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

Installing prebuilt DALI packages



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


nvidia-dali package contains prebuilt versions of the dali tensorflow plugin for several versions of tensorflow. Since release 0.6.1 there is also a possibility to install dali tensorflow plugin for the currently installed version of tensorflow, thus allowing forward compatibility:

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

Installing this package will install nvidia-dali and its dependencies if 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, please provide the version explicitely to the pip install command.

pip install --extra-index-url nvidia-dali-tf-plugin==$OLDER_VERSION

Compiling DALI from source (bare metal)


Linux x64  
GCC 4.9.2 or later  
Boost 1.66 or later Modules: preprocessor
GCC 4.9.2 or later NVIDIA CUDA 9.0 CUDA 8.0 compatibility is provided unofficially
nvJPEG library This can be unofficially disabled. See below
version 2 or later
(version 3 or later is required for TensorFlow TFRecord file format support)
CMake 3.5 or later  
libjpeg-turbo 1.5.x or later This can be unofficially disabled. See below
FFmpeg 3.4.2 or later We recommend using version 3.4.2 compiled following the instructions below.
OpenCV 3 or later
We recommend using version 3.4+, however previous versions are also compatible.
OpenCV 2.x compatibility is provided unofficially
(Optional) liblmdb 0.9.x or later  
One or more of the following Deep Learning frameworks:


TensorFlow installation is required to build the TensorFlow plugin for DALI


Items marked “unofficial” are community contributions that are believed to work but not officially tested or maintained by NVIDIA.


This software uses code of FFmpeg licensed under the LGPLv2.1 and its source can be downloaded

FFmpeg was compiled using the following command line:

./configure \
  --prefix=/usr/local \
  --disable-static \
  --disable-all \
  --disable-autodetect \
  --disable-iconv \
  --enable-shared \
  --enable-avformat \
  --enable-avcodec \
  --enable-avfilter \
  --enable-protocol=file \
  --enable-demuxer=mov,matroska \
  --enable-bsf=h264_mp4toannexb,hevc_mp4toannexb && \

Get the DALI source

git clone --recursive
cd dali

Make the build directory

mkdir build
cd build

Compile DALI

To build DALI without LMDB support:

cmake ..
make -j"$(nproc)"

To build DALI with LMDB support:

cmake -DBUILD_LMDB=ON ..
make -j"$(nproc)"

To build DALI using Clang (experimental):


This build is experimental and it is not maintained and tested like the default configuration. It is not guaranteed to work. We recommend using GCC for production builds.

make -j"$(nproc)"

Optional CMake build parameters:

  • BUILD_PYTHON - build Python bindings (default: ON)
  • BUILD_TEST - include building test suite (default: ON)
  • BUILD_BENCHMARK - include building benchmarks (default: ON)
  • BUILD_LMDB - build with support for LMDB (default: OFF)
  • BUILD_NVTX - build with NVTX profiling enabled (default: OFF)
  • BUILD_TENSORFLOW - build TensorFlow plugin (default: OFF)
  • WERROR - treat all build warnings as errors (default: OFF)
  • (Unofficial) BUILD_JPEG_TURBO - build with libjpeg-turbo (default: ON)
  • (Unofficial) BUILD_NVJPEG - build with nvJPEG (default: ON)

Install Python bindings

pip install dali/python