onnx-mlir/README.md

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# ONNF
Open Neural Network Frontend : an ONNX frontend for MLIR.
[![CircleCI](https://circleci.com/gh/clang-ykt/ONNF.svg?style=svg)](https://circleci.com/gh/clang-ykt/ONNF)
## Installation
We assume an existing installation of MLIR. The LLVM-Project repo commit hash we used to test against is 9b6ad8466bb8b97082b705270603ad7f4559e931 and the MLIR repo commit hash we used is 0710266d0f56cf6ab0f437badbd7416b6cecdf5f.
Two environment variables need to be set:
- LLVM_SRC should point to the llvm src directory (e.g., llvm-project/llvm).
- LLVM_BUILD should point to the llvm build directory (e.g., llvm-project/build).
To build ONNF, use the following command:
```
git clone --recursive git@github.com:clang-ykt/ONNF.git
mkdir build
cd build
cmake ..
cmake --build . --target all
```
After the above commands succeed, an `onnf` executable should appear in the `bin` directory.
## Using ONNF
The usage of `onnf` is as such:
```
OVERVIEW: ONNF MLIR modular optimizer driver
USAGE: onnf [options] <input file>
OPTIONS:
Generic Options:
--help - Display available options (--help-hidden for more)
--help-list - Display list of available options (--help-list-hidden for more)
--version - Display the version of this program
ONNF Options:
These are frontend options.
Choose target to emit:
--EmitONNXIR - Ingest ONNX and emit corresponding ONNX dialect.
--EmitMLIR - Lower model to MLIR built-in transformation dialect.
--EmitLLVMIR - Lower model to LLVM IR (LLVM dialect).
--EmitLLVMBC - Lower model to LLVM IR and emit (to file) LLVM bitcode for model.
```
## Example
For example, to lower an ONNX model (e.g., add.onnx) to ONNX dialect, use the following command:
```
./onnf --EmitONNXIR add.onnx
```
The output should look like:
```
module {
func @main_graph(%arg0: tensor<10x10x10xf32>, %arg1: tensor<10x10x10xf32>) -> tensor<10x10x10xf32> {
%0 = "onnx.Add"(%arg0, %arg1) : (tensor<10x10x10xf32>, tensor<10x10x10xf32>) -> tensor<10x10x10xf32>
return %0 : tensor<10x10x10xf32>
}
}
```