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Results 1 - 10 of 34 for tac_module (0.16 sec)
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tensorflow/compiler/mlir/lite/experimental/tac/tac_module.cc
// large functions (and maybe other metadata as well). } const tac::TargetHardware* TacModule::GetTargetHardware( const std::string& hardware_name) const { for (auto& hardware : backends_) { if (GetHardwareName(hardware.get()) == hardware_name) return hardware.get(); } return nullptr; } absl::Status TacModule::RunTacPasses(mlir::ModuleOp* module, bool debug_mode) { mlir::PassManager pm((*module)->getName(),
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jun 08 01:19:25 UTC 2023 - 5.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/experimental/tac/tac_module.h
// 1) users should create object form this class, with desired options // (TacModule::Options). // 2) Use SetImporter/SetExporter to the desired importer // and exporter. // 3) Call Run() // // The module fetches all TargetHardware backends registered in the binary // and only create TargetHardware requested in Options. // // This class is not thread safe. class TacModule { public: // TAC options. Contains knobs to configure TAC as needed.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jun 08 01:19:25 UTC 2023 - 4.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/experimental/tac/py_wrapper/tac_wrapper.cc
mlir::TFL::tac::TacModule::Options options; options.hardware_backends = device_specs; options.enable_inliner = true; options.legalize_to_tflite_ops = true; mlir::TFL::tac::TacModule tac_module(options); mlir::DialectRegistry registry; mlir::RegisterAllTensorFlowDialects(registry); tac_module.RegisterExtraDialects(registry); tac_module.SetImporter(CreateTfLiteImporter(model_file_path));
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 06 03:08:33 UTC 2023 - 2.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/experimental/tac/tac_translate.cc
tac_module.RegisterExtraDialects(registry); tac_module.SetImporter(CreateTfLiteImporter()); tac_module.SetExporter(CreateTfLiteExporter(options.hardware_backends)); return tac_module.Run(); } } // namespace int main(int argc, char** argv) { tensorflow::InitMlir y(&argc, &argv); llvm::cl::ParseCommandLineOptions(argc, argv, "Target aware conversion\n");
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Mar 22 14:25:57 UTC 2022 - 5.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/experimental/tac/BUILD
"@llvm-project//mlir:Pass", "@llvm-project//mlir:Support", ], alwayslink = 1, ) # TODO(b/177376459): split tac_module and passes dependency to separate libraries. cc_library( name = "target_aware_conversion", srcs = [ "tac_module.cc", "transforms/compute_cost.cc", "transforms/fold_constants_to_subgraph.cc", "transforms/get_alternative_subgraph.cc",
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 11 06:11:34 UTC 2024 - 12K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/experimental/tac/transforms/tac_pass.h
#include "mlir/Pass/Pass.h" // from @llvm-project #include "tensorflow/compiler/mlir/lite/experimental/tac/hardwares/target_hardware.h" #include "tensorflow/compiler/mlir/lite/experimental/tac/tac_module.h" namespace mlir { namespace TFL { namespace tac { // An OperationPass<> with access to the TAC module instance that the // pass is running part of.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 06 03:08:33 UTC 2023 - 3.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/experimental/tac/tac_importer_exporter.h
namespace mlir { namespace TFL { namespace tac { // Interface for Importing program to TAC (Target Aware Conversion) Module. // This class is an interface for importing program in TAC. // See TacModule in how to register it with the module and use it. class TacImporter { public: virtual ~TacImporter() = default; // Imports and returns the Module for the imported program.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jun 08 01:19:25 UTC 2023 - 1.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/experimental/tac/transforms/passes.h
#include "mlir/Pass/Pass.h" // from @llvm-project #include "tensorflow/compiler/mlir/lite/experimental/tac/tac_filter.pb.h" namespace mlir { namespace TFL { namespace tac { class TacModule; // Create an instance of the TargetAnnotationPass. // TODO(b/177376459): Remove in favor of the one below. std::unique_ptr<OperationPass<func::FuncOp>> CreateTargetAnnotationPass(
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 19 19:32:06 UTC 2023 - 3.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfr/integration/tfr_decompose_ctx.h
mlir::MLIRContext* mlir_ctx); // Constructor of the decompose context. To share the decompose library, the // whole decompose TFR function library is loaded. explicit TFRDecomposeContext(mlir::ModuleOp tfr_module); // Constructs the decompose context from the tfr text module and the mlir // context. The tfr text module is added to the mlir context. static std::unique_ptr<TFRDecomposeContext> GetFromText(
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Feb 26 11:12:54 UTC 2024 - 3.2K bytes - Viewed (0) -
tensorflow/cc/saved_model/testdata/generate_saved_models.py
return 2 os.makedirs(export_path) tf_module = module_ctor() if version == 2: options = save_options.SaveOptions(save_debug_info=True) saved_model.save(tf_module, export_path, options=options) else: builder = saved_model.builder.SavedModelBuilder(export_path) builder.add_meta_graph_and_variables(tf_module, ["serve"]) builder.save() if __name__ == "__main__":
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Sep 18 18:06:18 UTC 2023 - 4.6K bytes - Viewed (0)