Installation of ONNX-MLIR on Linux / OSX

We provide here directions to install ONNX-MLIR on Linux and OSX. On Mac, there are a couple of commands that are different. These differences will be listed in the explanation below, when relevant. Installing ONNX-MLIR on Apple silicon is natively supported and it is recommended to use brew to manage prerequisites.

MLIR

Firstly, install MLIR (as a part of LLVM-Project):

git clone -n https://github.com/llvm/llvm-project.git
# Check out a specific branch that is known to work with ONNX-MLIR.
cd llvm-project && git checkout 7ac7d418ac2b16fd44789dcf48e2b5d73de3e715 && cd ..

mkdir llvm-project/build
cd llvm-project/build
cmake -G Ninja ../llvm \
   -DLLVM_ENABLE_PROJECTS=mlir \
   -DLLVM_TARGETS_TO_BUILD="host" \
   -DCMAKE_BUILD_TYPE=Release \
   -DLLVM_ENABLE_ASSERTIONS=ON \
   -DLLVM_ENABLE_RTTI=ON \
   -DLLVM_ENABLE_LIBEDIT=OFF

cmake --build . -- ${MAKEFLAGS}
cmake --build . --target check-mlir

ONNX-MLIR (this project)

Build

The MLIR_DIR cmake variable must be set before building onnx-mlir. It should point to the mlir cmake module inside an llvm-project build or install directory (e.g., llvm-project/build/lib/cmake/mlir).

This project uses lit (LLVM’s Integrated Tester) for unit tests. When running cmake, we can also specify the path to the lit tool from LLVM using the LLVM_EXTERNAL_LIT variable but it is not required as long as MLIR_DIR points to a build directory of llvm-project. If MLIR_DIR points to an install directory of llvm-project, LLVM_EXTERNAL_LIT is required.

To build ONNX-MLIR, use the following commands (maybe with additional -DCMAKE_CXX_FLAGS argument described below):

same-as-file: <> ({“ref”: “utils/install-onnx-mlir.sh”, “skip-doc”: 2})

git clone --recursive https://github.com/onnx/onnx-mlir.git

# MLIR_DIR must be set with cmake option now
MLIR_DIR=$(pwd)/llvm-project/build/lib/cmake/mlir
mkdir onnx-mlir/build && cd onnx-mlir/build
if [[ -z "$pythonLocation" ]]; then
  cmake -G Ninja \
        -DCMAKE_CXX_COMPILER=/usr/bin/c++ \
        -DMLIR_DIR=${MLIR_DIR} \
        ..
else
  cmake -G Ninja \
        -DCMAKE_CXX_COMPILER=/usr/bin/c++ \
        -DPython3_ROOT_DIR=$pythonLocation \
        -DMLIR_DIR=${MLIR_DIR} \
        ..
fi
cmake --build .

# Run lit tests:
export LIT_OPTS=-v
cmake --build . --target check-onnx-lit

Since OSX Big Sur, add the -DCMAKE_CXX_COMPILER=/usr/bin/c++ option to the above cmake .. command due to changes in default compilers.

The environment variable $pythonLocation may be used to specify the base directory of the Python compiler.

After the above commands succeed, an onnx-mlir executable should appear in the Debug/bin or Release/bin directory.

Enable CPU Optimizations

To make the compiler run faster (without any affect on the generated code) you can pass -DCMAKE_CXX_FLAGS=-march=native to the cmake -G Ninja .. build configuration step above to generate code that exploits all the features of your local CPU, at the expense of portability. Or you can enable a specific CPU feature, e.g. -DCMAKE_CXX_FLAGS=-mf16c to enable the F16C feature to enable native conversion between float16 and (32 bit) float. It is used in src/Support/SmallFP.hpp.

Known MacOS Issues

jsoniter issue

There is a known issue when building onnx-mlir. If you see an error of this sorts:

Cloning into '/home/user/onnx-mlir/build/src/Runtime/jni/jsoniter'...

[...]

make[2]: *** [src/Runtime/jni/CMakeFiles/jsoniter.dir/build.make:74: src/Runtime/jni/jsoniter/target/jsoniter-0.9.23.jar] Error 127
make[1]: *** [CMakeFiles/Makefile2:3349: src/Runtime/jni/CMakeFiles/jsoniter.dir/all] Error 2
make: *** [Makefile:146: all] Error 2.

The suggested workaround until jsoniter is fixed is as follows: install maven (e.g. brew install maven) and run alias nproc="sysctl -n hw.logicalcpu" in your shell.

Protobuf issue (Mac M1, specific to protobuf 4.21.12 which is currently required)

On Mac M1, you may have some issues building protobuf. In particular, you may fail to install onnx (via pip install -e third_party/onnx) or you may fail to compile onnx-mlir (no arm64 symbol for InternalMetadata::~InternalMetadata).

The first failure is likely an issue with having multiple versions of protobuf. Installing a version with brew was not helpful (version 4.21.12 because of a known bug that can be corrected with a patch below). Uninstall the brew version, and make sure you install the right one with pip: pip install protobuf== 4.21.12.

The second failure can be remediated by downloading protobuf source code, applying a patch, and installing it on the local machine. See Dockerfile.llvm-project on line 66 for cloning instructions. After cloning the right version, you should apply a patch patch by downloading from the link above and applying it. Then you should follow the steps in the Dockerfile.llvm-project file (skipped the ldconfig step without consequences). You may have to brew a couple of the tools, see the yum install in the Dockerfile.llvm-project file above. You should then be able to successfully install protobuf and compile onnx-mlir. As the dependences between third_party and onnx-mlir might cause issues, it is always safe to delete the third_party directory, reinstall using git submodule update --init --recursive, reinstall onnx, delete onnx-mlir/build and rebuild onnx-mlir from scratch.

Trouble shooting build issues

Check this page for helpful hints.