PyTorch Release 18.11

The NVIDIA container image for PyTorch, release 18.11, is available.

Contents of PyTorch

This container image contains the complete source of the version of PyTorch in /opt/pytorch. It is pre-built and installed in the pytorch-py3.6 Conda™ environment in the container image.

Driver Requirements

Release 18.11 is based on CUDA 10, which requires NVIDIA Driver release 410.xx. However, if you are running on Tesla (Tesla V100, Tesla P4, Tesla P40, or Tesla P100), you may use NVIDIA driver release 384. For more information, see CUDA Compatibility and Upgrades.

Key Features and Enhancements

This PyTorch release includes the following key features and enhancements.
  • PyTorch container image version 18.11 is based on PyTorch v0.4.1+ with up-to-date features from the PyTorch v1.0 preview (master branch up to PR 11834). PyTorch 0.4.1+ is released and included with this container.
  • Latest version of NCCL 2.3.7.
  • Latest version of NVIDIA cuDNN 7.4.1.
  • Latest version of TensorRT 5.0.2
  • Latest version of DALI 0.4.1 Beta.
  • Ubuntu 16.04 with October 2018 updates

Tensor Core Examples

Known Issues

There is a known bug when using persistent batch normalization kernels. If you are experiencing a drop in predictive power during testing and validation, the recommended workaround is to not add the .eval() flag on your model when doing testing or validation.