NVIDIA Optimized Deep Learning Framework, powered by Apache MXNet Release Notes

These release notes describe the key features, software enhancements and improvements, known issues, and how to run this container for the 21.09 and earlier releases. The Apache MXNet framework delivers high convolutional neural network performance and multi-GPU training, provides automatic differentiation, and optimized predefined layers. It’s a useful framework for those who need their model inference to “run anywhere”; for example, a data scientist can train a model on a DGX-1 with Volta by writing a model in Python, while a data engineer can deploy the trained model using a Scala API tied to the company’s existing infrastructure. The Optimized Deep Learning Framework container is released monthly to provide you with the latest NVIDIA deep learning software libraries and GitHub code contributions that have been sent upstream; which are all tested, tuned, and optimized.

To see a single view of the supported software and specific versions that come packaged with the frameworks based on the container image, see the Frameworks Support Matrix.