DALI and NGC¶
DALI is preinstalled in the NVIDIA GPU Cloud TensorFlow, PyTorch, and MXNet containers in versions 18.07 and later.
Installing prebuilt DALI packages¶
One or more of the following deep learning frameworks:
Execute the below command CUDA 9.0 based build:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/cuda/9.0 nvidia-dali
Starting DALI 0.8.0 for CUDA 10.0 based build use:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/cuda/10.0 nvidia-dali
Starting 0.6.1 the
nvidia-dali package no longer contains prebuilt versions of the DALI TensorFlow plugin, so you need to install DALI TensorFlow plugin for the currently installed version of TensorFlow:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/cuda/9.0 nvidia-dali-tf-plugin
Starting DALI 0.8.0 for CUDA 10.0 based build execute:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/cuda/10.0 nvidia-dali-tf-plugin
Installing this package will install
nvidia-dali and its dependencies, if these dependencies are not already installed. The package
tensorflow-gpu must be installed before attempting to install
nvidia-dali-tf-plugin has a strict requirement with
nvidia-dali as its exact same version.
nvidia-dali-tf-plugin at its latest version will replace any older
nvidia-dali versions already installed with the latest.
To work with older versions of DALI, provide the version explicitly to the
pip install command.
OLDER_VERSION=0.6.1 pip install --extra-index-url https://developer.download.nvidia.com/compute/redist nvidia-dali-tf-plugin==$OLDER_VERSION
Pre-built packages in Watson Machine Learing Community Edition¶
IBM publishes pre-built DALI packages as part of Watson Machine Learning Community Edition (WML CE). WML CE includes conda packages for both IBM Power and x86 systems. The initial release includes DALI 0.9 built against CUDA 10.1 and with TensorFlow support. Other versions may be added in the future. The WML CE conda channel also includes the CUDA prerequisites for DALI.
After installing conda and configuring the WML CE conda channel (see WML CE installation) you can install DALI:
$ conda create -y -n my-dali-env python=3.6 dali $ conda activate my-dali-env (my-dali-env) $ conda list dali ... dali 0.9 py36_666ce55_1094.g70c071f
Nightly and weekly release channels¶
While binaries available to download from nightly and weekly builds include most recent changes available in the GitHub some functionalities may not work or provide inferior performance comparing to the official releases. Those builds are meant for the early adopters seeking for the most recent version available and being ready to boldly go where no man has gone before.
It is recommended to uninstall regular DALI and TensorFlow plugin before installing nvidia-dali-nightly or nvidia-dali-weekly as they are installed in the same path
To access most recent nightly builds please use flowing release channel:
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/nightly/cuda/9.0 nvidia-dali-nightly pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/nightly/cuda/9.0 nvidia-dali-tf-plugin-nightly
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/nightly/cuda/10.0 nvidia-dali-nightly pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/nightly/cuda/10.0 nvidia-dali-tf-plugin-nightly
Also, there is a weekly release channel with more thorough testing (only CUDA10 builds are provided there):
pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/weekly/cuda/10.0 nvidia-dali-weekly pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/weekly/cuda/10.0 nvidia-dali-tf-plugin-weekly