthrough research in artificial intelligence to production deployment.

Source: ai.facebook.com