mirror of https://github.com/llvm/torch-mlir
130 lines
4.6 KiB
C++
130 lines
4.6 KiB
C++
//===- npcomp-opt.cpp -------------------------------------------*- C++ -*-===//
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//
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// This file is licensed 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 "mlir/IR/Dialect.h"
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#include "mlir/IR/MLIRContext.h"
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#include "mlir/InitAllDialects.h"
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#include "mlir/InitAllPasses.h"
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#include "mlir/Pass/Pass.h"
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#include "mlir/Pass/PassManager.h"
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#include "mlir/Support/FileUtilities.h"
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#include "mlir/Support/MlirOptMain.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/SourceMgr.h"
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#include "llvm/Support/ToolOutputFile.h"
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#include "npcomp/Dialect/Basicpy/BasicpyDialect.h"
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#include "npcomp/Dialect/Numpy/NumpyDialect.h"
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#include "npcomp/Dialect/TCF/IR/TCFDialect.h"
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#include "npcomp/Dialect/TCP/IR/TCPDialect.h"
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#include "npcomp/Conversion/TCFToTCP/TCFToTCP.h"
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#include "npcomp/Conversion/TCPToLinalg/TCPToLinalg.h"
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#include "npcomp/E2E/E2E.h"
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static 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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static llvm::cl::opt<std::string>
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outputFilename("o", llvm::cl::desc("Output filename"),
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llvm::cl::value_desc("filename"), llvm::cl::init("-"));
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static llvm::cl::opt<bool> splitInputFile(
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"split-input-file",
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llvm::cl::desc("Split the input file into pieces and process each "
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"chunk independently"),
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llvm::cl::init(false));
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static llvm::cl::opt<bool> verifyDiagnostics(
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"verify-diagnostics",
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llvm::cl::desc("Check that emitted diagnostics match "
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"expected-* lines on the corresponding line"),
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llvm::cl::init(false));
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static llvm::cl::opt<bool> verifyPasses(
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"verify-each",
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llvm::cl::desc("Run the verifier after each transformation pass"),
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llvm::cl::init(true));
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static llvm::cl::opt<bool> allowUnregisteredDialects(
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"allow-unregistered-dialect",
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llvm::cl::desc("Allow operation with no registered dialects"),
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llvm::cl::init(false));
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static llvm::cl::opt<bool>
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showDialects("show-dialects",
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llvm::cl::desc("Print the list of registered dialects"),
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llvm::cl::init(false));
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int main(int argc, char **argv) {
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// TODO: Move all npcomp registration to a common helper.
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mlir::registerAllDialects();
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mlir::registerAllPasses();
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mlir::registerDialect<mlir::NPCOMP::Basicpy::BasicpyDialect>();
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mlir::registerDialect<mlir::NPCOMP::Numpy::NumpyDialect>();
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mlir::registerDialect<mlir::NPCOMP::tcf::TCFDialect>();
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mlir::registerDialect<mlir::NPCOMP::tcp::TCPDialect>();
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using mlir::Pass; // The .inc files reference this unqualified.
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#define GEN_PASS_REGISTRATION
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#include "npcomp/E2E/Passes.h.inc"
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mlir::PassPipelineRegistration<>("e2e-lowering-pipeline", "E2E lowering pipeline.",
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mlir::NPCOMP::createE2ELoweringPipeline);
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mlir::PassPipelineRegistration<>(
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"lower-to-hybrid-tensor-memref-pipeline",
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"Pipeline lowering to hybrid tensor/memref.",
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mlir::NPCOMP::createLowerToHybridTensorMemRefPipeline);
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#define GEN_PASS_REGISTRATION
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#include "npcomp/Conversion/Passes.h.inc"
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llvm::InitLLVM y(argc, argv);
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// Register any pass manager command line options.
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mlir::registerPassManagerCLOptions();
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mlir::PassPipelineCLParser passPipeline("", "Compiler passes to run");
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// Parse pass names in main to ensure static initialization completed.
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llvm::cl::ParseCommandLineOptions(argc, argv,
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"MLIR modular optimizer driver\n");
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mlir::MLIRContext context;
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if (showDialects) {
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llvm::outs() << "Registered Dialects:\n";
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for (mlir::Dialect *dialect : context.getRegisteredDialects()) {
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llvm::outs() << dialect->getNamespace() << "\n";
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}
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return 0;
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}
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// Set up the input file.
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std::string errorMessage;
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auto file = mlir::openInputFile(inputFilename, &errorMessage);
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if (!file) {
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llvm::errs() << errorMessage << "\n";
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return 1;
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}
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auto output = mlir::openOutputFile(outputFilename, &errorMessage);
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if (!output) {
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llvm::errs() << errorMessage << "\n";
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exit(1);
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}
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if (failed(MlirOptMain(output->os(), std::move(file), passPipeline,
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splitInputFile, verifyDiagnostics, verifyPasses,
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allowUnregisteredDialects))) {
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return 1;
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}
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// Keep the output file if the invocation of MlirOptMain was successful.
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output->keep();
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return 0;
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}
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