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**Description**: Describe your changes. add rocm ep doc. Perview Github page : https://ytaous.github.io/onnxruntime/ Added items Home page - [ ] Update matrix on home page: https://ytaous.github.io/onnxruntime/ - [ ] Link "Installation Instruction Follow build instructions from here" to onnxruntime build with ROCm(inference) page.(This link now point to preview page, will change later) Installation - [ ] Update installation page: https://ytaous.github.io/onnxruntime/docs/install/#training-install-table-for-all-languages Build onnxruntime - [ ] Add onnxruntime build with ROCm(inference): https://ytaous.github.io/onnxruntime/docs/build/eps.html#amd-rocm - [ ] Update onnxruntime build with ROCm(training): https://ytaous.github.io/onnxruntime/docs/build/training.html#gpu--rocm ExecutionProvider - [ ] Add ROCm ExecutionProvider navitagation: https://ytaous.github.io/onnxruntime/docs/execution-providers/ - [ ] Add ROCm-ExecutionProvider page: https://ytaous.github.io/onnxruntime/docs/execution-providers/ROCm-ExecutionProvider.html Performance - [ ] Add enable_rocm_profiling introcduction: https://ytaous.github.io/onnxruntime/docs/performance/tune-performance.html#profiling-and-performance-report - [ ] Add graph-optimation for ROCm ep: https://ytaous.github.io/onnxruntime/docs/performance/graph-optimizations.html#extended-graph-optimizations Co-authored-by: Ethan Tao <ettao@microsoft.com@orttrainingdev7.d32nl1ml4oruzj4qz3bqlggovf.px.internal.cloudapp.net> Co-authored-by: ytaous <4484531+ytaous@users.noreply.github.com>
115 lines
3.6 KiB
Markdown
115 lines
3.6 KiB
Markdown
---
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title: Build for training
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parent: Build ONNX Runtime
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description: Learn how to build ONNX Runtime for training from source for different hardware targets
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nav_order: 2
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redirect_from: /docs/how-to/build/training
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---
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# Build ONNX Runtime for training
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{: .no_toc }
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## Contents
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{: .no_toc }
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* TOC placeholder
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{:toc}
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## CPU
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### Build Instructions
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{: .no_toc }
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To build ORT with training support add `--enable_training` build instruction.
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All other build options are the same for inferencing as they are for training.
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#### Windows
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```
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.\build.bat --config RelWithDebInfo --build_shared_lib --parallel --enable_training
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```
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The default Windows CMake Generator is Visual Studio 2017, but you can also use the newer Visual Studio 2019 by passing
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`--cmake_generator "Visual Studio 16 2019"` to `.\build.bat`
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#### Linux/macOS
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```
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./build.sh --config RelWithDebInfo --build_shared_lib --parallel --enable_training
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```
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## GPU / CUDA
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### Prerequisites
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{: .no_toc }
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The default NVIDIA GPU build requires CUDA runtime libraries installed on the system:
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* [CUDA](https://developer.nvidia.com/cuda-toolkit) 10.2
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* [cuDNN](https://developer.nvidia.com/cudnn) 8.0
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* [NCCL](https://developer.nvidia.com/nccl) 2.7
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* [OpenMPI](https://www.open-mpi.org/) 4.0.4
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* See [install_openmpi.sh](https://github.com/microsoft/onnxruntime/blob/master/tools/ci_build/github/linux/docker/scripts/install_openmpi.sh)
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These dependency versions should reflect what is in the [Dockerfiles](https://github.com/pytorch/ort/tree/main/docker).
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### Build instructions
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{: .no_toc }
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1. Checkout this code repo with `git clone https://github.com/microsoft/onnxruntime`
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2. Set the environment variables: *adjust the path for location your build machine*
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```
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export CUDA_HOME=<location for CUDA libs> # e.g. /usr/local/cuda
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export CUDNN_HOME=<location for cuDNN libs> # e.g. /usr/local/cuda
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export CUDACXX=<location for NVCC> #e.g. /usr/local/cuda/bin/nvcc
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export PATH=<location for openmpi/bin/>:$PATH
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export LD_LIBRARY_PATH=<location for openmpi/lib/>:$LD_LIBRARY_PATH
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export MPI_CXX_INCLUDE_PATH=<location for openmpi/include/>
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```
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3. Create the ONNX Runtime wheel
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* Change to the ONNX Runtime repo base folder: `cd onnxruntime`
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* Run `./build.sh --enable_training --use_cuda --config=RelWithDebInfo --build_wheel`
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This produces the .whl file in `./build/Linux/RelWithDebInfo/dist` for ONNX Runtime Training.
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## GPU / ROCm
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### Prerequisites
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{: .no_toc }
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The default AMD GPU build requires ROCm software toolkit installed on the system:
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* [ROCm](https://docs.amd.com/bundle/ROCm-Installation-Guide-v5.2.3/page/How_to_Install_ROCm.html#_How_to_Install) 5.2.3
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* [OpenMPI](https://www.open-mpi.org/) 4.0.4
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* See [install_openmpi.sh](https://github.com/microsoft/onnxruntime/blob/master/tools/ci_build/github/linux/docker/scripts/install_openmpi.sh)
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### Build instructions
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{: .no_toc }
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1. Checkout this code repo with `git clone https://github.com/microsoft/onnxruntime`
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2. Create the ONNX Runtime wheel
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* Change to the ONNX Runtime repo base folder: `cd onnxruntime`
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* Run `./build.sh --config RelWithDebInfo --enable_training --build_wheel --use_rocm --rocm_home /opt/rocm --nccl_home /opt/rocm --mpi_home <location for openmpi>`
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This produces the .whl file in `./build/Linux/RelWithDebInfo/dist` for ONNX Runtime Training.
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## DNNL and MKLML
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### Build Instructions
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{: .no_toc }
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#### Linux
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`./build.sh --enable_training --use_dnnl`
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#### Windows
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`.\build.bat --enable_training --use_dnnl`
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Add `--build_wheel` to build the ONNX Runtime wheel
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This will produce a .whl file in `build/Linux/RelWithDebInfo/dist` for ONNX Runtime Training
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