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ONNX-Frontend

ONNX-Frontend is a project to build customized onnx graph --> onnx dialect --> stablehlo dialect pipeline.

Quick Start

Prepare

git clone https://github.com/bytedance/byteir.git
cd byteir/frontends/onnx-frontend
export ONNX_FRONTEND_ROOT=$(pwd)
export ONNX_MLIR_ROOT=$ONNX_FRONTEND_ROOT/third_party/onnx-mlir
export ONNX_OFFICIAL_ROOT=$ONNX_MLIR_ROOT/third_party/onnx

git submodule update --init --recursive $ONNX_MLIR_ROOT

cd $ONNX_MLIR_ROOT && git apply $ONNX_FRONTEND_ROOT/third_party/patches/OnnxMlir*.patch
cd $ONNX_OFFICIAL_ROOT && git apply $ONNX_FRONTEND_ROOT/third_party/patches/OnnxOfficial*.patch

pip3 install lit>=14.0.0

Build onnx-frontend from source code and run

First, build MLIR (llvm-project commit b2cdf3cc4c08729d0ff582d55e40793a20bbcdcc) with cmake option -DLLVM_ENABLE_RTTI=ON. Then,

mkdir $ONNX_FRONTEND_ROOT/build
cd $ONNX_FRONTEND_ROOT/build
cmake "-H$ONNX_FRONTEND_ROOT" \
      "-B$ONNX_FRONTEND_ROOT/build" \
      -GNinja \
      -DCMAKE_CXX_COMPILER=/usr/bin/c++ \
      -DPython3_ROOT_DIR=/usr/bin/python3.7 \
      -DPY_VERSION=3 \
      -DMLIR_DIR="${YOUR_MLIR_DIR}/lib/cmake/mlir" \
      -DCMAKE_BUILD_TYPE=Release \
      -DLLVM_EXTERNAL_LIT=$(which lit)

cmake --build "$ONNX_FRONTEND_ROOT/build" --config Release --target onnx-frontend onnx-frontend-opt

After the above commands succeed, an onnx-frontend executable should appear in $ONNX_FRONTEND_ROOT/build/onnx-frontend/src/.

Run lit test

cmake --build "$ONNX_FRONTEND_ROOT/build" --target check-of-lit

Example

onnx-frontend model.onnx -batch-size=1 -invokeOnnxVersionConverter -o model.stablehlo.mlir

Contributing

How to Add ONNX-2-STABLEHLO conversion

  • Before you start

  • Workflow

    • Develop new patterns in third_party/onnx-mlir
    • Save changes into a new .patch file under third_party/patches folder

  • Steps to add a onnx-2-stablehlo convertion pattern

    • Take a look at the definition of the onnx op you want to convert, and onnx is more like a coarse-grained op collection.
    • Take a look at the corresponding stablehlo op definition, and stablehlo is more like a fine-grained op collection.
    • Implement the pattern under onnx-mlir/src/Conversion/ directory, note that if there's no 1:1 mapping from onnx to stablehlo, converting the coarse-grained onnx op to fine-grained onnx ops is preferred before converting from onnx dialect to stablehlo dialect. In this way, the fine-grained onnx ops to stablehlo ops' conversion could be reused.
    • Populate the implemented pattern into convert-onnx-to-stablehlo pass
    • Add lit test under onnx-mlir/test/mlir/conversion/onnx_to_stablehlo directory

  • Developing tips