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NVIDIA has created this project to support newer hardware and improved libraries to NVIDIA GPU users who are using TensorFlow 1.x. With release of TensorFlow 2.0, Google announced that new major releases will not be provided on the TF 1.x branch after the release of TF 1.15 on October 14 2019. NVIDIA is working with Google and the community to improve TensorFlow 2.x by adding support for new hardware and libraries. However, a significant number of NVIDIA GPU users are still using TensorFlow 1.x in their software ecosystem. This release will maintain API compatibility with upstream TensorFlow 1.15 release. This project will be henceforth referred to as nvidia-tensorflow.

Link to Tensorflow README

• Ubuntu 18.04 or later (64-bit)
• GPU support requires a CUDA®-enabled card
• For NVIDIA GPUs, the r450 driver must be installed

For wheel installation:

• Python 3.6
• pip 19.0 or later

See the nvidia-tensorflow install guide to use the pip package, to pull and run Docker container, and customize and extend TensorFlow.

NVIDIA wheels are not hosted on PyPI.org. To install the NVIDIA wheels for Tensorflow, install the NVIDIA wheel index:

$ pip install --user nvidia-pyindex

To install the current NVIDIA Tensorflow release:

$ pip install --user nvidia-tensorflow[horovod]

The nvidia-tensorflow package includes CPU and GPU support for Linux.

By using the software you agree to fully comply with the terms and conditions of the SLA (Software License Agreement):

• CUDA – https://docs.nvidia.com/cuda/eula/index.html#abstract

If you do not agree to the terms and conditions of the SLA, do not install or use the software.

Please review the Contribution Guidelines.

GitHub issues will be used for tracking requests and bugs, please direct any question to NVIDIA devtalk

Apache License 2.0