PyTorch Release 18.05
The NVIDIA container image of PyTorch, release 18.05, 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) 9.0.333 (see section 2.3.1)
- NVIDIA CUDA® Deep Neural Network library™ (cuDNN) 7.1.2
- NCCL 2.1.15 (optimized for NVLink™ )
- Caffe2 0.8.1
Release 18.05 is based on CUDA 9, which requires NVIDIA Driver release 384.xx.
Key Features and Enhancements
- PyTorch container image version 18.05 is based on PyTorch 0.4.0.
- Includes Caffe2 0.8.1. For more information, see PyTorch and Caffe2 repos getting closer together.
- APEx, an extension providing utilities for FP16 and multi-gpu training. For more information, see APEx: A PyTorch Extension and APEx.
- Ubuntu 16.04 with April 2018 updates
- Some mixed-precision models might encounter a crash due to a new FP16 overflow check added in PyTorch. We have an upstream fix submitted with PR 7382 and should be resolved in a future container.
- There is a minor performance regression with the imagenet sample in
/opt/pytorch/examples/imagnetfor some network architectures on multi-gpu cases. This regression will be fixed in the next release.