For example, a dynamic neural network model in PyTorch may add and remove hidden layers during training to improve its accuracy and generality. PyTorch recreates the graph on the fly at each ...

Known for its flexibility, ease of use, and GPU acceleration, PyTorch is widely adopted in both research and industry. Its dynamic computation graph helps ... AI models to function on mobile ...

Graph-enhanced ML and graph neural networks, fully integrated with the TigerGraph database, can quickly be used for parallelized graph data processing. The ML Workbench was designed to interoperate ...

Now with all major cloud and chip vendors on board, PyTorch 1.0 could become the foundation for new types of models to emerge given that developers are already familiar with a lot of those practices.