mirror of https://github.com/llvm/torch-mlir
68 lines
2.1 KiB
C++
68 lines
2.1 KiB
C++
//===- MlirInit.cpp -------------------------------------------------------===//
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//
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// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
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// See https://llvm.org/LICENSE.txt for license information.
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// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
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//
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//===----------------------------------------------------------------------===//
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#include "npcomp/Python/MlirInit.h"
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#include "mlir/ExecutionEngine/OptUtils.h"
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#include "mlir/IR/Dialect.h"
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#include "mlir/InitAllDialects.h"
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#include "mlir/InitAllPasses.h"
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#include "mlir/Pass/PassManager.h"
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#include "mlir/Pass/PassRegistry.h"
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#include "npcomp/Dialect/Basicpy/IR/BasicpyDialect.h"
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#include "npcomp/Dialect/Numpy/IR/NumpyDialect.h"
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#include "npcomp/InitAll.h"
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#include "llvm/Support/CommandLine.h"
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#include "llvm/Support/InitLLVM.h"
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#include "llvm/Support/PrettyStackTrace.h"
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#include "llvm/Support/Signals.h"
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#include "llvm/Support/TargetSelect.h"
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namespace mlir {
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namespace npcomp {
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namespace python {
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bool npcompMlirInitialize() {
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// Enable LLVM's signal handler to get nice stack traces.
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llvm::sys::SetOneShotPipeSignalFunction(
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llvm::sys::DefaultOneShotPipeSignalHandler);
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llvm::sys::PrintStackTraceOnErrorSignal("npcomp");
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// Register any pass manager command line options.
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mlir::registerPassManagerCLOptions();
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mlir::registerMLIRContextCLOptions();
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std::string program_name = "npcomp";
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std::vector<const char *> default_options = {program_name.c_str(), nullptr};
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llvm::cl::ParseCommandLineOptions(1, default_options.data());
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// Global registration.
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::mlir::registerAllDialects();
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::mlir::registerAllPasses();
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// Local registration.
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::mlir::NPCOMP::registerAllDialects();
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::mlir::NPCOMP::registerAllPasses();
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// LLVM codegen initialization.
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llvm::InitializeNativeTarget();
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llvm::InitializeNativeTargetAsmPrinter();
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mlir::initializeLLVMPasses();
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return true;
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}
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LogicalResult parsePassPipeline(StringRef pipeline, OpPassManager &pm,
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raw_ostream &errorStream = llvm::errs()) {
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return ::mlir::parsePassPipeline(pipeline, pm, errorStream);
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}
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} // namespace python
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} // namespace npcomp
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} // namespace mlir
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