// Finds and returns the MetaGraphDef (within the provided SavedModel) that
// matches the given set of tags. The lifetime of the returned MetaGraphDef is
// the same as the lifetime of `saved_model_proto`.
//
// FindMetaGraphDef returns a failure status when no MetaGraphDef matches the
// provided tags.
absl::StatusOr<MetaGraphDef*> FindMetaGraphDef(

    return meta_graph_def.signature_def();
  }

  std::unique_ptr<Session> session;
  MetaGraphDef meta_graph_def;
  std::unique_ptr<GraphDebugInfo> debug_info;
};

// A version of SavedModelBundle that avoids storing a potentially large
// MetaGraphDef. Prefer to use SavedModelBundleLite in new code.
class SavedModelBundleLite : public SavedModelBundleInterface {
 public:

 public:
  SavedModelMLIRImportInput(const MetaGraphDef* meta_graph_def,
                            const GraphDebugInfo& debug_info)
      : meta_graph_def_(meta_graph_def), debug_info_(debug_info) {
    DCHECK(meta_graph_def);
  }

  virtual ~SavedModelMLIRImportInput();

  // The original MetaGraphDef of the savedmodel.
  const MetaGraphDef& meta_graph_def() const { return *meta_graph_def_; }

// in the SignatureDef (v2) or a collection (v1). If an init_op collection
// exists, then the collection must contain exactly one op.
Status GetInitOp(const string& export_dir, const MetaGraphDef& meta_graph_def,
                 string* init_op_name) {
  const auto& sig_def_map = meta_graph_def.signature_def();
  const auto& init_op_sig_it =
      meta_graph_def.signature_def().find(kSavedModelInitOpSignatureKey);

  // exported model is produced. It is used to copy the asset files to
  // `dst_saved_model_path`. `tags` will be attached to the saved
  // `MetaGraphDef`. `signature_def_map` will be passed to the
  // `add_meta_graph_and_variables` function, which is internally used to add a
  // `MetaGraphDef` to save to the SavedModel.
  //
  // Returns `true` if successful. Returns `std::nullopt` otherwise.
  //

#define IS_OSS true

namespace tensorflow {

absl::StatusOr<MetaGraphDef*> FindMetaGraphDef(
    const std::unordered_set<string>& tags, SavedModel* saved_model_proto) {
  LOG(INFO) << "Reading meta graph with tags { " << absl::StrJoin(tags, " ")
            << " }";
  for (MetaGraphDef& graph_def : *saved_model_proto->mutable_meta_graphs()) {
    // Get tags from the graph_def.

// Loads a SavedModel at `saved_model_path` and converts it to `mlir::ModuleOp`.
//
// `tags` identify the `tensorflow::MetaGraphDef` to load from the SavedModel.
// Similarly, `signature_keys` identify the functions (`SignatureDef`s) to load
// within the `MetaGraphDef`. `ctx` is the `MLIRContext`, which should outlive
// the returned `ModuleOp`, thus marked with the lifetime bound attribute.

// An empty init_op_name indicates that there are no init ops to run.
Status RunInitOp(const RunOptions& run_options, const string& export_dir,
                 const MetaGraphDef& meta_graph_def,
                 const std::vector<AssetFileDef>& asset_file_defs,
                 Session* session, const string& init_op_name) {
  if (!init_op_name.empty()) {

  metrics::SavedModelReadPath().Set(export_dir);

  // Load MetaGraphDef.
  // In version 2 SavedModels, there is only one MetaGraphDef.
  if (saved_model_proto.meta_graphs_size() != 1) {
    return absl::Status(
        absl::StatusCode::kInvalidArgument,
        strings::StrCat(
            "SavedModelV2 should have exactly one MetaGraphDef but actually ",
            "contains ", saved_model_proto.meta_graphs_size()));
  }

  the representative dataset for the actual data provided for inference.

  Args:
    model_dir: Path to SavedModel directory.
    tags: Collection of tags identifying the MetaGraphDef within the SavedModel.
    representative_dataset_map: A map where signature keys are mapped to
      corresponding representative datasets.

  Raises: