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