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This changes the behavior of constructing MLIRContext to no longer load globally
registered dialects on construction. Instead Dialects are only loaded explicitly
on demand:
- the Parser is lazily loading Dialects in the context as it encounters them
during parsing. This is the only purpose for registering dialects and not load
them in the context.
- Passes are expected to declare the dialects they will create entity from
(Operations, Attributes, or Types), and the PassManager is loading Dialects into
the Context when starting a pipeline.
This changes simplifies the configuration of the registration: a compiler only
need to load the dialect for the IR it will emit, and the optimizer is
self-contained and load the required Dialects. For example in the Toy tutorial,
the compiler only needs to load the Toy dialect in the Context, all the others
(linalg, affine, std, LLVM, ...) are automatically loaded depending on the
optimization pipeline enabled.
To adjust to this change, stop using the existing dialect registration: the
global registry will be removed soon.
1) For passes, you need to override the method:
virtual void getDependentDialects(DialectRegistry ®istry) const {}
and registery on the provided registry any dialect that this pass can produce.
Passes defined in TableGen can provide this list in the dependentDialects list
field.
2) For dialects, on construction you can register dependent dialects using the
provided MLIRContext: `context.getOrLoadDialect<DialectName>()`
This is useful if a dialect may canonicalize or have interfaces involving
another dialect.
3) For loading IR, dialect that can be in the input file must be explicitly
registered with the context. `MlirOptMain()` is taking an explicit registry for
this purpose. See how the standalone-opt.cpp example is setup:
mlir::DialectRegistry registry;
registry.insert<mlir::standalone::StandaloneDialect>();
registry.insert<mlir::StandardOpsDialect>();
Only operations from these two dialects can be in the input file. To include all
of the dialects in MLIR Core, you can populate the registry this way:
mlir::registerAllDialects(registry);
4) For `mlir-translate` callback, as well as frontend, Dialects can be loaded in
the context before emitting the IR: context.getOrLoadDialect<ToyDialect>()
Differential Revision: https://reviews.llvm.org/D85622
318 lines
12 KiB
C++
318 lines
12 KiB
C++
//===- jit-runner.cpp - MLIR CPU Execution Driver Library -----------------===//
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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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//
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// This is a library that provides a shared implementation for command line
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// utilities that execute an MLIR file on the CPU by translating MLIR to LLVM
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// IR before JIT-compiling and executing the latter.
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//
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// The translation can be customized by providing an MLIR to MLIR
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// transformation.
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//===----------------------------------------------------------------------===//
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#include "mlir/ExecutionEngine/JitRunner.h"
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#include "mlir/Dialect/LLVMIR/LLVMDialect.h"
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#include "mlir/ExecutionEngine/ExecutionEngine.h"
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#include "mlir/ExecutionEngine/OptUtils.h"
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#include "mlir/IR/MLIRContext.h"
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#include "mlir/IR/Module.h"
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#include "mlir/IR/StandardTypes.h"
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#include "mlir/Parser.h"
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#include "mlir/Support/FileUtilities.h"
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#include "llvm/ADT/STLExtras.h"
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#include "llvm/ExecutionEngine/Orc/JITTargetMachineBuilder.h"
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#include "llvm/IR/IRBuilder.h"
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#include "llvm/IR/LLVMContext.h"
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#include "llvm/IR/LegacyPassNameParser.h"
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#include "llvm/IR/Module.h"
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#include "llvm/Support/CommandLine.h"
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#include "llvm/Support/FileUtilities.h"
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#include "llvm/Support/SourceMgr.h"
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#include "llvm/Support/StringSaver.h"
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#include "llvm/Support/ToolOutputFile.h"
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#include <cstdint>
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#include <numeric>
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using namespace mlir;
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using llvm::Error;
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namespace {
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/// This options struct prevents the need for global static initializers, and
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/// is only initialized if the JITRunner is invoked.
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struct Options {
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llvm::cl::opt<std::string> inputFilename{llvm::cl::Positional,
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llvm::cl::desc("<input file>"),
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llvm::cl::init("-")};
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llvm::cl::opt<std::string> mainFuncName{
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"e", llvm::cl::desc("The function to be called"),
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llvm::cl::value_desc("<function name>"), llvm::cl::init("main")};
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llvm::cl::opt<std::string> mainFuncType{
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"entry-point-result",
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llvm::cl::desc("Textual description of the function type to be called"),
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llvm::cl::value_desc("f32 | i32 | i64 | void"), llvm::cl::init("f32")};
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llvm::cl::OptionCategory optFlags{"opt-like flags"};
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// CLI list of pass information
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llvm::cl::list<const llvm::PassInfo *, bool, llvm::PassNameParser> llvmPasses{
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llvm::cl::desc("LLVM optimizing passes to run"), llvm::cl::cat(optFlags)};
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// CLI variables for -On options.
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llvm::cl::opt<bool> optO0{"O0",
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llvm::cl::desc("Run opt passes and codegen at O0"),
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llvm::cl::cat(optFlags)};
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llvm::cl::opt<bool> optO1{"O1",
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llvm::cl::desc("Run opt passes and codegen at O1"),
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llvm::cl::cat(optFlags)};
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llvm::cl::opt<bool> optO2{"O2",
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llvm::cl::desc("Run opt passes and codegen at O2"),
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llvm::cl::cat(optFlags)};
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llvm::cl::opt<bool> optO3{"O3",
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llvm::cl::desc("Run opt passes and codegen at O3"),
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llvm::cl::cat(optFlags)};
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llvm::cl::OptionCategory clOptionsCategory{"linking options"};
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llvm::cl::list<std::string> clSharedLibs{
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"shared-libs", llvm::cl::desc("Libraries to link dynamically"),
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llvm::cl::ZeroOrMore, llvm::cl::MiscFlags::CommaSeparated,
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llvm::cl::cat(clOptionsCategory)};
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/// CLI variables for debugging.
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llvm::cl::opt<bool> dumpObjectFile{
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"dump-object-file",
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llvm::cl::desc("Dump JITted-compiled object to file specified with "
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"-object-filename (<input file>.o by default).")};
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llvm::cl::opt<std::string> objectFilename{
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"object-filename",
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llvm::cl::desc("Dump JITted-compiled object to file <input file>.o")};
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};
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} // end anonymous namespace
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static OwningModuleRef parseMLIRInput(StringRef inputFilename,
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MLIRContext *context) {
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// Set up the input file.
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std::string errorMessage;
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auto file = openInputFile(inputFilename, &errorMessage);
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if (!file) {
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llvm::errs() << errorMessage << "\n";
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return nullptr;
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}
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llvm::SourceMgr sourceMgr;
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sourceMgr.AddNewSourceBuffer(std::move(file), llvm::SMLoc());
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return OwningModuleRef(parseSourceFile(sourceMgr, context));
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}
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static inline Error make_string_error(const Twine &message) {
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return llvm::make_error<llvm::StringError>(message.str(),
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llvm::inconvertibleErrorCode());
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}
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static Optional<unsigned> getCommandLineOptLevel(Options &options) {
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Optional<unsigned> optLevel;
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SmallVector<std::reference_wrapper<llvm::cl::opt<bool>>, 4> optFlags{
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options.optO0, options.optO1, options.optO2, options.optO3};
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// Determine if there is an optimization flag present.
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for (unsigned j = 0; j < 4; ++j) {
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auto &flag = optFlags[j].get();
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if (flag) {
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optLevel = j;
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break;
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}
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}
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return optLevel;
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}
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// JIT-compile the given module and run "entryPoint" with "args" as arguments.
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static Error
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compileAndExecute(Options &options, ModuleOp module, StringRef entryPoint,
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std::function<llvm::Error(llvm::Module *)> transformer,
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void **args) {
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Optional<llvm::CodeGenOpt::Level> jitCodeGenOptLevel;
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if (auto clOptLevel = getCommandLineOptLevel(options))
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jitCodeGenOptLevel =
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static_cast<llvm::CodeGenOpt::Level>(clOptLevel.getValue());
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SmallVector<StringRef, 4> libs(options.clSharedLibs.begin(),
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options.clSharedLibs.end());
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auto expectedEngine = mlir::ExecutionEngine::create(module, transformer,
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jitCodeGenOptLevel, libs);
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if (!expectedEngine)
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return expectedEngine.takeError();
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auto engine = std::move(*expectedEngine);
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auto expectedFPtr = engine->lookup(entryPoint);
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if (!expectedFPtr)
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return expectedFPtr.takeError();
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if (options.dumpObjectFile)
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engine->dumpToObjectFile(options.objectFilename.empty()
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? options.inputFilename + ".o"
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: options.objectFilename);
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void (*fptr)(void **) = *expectedFPtr;
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(*fptr)(args);
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return Error::success();
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}
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static Error compileAndExecuteVoidFunction(
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Options &options, ModuleOp module, StringRef entryPoint,
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std::function<llvm::Error(llvm::Module *)> transformer) {
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auto mainFunction = module.lookupSymbol<LLVM::LLVMFuncOp>(entryPoint);
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if (!mainFunction || mainFunction.empty())
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return make_string_error("entry point not found");
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void *empty = nullptr;
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return compileAndExecute(options, module, entryPoint, transformer, &empty);
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}
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template <typename Type>
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Error checkCompatibleReturnType(LLVM::LLVMFuncOp mainFunction);
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template <>
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Error checkCompatibleReturnType<int32_t>(LLVM::LLVMFuncOp mainFunction) {
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if (!mainFunction.getType().getFunctionResultType().isIntegerTy(32))
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return make_string_error("only single llvm.i32 function result supported");
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return Error::success();
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}
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template <>
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Error checkCompatibleReturnType<int64_t>(LLVM::LLVMFuncOp mainFunction) {
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if (!mainFunction.getType().getFunctionResultType().isIntegerTy(64))
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return make_string_error("only single llvm.i64 function result supported");
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return Error::success();
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}
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template <>
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Error checkCompatibleReturnType<float>(LLVM::LLVMFuncOp mainFunction) {
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if (!mainFunction.getType().getFunctionResultType().isFloatTy())
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return make_string_error("only single llvm.f32 function result supported");
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return Error::success();
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}
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template <typename Type>
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Error compileAndExecuteSingleReturnFunction(
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Options &options, ModuleOp module, StringRef entryPoint,
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std::function<llvm::Error(llvm::Module *)> transformer) {
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auto mainFunction = module.lookupSymbol<LLVM::LLVMFuncOp>(entryPoint);
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if (!mainFunction || mainFunction.isExternal())
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return make_string_error("entry point not found");
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if (mainFunction.getType().getFunctionNumParams() != 0)
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return make_string_error("function inputs not supported");
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if (Error error = checkCompatibleReturnType<Type>(mainFunction))
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return error;
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Type res;
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struct {
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void *data;
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} data;
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data.data = &res;
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if (auto error = compileAndExecute(options, module, entryPoint, transformer,
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(void **)&data))
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return error;
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// Intentional printing of the output so we can test.
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llvm::outs() << res << '\n';
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return Error::success();
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}
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/// Entry point for all CPU runners. Expects the common argc/argv
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/// arguments for standard C++ main functions and an mlirTransformer.
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/// The latter is applied after parsing the input into MLIR IR and
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/// before passing the MLIR module to the ExecutionEngine.
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int mlir::JitRunnerMain(
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int argc, char **argv,
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function_ref<LogicalResult(mlir::ModuleOp)> mlirTransformer) {
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// Create the options struct containing the command line options for the
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// runner. This must come before the command line options are parsed.
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Options options;
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llvm::cl::ParseCommandLineOptions(argc, argv, "MLIR CPU execution driver\n");
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Optional<unsigned> optLevel = getCommandLineOptLevel(options);
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SmallVector<std::reference_wrapper<llvm::cl::opt<bool>>, 4> optFlags{
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options.optO0, options.optO1, options.optO2, options.optO3};
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unsigned optCLIPosition = 0;
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// Determine if there is an optimization flag present, and its CLI position
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// (optCLIPosition).
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for (unsigned j = 0; j < 4; ++j) {
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auto &flag = optFlags[j].get();
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if (flag) {
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optCLIPosition = flag.getPosition();
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break;
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}
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}
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// Generate vector of pass information, plus the index at which we should
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// insert any optimization passes in that vector (optPosition).
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SmallVector<const llvm::PassInfo *, 4> passes;
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unsigned optPosition = 0;
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for (unsigned i = 0, e = options.llvmPasses.size(); i < e; ++i) {
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passes.push_back(options.llvmPasses[i]);
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if (optCLIPosition < options.llvmPasses.getPosition(i)) {
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optPosition = i;
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optCLIPosition = UINT_MAX; // To ensure we never insert again
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}
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}
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MLIRContext context(/*loadAllDialects=*/false);
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registerAllDialects(&context);
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auto m = parseMLIRInput(options.inputFilename, &context);
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if (!m) {
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llvm::errs() << "could not parse the input IR\n";
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return 1;
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}
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if (mlirTransformer)
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if (failed(mlirTransformer(m.get())))
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return EXIT_FAILURE;
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auto tmBuilderOrError = llvm::orc::JITTargetMachineBuilder::detectHost();
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if (!tmBuilderOrError) {
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llvm::errs() << "Failed to create a JITTargetMachineBuilder for the host\n";
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return EXIT_FAILURE;
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}
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auto tmOrError = tmBuilderOrError->createTargetMachine();
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if (!tmOrError) {
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llvm::errs() << "Failed to create a TargetMachine for the host\n";
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return EXIT_FAILURE;
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}
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auto transformer = mlir::makeLLVMPassesTransformer(
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passes, optLevel, /*targetMachine=*/tmOrError->get(), optPosition);
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// Get the function used to compile and execute the module.
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using CompileAndExecuteFnT =
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Error (*)(Options &, ModuleOp, StringRef,
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std::function<llvm::Error(llvm::Module *)>);
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auto compileAndExecuteFn =
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llvm::StringSwitch<CompileAndExecuteFnT>(options.mainFuncType.getValue())
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.Case("i32", compileAndExecuteSingleReturnFunction<int32_t>)
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.Case("i64", compileAndExecuteSingleReturnFunction<int64_t>)
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.Case("f32", compileAndExecuteSingleReturnFunction<float>)
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.Case("void", compileAndExecuteVoidFunction)
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.Default(nullptr);
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Error error =
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compileAndExecuteFn
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? compileAndExecuteFn(options, m.get(),
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options.mainFuncName.getValue(), transformer)
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: make_string_error("unsupported function type");
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int exitCode = EXIT_SUCCESS;
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llvm::handleAllErrors(std::move(error),
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[&exitCode](const llvm::ErrorInfoBase &info) {
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llvm::errs() << "Error: ";
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info.log(llvm::errs());
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llvm::errs() << '\n';
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exitCode = EXIT_FAILURE;
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});
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return exitCode;
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}
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