onnxruntime/docs/build/training.md

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Build ONNX Runtime for training

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Contents

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• TOC placeholder {:toc}

CPU

Build Instructions

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To build ORT with training support add --enable_training build instruction.

All other build options are the same for inferencing as they are for training.

Windows

.\build.bat --config RelWithDebInfo --build_shared_lib --parallel --enable_training

The default Windows CMake Generator is Visual Studio 2017, but you can also use the newer Visual Studio 2019 by passing --cmake_generator "Visual Studio 16 2019" to .\build.bat

Linux/macOS

./build.sh --config RelWithDebInfo --build_shared_lib --parallel --enable_training

GPU / CUDA

Prerequisites

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The default NVIDIA GPU build requires CUDA runtime libraries installed on the system:

• CUDA 10.2
• cuDNN 8.0
• NCCL 2.7
• OpenMPI 4.0.4
  • See install_openmpi.sh

These dependency versions should reflect what is in the Dockerfiles.

Build instructions

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1. Checkout this code repo with git clone https://github.com/microsoft/onnxruntime

2. Set the environment variables: adjust the path for location your build machine

   export CUDA_HOME=<location for CUDA libs> # e.g. /usr/local/cuda
   export CUDNN_HOME=<location for cuDNN libs> # e.g. /usr/local/cuda
   export CUDACXX=<location for NVCC> #e.g. /usr/local/cuda/bin/nvcc
   export PATH=<location for openmpi/bin/>:$PATH
   export LD_LIBRARY_PATH=<location for openmpi/lib/>:$LD_LIBRARY_PATH
   export MPI_CXX_INCLUDE_PATH=<location for openmpi/include/>
   

3. Create the ONNX Runtime wheel

   • Change to the ONNX Runtime repo base folder: cd onnxruntime
   • Run ./build.sh --enable_training --use_cuda --config=RelWithDebInfo --build_wheel

   This produces the .whl file in ./build/Linux/RelWithDebInfo/dist for ONNX Runtime Training.

GPU / ROCm

Prerequisites

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The default AMD GPU build requires ROCm software toolkit installed on the system:

• ROCm 5.4
• OpenMPI 4.0.4
  • See install_openmpi.sh

Build instructions

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1. Checkout this code repo with git clone https://github.com/microsoft/onnxruntime

2. Create the ONNX Runtime wheel

   • Change to the ONNX Runtime repo base folder: cd onnxruntime
   • Run ./build.sh --config Release --enable_training --build_wheel --parallel --skip_tests --use_rocm --rocm_home /opt/rocm --nccl_home /opt/rocm --mpi_home <location for openmpi>

   This produces the .whl file in ./build/Linux/Release/dist for ONNX Runtime Training.

DNNL and MKLML

Build Instructions

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Linux

./build.sh --enable_training --use_dnnl

Windows

.\build.bat --enable_training --use_dnnl

Add --build_wheel to build the ONNX Runtime wheel.

This will produce a .whl file in build/Linux/RelWithDebInfo/dist for ONNX Runtime Training.