// 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.

    const std::vector<::tensorflow::proto_splitter::ChunkInfo>& chunks_info);

// Hashes the contents of `signature_def`.
absl::StatusOr<uint64_t> HashSignatureDef(
    const Map<std::string, ::tensorflow::SignatureDef>& signature_def_map,
    const ::tensorflow::proto_splitter::ChunkedMessage& chunked_message,
    riegeli::RecordReader<riegeli::FdReader<>>& reader,
    const std::vector<::tensorflow::proto_splitter::ChunkInfo>& chunks_info);

    for (const auto& input : inputs) {
      TensorProto tensor_proto;
      input.second.AsProtoTensorContent(&tensor_proto);
      protos.push_back({input.first, std::move(tensor_proto)});
    }
  }

  SignatureDef sig_;
  google::protobuf::Map<std::string, TensorProto> request_;
  std::map<std::string, TensorProto> unaliased_request_;
  TensorProto input_x_, input_y_, default_x_, default_y_;
};

  // (TF1 SavedModel only) Collection of tags identifying the MetaGraphDef
  // within the SavedModel to analyze. If not specified, ["serve"] is used.
  repeated string tags = 5;

  // Sequence of keys identifying SignatureDef containing inputs and outputs.
  // If not specified, ["serving_default"] is used.
  repeated string signature_keys = 6;

  // A map from signature keys to the corresponding representative dataset.