PyTorch Release 18.08
The NVIDIA container image of PyTorch, release 18.08, 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.
The container also includes the following:
- Ubuntu 16.04 including Python 3.6 environment
- NVIDIA CUDA 9.0.176 (see Errata section and 2.1) including CUDA® Basic Linear Algebra Subroutines library™ (cuBLAS) 9.0.425
- NVIDIA CUDA® Deep Neural Network library™ (cuDNN) 7.2.1
- NCCL 2.2.13 (optimized for NVLink™ )
- Caffe2 0.8.1
- DALI 0.1.2 Beta
- Tensor Core Optimized Examples:
Driver Requirements
Release 18.08 is based on CUDA 9, which requires NVIDIA Driver release 384.xx.
Key Features and Enhancements
This PyTorch release includes the following key features and
enhancements.
- PyTorch container image version 18.08 is based on PyTorch 0.4.1. PyTorch 0.4.1 is released and included with this container. See the release notes at https://github.com/pytorch/pytorch/releases for significant changes from PyTorch 0.4.
- Apex is now entirely Python for improved compatibility. Previous versions of Apex will not work with PyTorch 0.4.1 or newer versions.
- New ops in 18.08: torch.pinverse, torch.unique, torch.erfc, torch.isinf, torch.isfinite, torch.reshape_as.
- Support for cross-device gradient clipping.
- torch.svd and torch.eig in CUDA have been fixed, previously they could return incorrect results.
- An implementation of GNMT v2. The GNMT v2 model is similar to the one discussed in the Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation paper.
- Latest version of cuDNN 7.2.1.
- Latest version of DALI 0.1.2 Beta.
- Added support for the Tensor Core Optimized Example: PyTorch GNMT model
- Ubuntu 16.04 with July 2018 updates