| /* Copyright 2019 The TensorFlow Authors. All Rights Reserved. |
| |
| Licensed under the Apache License, Version 2.0 (the "License"); |
| you may not use this file except in compliance with the License. |
| You may obtain a copy of the License at |
| |
| http://www.apache.org/licenses/LICENSE-2.0 |
| |
| Unless required by applicable law or agreed to in writing, software |
| distributed under the License is distributed on an "AS IS" BASIS, |
| WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| See the License for the specific language governing permissions and |
| limitations under the License. |
| ==============================================================================*/ |
| |
| #include <unordered_set> |
| |
| #include "absl/strings/str_split.h" |
| #include "llvm/Support/InitLLVM.h" |
| #include "llvm/Support/MemoryBuffer.h" |
| #include "llvm/Support/SMLoc.h" |
| #include "llvm/Support/SourceMgr.h" |
| #include "llvm/Support/ToolOutputFile.h" |
| #include "mlir/IR/AsmState.h" // from @llvm-project |
| #include "mlir/IR/MLIRContext.h" // from @llvm-project |
| #include "mlir/Support/FileUtilities.h" // from @llvm-project |
| #include "mlir/Support/LogicalResult.h" // from @llvm-project |
| #include "mlir/Support/ToolUtilities.h" // from @llvm-project |
| #include "mlir/Translation.h" // from @llvm-project |
| #include "tensorflow/compiler/mlir/init_mlir.h" |
| #include "tensorflow/compiler/mlir/tensorflow/translate/tf_mlir_translate.h" |
| #include "tensorflow/compiler/mlir/tensorflow/translate/tf_mlir_translate_cl.h" |
| #include "tensorflow/core/platform/init_main.h" |
| |
| // NOLINTNEXTLINE |
| static llvm::cl::opt<std::string> input_filename(llvm::cl::Positional, |
| llvm::cl::desc("<input file>"), |
| llvm::cl::init("-")); |
| |
| // NOLINTNEXTLINE |
| static llvm::cl::opt<std::string> output_filename( |
| "o", llvm::cl::desc("Output filename"), llvm::cl::value_desc("filename"), |
| llvm::cl::init("-")); |
| |
| // NOLINTNEXTLINE |
| static llvm::cl::opt<bool> splitInputFile( |
| "split-input-file", |
| llvm::cl::desc("Split the input file into pieces and process each chunk " |
| "independently"), |
| llvm::cl::init(false)); |
| |
| // NOLINTNEXTLINE |
| static llvm::cl::opt<bool> import_saved_model_object_graph( |
| "savedmodel-objectgraph-to-mlir", |
| llvm::cl::desc( |
| "Import a saved model's object graph to its MLIR representation"), |
| llvm::cl::value_desc("dir")); |
| |
| // NOLINTNEXTLINE |
| static llvm::cl::opt<bool> import_saved_model_signature_defs( |
| "savedmodel-signaturedefs-to-mlir", |
| llvm::cl::desc( |
| "Import a saved model's SignatureDefs to to their MLIR representation"), |
| llvm::cl::value_desc("dir")); |
| |
| // NOLINTNEXTLINE |
| static llvm::cl::opt<std::string> saved_model_tags( |
| "tf-savedmodel-tags", |
| llvm::cl::desc("Tags used to indicate which MetaGraphDef to import, " |
| "separated by ','"), |
| llvm::cl::init("serve")); |
| |
| // NOLINTNEXTLINE |
| static llvm::cl::opt<std::string> saved_model_exported_names( |
| "tf-savedmodel-exported-names", |
| llvm::cl::desc("Names to export from SavedModel, separated by ','. Empty " |
| "(the default) means export all."), |
| llvm::cl::init("")); |
| |
| int main(int argc, char** argv) { |
| tensorflow::InitMlir y(&argc, &argv); |
| |
| // Add flags for all the registered translations. |
| llvm::cl::opt<const mlir::TranslateFunction*, false, mlir::TranslationParser> |
| requested_translation("", llvm::cl::desc("Translation to perform")); |
| mlir::registerAsmPrinterCLOptions(); |
| llvm::cl::ParseCommandLineOptions(argc, argv, "TF MLIR translation driver\n"); |
| |
| if (!import_saved_model_object_graph && !import_saved_model_signature_defs && |
| !requested_translation) { |
| llvm::errs() << "error: need to specify one translation to perform\n"; |
| return 1; |
| } else if (import_saved_model_object_graph && |
| import_saved_model_signature_defs && requested_translation) { |
| llvm::errs() |
| << "error: cannot specify more than one translation to perform\n"; |
| return 1; |
| } |
| |
| std::string error_message; |
| auto output = mlir::openOutputFile(output_filename, &error_message); |
| if (!output) { |
| llvm::errs() << error_message << "\n"; |
| return 1; |
| } |
| |
| std::unordered_set<std::string> tags = absl::StrSplit(saved_model_tags, ','); |
| std::vector<std::string> exported_names_vector = |
| absl::StrSplit(saved_model_exported_names, ',', absl::SkipEmpty()); |
| absl::Span<std::string> exported_names(exported_names_vector); |
| |
| if (import_saved_model_object_graph) { |
| mlir::MLIRContext context; |
| |
| auto module_or = tensorflow::SavedModelObjectGraphToMlirImport( |
| input_filename, tags, exported_names, &context); |
| if (!module_or.status().ok()) return 1; |
| |
| module_or.ConsumeValueOrDie()->print(output->os()); |
| } else if (import_saved_model_signature_defs) { |
| mlir::MLIRContext context; |
| |
| auto module_or = tensorflow::SavedModelSignatureDefsToMlirImport( |
| input_filename, tags, exported_names, &context, upgrade_legacy); |
| if (!module_or.status().ok()) return 1; |
| |
| module_or.ConsumeValueOrDie()->print(output->os()); |
| } else { |
| auto input = mlir::openInputFile(input_filename, &error_message); |
| |
| if (!input) { |
| llvm::errs() << error_message << "\n"; |
| return 1; |
| } |
| |
| // Processes the memory buffer with a new MLIRContext. |
| auto processBuffer = [&](std::unique_ptr<llvm::MemoryBuffer> ownedBuffer, |
| llvm::raw_ostream& os) { |
| llvm::SourceMgr sourceMgr; |
| sourceMgr.AddNewSourceBuffer(std::move(ownedBuffer), llvm::SMLoc()); |
| mlir::MLIRContext context; |
| mlir::SourceMgrDiagnosticHandler diagnostic_handler(sourceMgr, &context); |
| return (*requested_translation)(sourceMgr, os, &context); |
| }; |
| |
| if (splitInputFile) { |
| if (failed(mlir::splitAndProcessBuffer(std::move(input), processBuffer, |
| output->os()))) |
| return 1; |
| } else { |
| if (failed(processBuffer(std::move(input), output->os()))) return 1; |
| } |
| } |
| |
| output->keep(); |
| return 0; |
| } |