#include "tensorflow/core/framework/types.pb.h"
#include "tensorflow/core/lib/core/errors.h"
#include "tensorflow/core/platform/errors.h"
#include "tensorflow/core/platform/types.h"

namespace tensorflow {

std::string GraphImportConfig::str() const {
  std::ostringstream ss;

  ss << "graph_func_name: " << graph_func_name;
  InputArrays inputs;
  ss << "\ninputs: ";
  for (auto& it : inputs) {
    ss << "\n\t" << it.first << " -> "

                                      bool show_debug_info,
                                      GraphDebugInfo& debug_info,
                                      GraphImportConfig& specs,
                                      TF_Status* status) {
  GraphDef graphdef;
  auto s = tensorflow::LoadProtoFromBuffer(proto, &graphdef);
  if (!s.ok()) {
    tsl::Set_TF_Status_from_Status(status, s);

  }

  GraphDebugInfo debug_info;
  mlir::DialectRegistry registry;
  RegisterDialects(registry);
  mlir::MLIRContext context(registry);
  GraphImportConfig import_config;
  import_config.graph_as_function = true;
  import_config.control_outputs = *control_ret_node_names;
  import_config.upgrade_legacy = true;

absl::StatusOr<OwningOpRef<ModuleOp>> LoadFromGraphdefOrMlirSource(
    const std::string& input_filename, bool input_mlir,
    bool use_splatted_constant, const std::vector<std::string>& extra_tf_opdefs,
    const GraphImportConfig& specs, absl::string_view debug_info_file,
    absl::string_view input_arrays, absl::string_view input_dtypes,
    absl::string_view input_shapes, absl::string_view output_arrays,

  absl::Span<std::string> exported_names(exported_names_in_vector);

  if (exported_names.empty()) {
    return errors::Unimplemented("Need at least one exported name.");
  }

  tensorflow::GraphImportConfig specs;
  specs.upgrade_legacy = true;

  std::vector<std::string> custom_opdefs(toco_flags.custom_opdefs().begin(),
                                         toco_flags.custom_opdefs().end());

  GraphDebugInfo debug_info;
  if (!import_options.debug_info_file.empty()) {
    TF_RETURN_IF_ERROR(
        LoadProtoFromFile(import_options.debug_info_file, &debug_info));
  }

  GraphImportConfig specs;
  specs.prune_unused_nodes = import_options.prune_unused_nodes;
  specs.convert_legacy_fed_inputs = import_options.convert_legacy_fed_inputs;
  specs.graph_as_function = import_options.graph_as_function;

      absl::StrSplit(exported_model_signatures, ',');
  absl::Span<std::string> exported_names(exported_names_in_vector);
  std::vector<std::string> custom_opdefs;

  tensorflow::GraphImportConfig specs;
  specs.upgrade_legacy = true;

  return ImportSavedModel(input_path, /*saved_model_version=*/1, tags,
                          absl::MakeSpan(custom_opdefs), exported_names, specs,

    context.appendDialectRegistry(registry);
  }

  absl::StatusOr<mlir::OwningOpRef<mlir::ModuleOp>> module;
  std::unordered_set<std::string> tags;

  tensorflow::GraphImportConfig specs;
  specs.upgrade_legacy = upgrade_legacy;
  specs.prune_unused_nodes = true;

  if (!select_user_tf_ops.empty() && !emit_select_tf_ops) {

    mlir::MLIRContext* context) {
  mlir::DialectRegistry registry;
  RegisterDialects(registry);
  context->appendDialectRegistry(registry);
  GraphImportConfig config;
  config.graph_as_function = true;
  config.control_outputs = control_rets;
  // Disable shape inference during import as some TensorFlow op fails during