| // Copyright 2020 The IREE Authors | |
| // | |
| // Licensed under the Apache License v2.0 with LLVM Exceptions. | |
| // See https://llvm.org/LICENSE.txt for license information. | |
| // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception | |
| #include "iree_tf_compiler/TFL/Passes.h" | |
| #include "llvm/Support/CommandLine.h" | |
| #include "llvm/Support/ErrorHandling.h" | |
| #include "llvm/Support/InitLLVM.h" | |
| #include "llvm/Support/MemoryBuffer.h" | |
| #include "llvm/Support/SourceMgr.h" | |
| #include "llvm/Support/ToolOutputFile.h" | |
| #include "mlir/Dialect/Tosa/IR/TosaOps.h" | |
| #include "mlir/IR/AsmState.h" | |
| #include "mlir/IR/BuiltinOps.h" | |
| #include "mlir/IR/Dialect.h" | |
| #include "mlir/IR/MLIRContext.h" | |
| #include "mlir/IR/OperationSupport.h" | |
| #include "mlir/Pass/PassManager.h" | |
| #include "mlir/Support/FileUtilities.h" | |
| #include "tensorflow/compiler/mlir/lite/flatbuffer_import.h" | |
| #include "tensorflow/compiler/mlir/lite/ir/tfl_ops.h" | |
| using namespace llvm; | |
| using namespace mlir; | |
| int main(int argc, char **argv) { | |
| llvm::InitLLVM y(argc, argv); | |
| static cl::opt<std::string> inputPath( | |
| cl::Positional, cl::desc("<TFLite FlatBuffer>"), cl::Required); | |
| static cl::opt<std::string> outputFilename("o", cl::desc("Output filename"), | |
| cl::value_desc("filename"), | |
| cl::init("-")); | |
| static cl::opt<std::string> saveTempTflInput( | |
| "save-temp-tfl-input", | |
| cl::desc("Save the TFL pipeline input to this file"), cl::init("")); | |
| static cl::opt<std::string> saveTempIreeImport( | |
| "save-temp-iree-input", | |
| cl::desc("Save the resultant IR to this file (useful for saving an " | |
| "intermediate in a pipeline)"), | |
| cl::init("")); | |
| static cl::list<std::string> inputArrayFlag( | |
| "input-array", | |
| cl::desc("Input tensor, if different from the default inputs"), | |
| cl::ZeroOrMore); | |
| static cl::list<std::string> outputArrayFlag( | |
| "output-array", | |
| cl::desc("Output tensor, if different from the default outputs"), | |
| cl::ZeroOrMore); | |
| // Register any command line options. | |
| registerAsmPrinterCLOptions(); | |
| registerMLIRContextCLOptions(); | |
| registerPassManagerCLOptions(); | |
| registerDefaultTimingManagerCLOptions(); | |
| cl::ParseCommandLineOptions(argc, argv); | |
| // Initialize dialects. | |
| DialectRegistry registry; | |
| registry.insert<mlir::TFL::TensorFlowLiteDialect>(); | |
| registry.insert<mlir::tosa::TosaDialect>(); | |
| registry.insert<quant::QuantizationDialect>(); | |
| registry.insert<StandardOpsDialect, mlir::arith::ArithmeticDialect>(); | |
| // Convert the Module proto into MLIR. | |
| MLIRContext context(registry); | |
| context.loadAllAvailableDialects(); | |
| llvm::SourceMgr sourceMgr; | |
| mlir::SourceMgrDiagnosticHandler sourceMgrHandler(sourceMgr, &context); | |
| // Load input buffer. | |
| std::string errorMessage; | |
| auto inputFile = openInputFile(inputPath, &errorMessage); | |
| if (!inputFile) { | |
| llvm::errs() << errorMessage << "\n"; | |
| return 1; | |
| } | |
| // Convert. | |
| std::vector<std::string> inputArrays(inputArrayFlag.begin(), | |
| inputArrayFlag.end()); | |
| std::vector<std::string> outputArrays(outputArrayFlag.begin(), | |
| outputArrayFlag.end()); | |
| auto loc = mlir::FileLineColLoc::get(&context, | |
| inputFile->getBufferIdentifier(), 0, 0); | |
| OwningModuleRef module = tflite::FlatBufferToMlir( | |
| absl::string_view(inputFile->getBufferStart(), | |
| inputFile->getBufferSize()), | |
| &context, loc, | |
| /*use_external_constant=*/false, inputArrays, outputArrays); | |
| if (!module) { | |
| // Error should have emitted. | |
| llvm::errs() << "Unable to import TFLite flatbuffer to MLIR Module\n"; | |
| return 2; | |
| } | |
| // Save. | |
| auto saveToFile = [&](llvm::StringRef savePath) -> LogicalResult { | |
| auto outputFile = openOutputFile(savePath); | |
| if (!outputFile) { | |
| llvm::errs() << "Could not open output file: " << savePath << "\n"; | |
| return failure(); | |
| } | |
| OpPrintingFlags printFlags; | |
| module->print(outputFile->os(), printFlags); | |
| outputFile->os() << "\n"; | |
| outputFile->keep(); | |
| return success(); | |
| }; | |
| // Save temp input. | |
| if (!saveTempTflInput.empty()) { | |
| if (failed(saveToFile(saveTempTflInput))) return 10; | |
| } | |
| // Run transformations. | |
| PassManager pm(&context, PassManager::Nesting::Implicit); | |
| applyPassManagerCLOptions(pm); | |
| applyDefaultTimingPassManagerCLOptions(pm); | |
| mlir::iree_integrations::TFL::buildTFLImportPassPipeline(pm); | |
| if (failed(pm.run(*module))) { | |
| llvm::errs() << "Running iree-import-tflite pass pipeline failed (see " | |
| "diagnostics)\n"; | |
| return 3; | |
| } | |
| // Save temp output. | |
| if (!saveTempIreeImport.empty()) { | |
| if (failed(saveToFile(saveTempIreeImport))) return 10; | |
| } | |
| // Save output. | |
| if (failed(saveToFile(outputFilename))) return 3; | |
| return 0; | |
| } |