Compiling DALI from source¶
Compiling DALI from source (using Docker builder) - recommended¶
Following these steps, it is possible to recreate Python wheels in a similar fashion as we provide as an official prebuild binary.
Prerequisites¶
Linux x64 |
|
Follow installation guide and manual at the link (version 17.05 or later is required). |
Building Python wheel and (optionally) Docker image¶
Change directory (cd
) into Docker directory and run ./build.sh
. If needed, set the following environment variables:
PYVER - Python version. Default is
2.7
.CUDA_VERSION - CUDA toolkit version (9 for 9.0 or 10 for 10.0). Default is
10
.NVIDIA_BUILD_ID - Custom ID of the build. Default is
1234
.CREATE_WHL - Create a standalone wheel. Default is
YES
.CREATE_RUNNER - Create Docker image with cuDNN, CUDA and DALI installed inside. It will create the
Docker_run_cuda
image, which needs to be run usingnvidia-docker
and DALI wheel in thewheelhouse
directory under$DALI_BUILD_FLAVOR - adds a suffix to DALI package name and put a note about it in the whl package description, i.e. nightly will result in the nvidia-dali-nightly
CMAKE_BUILD_TYPE - build type, available options: Debug, DevDebug, Release, RelWithDebInfo. Default is
Release
.BUILD_INHOST - ask docker to mount source code instead of copying it. Thank to that consecutive builds are resuing existing object files and are faster for the development. Uses $DALI_BUILD_DIR as a directory for build objects. Default is
YES
.REBUILD_BUILDERS - if builder docker images need to be rebuild or can be reused from the previous build. Default is
NO
.REBUILD_MANYLINUX - if manylinux base image need to be rebuild. Default is
NO
.DALI_BUILD_DIR - where DALI build should happen. It matters only bit the in-tree build where user may provide different path for every python/CUDA version. Default is
build-docker-${CMAKE_BUILD_TYPE}-${PYV}-${CUDA_VERSION}
.
It is worth to mention that build.sh should accept the same set of environment variables as the project CMake.
The recommended command line is:
PYVER=X.Y CUDA_VERSION=Z ./build.sh
For example:
PYVER=3.6 CUDA_VERSION=10 ./build.sh
Will build CUDA 10 based DALI for Python 3.6 and place relevant Python wheel inside DALI_root/wheelhouse
Compiling DALI from source (bare metal)¶
Prerequisites¶
Required Component |
Notes |
---|---|
Linux x64 |
|
GCC 4.9.2 or later |
|
Boost 1.66 or later |
Modules: preprocessor. |
CUDA 8.0 compatibility is provided unofficially. |
|
This can be unofficially disabled. See below. |
|
Version 2 or later
(Version 3 or later is required for TensorFlow TFRecord file format support).
|
|
CMake 3.11 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 |
Supported version: 3.4 |
(Optional) liblmdb 0.9.x or later |
|
|
Note
TensorFlow installation is required to build the TensorFlow plugin for DALI.
Note
Items marked “unofficial” are community contributions that are believed to work but not officially tested or maintained by NVIDIA.
Note
This software uses the FFmpeg licensed code under the LGPLv2.1. Its source can be downloaded from here.
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 && \
make
Get the DALI source¶
git clone --recursive https://github.com/NVIDIA/dali
cd dali
Make the build directory¶
mkdir build
cd build
Compile DALI¶
Building DALI without LMDB support:¶
cmake ..
make -j"$(nproc)"
Building DALI with LMDB support:¶
cmake -DBUILD_LMDB=ON ..
make -j"$(nproc)"
Building DALI using Clang (experimental):¶
Note
This build is experimental. It is neither maintained nor tested. It is not guaranteed to work. We recommend using GCC for production builds.
cmake -DCMAKE_CXX_COMPILER=clang++ -DCMAKE_C_COMPILER=clang ..
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)BUILD_NVJPEG
- build withnvJPEG
support (default: ON)BUILD_NVOF
- build withNVIDIA OPTICAL FLOW SDK
support (default: ON)BUILD_NVDEC
- build withNVIDIA NVDEC
support (default: ON)BUILD_NVML
- build withNVIDIA Management Library
(NVML
) support (default: ON)WERROR
- treat all build warnings as errors (default: OFF)DALI_BUILD_FLAVOR
- Allow to specify custom name sufix (i.e. ‘nightly’) for nvidia-dali whl package(Unofficial)
BUILD_JPEG_TURBO
- build withlibjpeg-turbo
(default: ON)
Note
DALI release packages are built with the options listed above set to ON and NVTX turned OFF. Testing is done with the same configuration. We ensure that DALI compiles with all of those options turned OFF, but there may exist cross-dependencies between some of those features.
Following CMake parameters could be helpful in setting the right paths:
FFMPEG_ROOT_DIR - path to installed FFmpeg
NVJPEG_ROOT_DIR - where nvJPEG can be found (from CUDA 10.0 it is shipped with the CUDA toolkit so this option is not needed there)
libjpeg-turbo options can be obtained from libjpeg CMake docs page
protobuf options can be obtained from protobuf CMake docs page
Install Python bindings¶
pip install dali/python
Cross-compiling DALI C++ API for aarch64 Linux (Docker)¶
Note
Support for aarch64 Linux platform is experimental. Some of the features are available only for x86-64 target and they are turned off in this build. There is no support for DALI Python library on aarch64 yet. Some Operators may not work as intended due to x86-64 specific implementations.
Build the aarch64 Linux Build Container¶
docker build -t dali_builder:aarch64-linux -f Dockerfile.build.aarch64-linux .
Compile¶
From the root of the DALI source tree
docker run -v $(pwd):/dali dali_builder:aarch64-linux
The relevant artifacts will be in build/install
and build/dali/python/nvidia/dali