TensorFlow Release 18.04

The NVIDIA container image of TensorFlow, release 18.04, is available.

Contents of TensorFlow

This container image contains the complete source of the version of NVIDIA TensorFlow in /opt/tensorflow. It is pre-built and installed as a system Python module.

To achieve optimum TensorFlow performance, for image based training, the container includes a sample script that demonstrates efficient training of convolutional neural networks (CNNs). The sample script may need to be modified to fit your application.

The container also includes the following:

Driver Requirements

Release 18.04 is based on CUDA 9, which requires NVIDIA Driver release 384.xx.

Key Features and Enhancements

This TensorFlow release includes the following key features and enhancements.
  • TensorFlow container image version 18.04 is based on TensorFlow 1.7.0.
  • Added the Mellanox user-space InfiniBand driver to the container.
  • Latest version of MLNX_OFED 3.4
  • Added support for TensorRT integration in TensorFlow. For functionality details, see TensorRT Integration Speeds Up TensorFlow Inference and the example in the nvidia-examples/tftrt directory.
  • Improved nvidia_examples/nvcnn.py and nvcnn_hvd.py to ensure ResNet-50 model converges correctly out of the box. See Changelog at the top of nvidia_examples/nvcnn.py for more details.
  • Enabled Tensor Op math for cuDNN-based RNNs in FP16 precision. This is enabled by default, but can be disabled by setting the environment variable TF_DISABLE_CUDNN_RNN_TENSOR_OP_MATH=1.
  • Includes integration with TensorRT 3.0.4
  • Latest version of NCCL 2.1.15
  • Ubuntu 16.04 with March 2018 updates


Starting with the next major version of CUDA release, we will no longer provide Python 2 containers and will only maintain Python 3 containers.

Known Issues

There is a degraded performance for graph construction time of grouped convolutions. For more information, see Support for depthwise convolution by groups.