56 lines
2.1 KiB
C++
56 lines
2.1 KiB
C++
//===--------------------------- main.cpp ---------------------------------===//
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//
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// Copyright 2019 The IBM Research Authors.
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//
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// =============================================================================
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//
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//===----------------------------------------------------------------------===//
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#include "src/MainUtils.hpp"
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using namespace std;
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using namespace onnx_mlir;
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int main(int argc, char *argv[]) {
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setExecPath(argv[0], (void *)main);
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registerDialects();
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llvm::cl::OptionCategory OnnxMlirOptions(
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"ONNX MLIR Options", "These are frontend options.");
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llvm::cl::opt<string> inputFilename(llvm::cl::Positional,
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llvm::cl::desc("<input file>"), llvm::cl::init("-"),
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llvm::cl::cat(OnnxMlirOptions));
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llvm::cl::opt<EmissionTargetType> emissionTarget(
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llvm::cl::desc("Choose target to emit:"),
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llvm::cl::values(
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clEnumVal(EmitONNXBasic,
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"Ingest ONNX and emit the basic ONNX operations without"
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"inferred shapes."),
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clEnumVal(
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EmitONNXIR, "Ingest ONNX and emit corresponding ONNX dialect."),
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clEnumVal(
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EmitMLIR, "Lower model to MLIR built-in transformation dialect."),
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clEnumVal(EmitLLVMIR, "Lower model to LLVM IR (LLVM dialect)."),
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clEnumVal(EmitLib, "Lower model to LLVM IR, emit (to file) "
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"LLVM bitcode for model, compile and link it to a "
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"shared library."),
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clEnumVal(EmitJNI, "Lower model to LLMV IR -> LLVM bitcode "
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"-> JNI shared library -> jar")),
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llvm::cl::init(EmitLib), llvm::cl::cat(OnnxMlirOptions));
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llvm::cl::HideUnrelatedOptions(OnnxMlirOptions);
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llvm::cl::ParseCommandLineOptions(
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argc, argv, "ONNX MLIR modular optimizer driver\n");
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mlir::MLIRContext context;
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mlir::OwningModuleRef module;
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processInputFile(inputFilename, emissionTarget, context, module);
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// Input file base name.
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string outputBaseName =
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inputFilename.substr(0, inputFilename.find_last_of("."));
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return compileModule(module, context, outputBaseName, emissionTarget);
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}
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