DALI is preinstalled in the NVIDIA GPU Cloud TensorFlow, PyTorch, and MXNet containers in versions 18.07 and later.

Installing prebuilt DALI packages


  1. Linux x64.

  2. NVIDIA Driver supporting CUDA 9.0 or later (i.e., 384.xx or later driver releases).

  3. One or more of the following deep learning frameworks:


Execute the below command CUDA 9.0 based build:

pip install --extra-index-url nvidia-dali

Starting DALI 0.8.0 for CUDA 10.0 based build use:

pip install --extra-index-url 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 nvidia-dali-tf-plugin

Starting DALI 0.8.0 for CUDA 10.0 based build execute:

pip install --extra-index-url 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.


The package nvidia-dali-tf-plugin has a strict requirement with nvidia-dali as its exact same version. Thus, installing 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.

pip install --extra-index-url 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

Nightly builds

To access most recent nightly builds please use flowing release channel:

  • for CUDA9

pip install --extra-index-url nvidia-dali-nightly
pip install --extra-index-url nvidia-dali-tf-plugin-nightly
  • for CUDA10

pip install --extra-index-url nvidia-dali-nightly
pip install --extra-index-url nvidia-dali-tf-plugin-nightly
Weekly builds

Also, there is a weekly release channel with more thorough testing (only CUDA10 builds are provided there):

pip install --extra-index-url nvidia-dali-weekly
pip install --extra-index-url nvidia-dali-tf-plugin-weekly