#include "tensorflow/cc/saved_model/loader.h"
#include "tensorflow/compiler/mlir/tensorflow/translate/mlir_import_options.h"

namespace tensorflow {

using tsl::Status;
using tsl::StatusOr;

struct GraphdefToMlirOptions {
  std::string debug_info_file;
  std::string xla_compile_device_type;
  bool prune_unused_nodes;
  bool convert_legacy_fed_inputs;
  bool graph_as_function;
  bool upgrade_legacy;

    const std::vector<std::optional<std::vector<int>>>& input_shapes,
    const std::vector<std::string>& output_arrays,
    const std::vector<std::string>& control_output_arrays,
    const GraphdefToMlirOptions& import_options, mlir::MLIRContext* context) {
  GraphDef graphdef;
  TF_RETURN_IF_ERROR(
      tensorflow::LoadProtoFromBuffer({input.data(), input.size()}, &graphdef));
  if (!port::kLittleEndian)

  return {ref.data(), ref.size()};
}
}  // namespace

static OwningOpRef<mlir::ModuleOp> GraphdefToMlirTranslateFunction(
    llvm::StringRef input, MLIRContext* context) {
  tensorflow::GraphdefToMlirOptions options{
      debug_info_file,        xla_compile_device_type,
      prune_unused_nodes,     convert_legacy_fed_inputs,
      graph_as_function,      upgrade_legacy,

  }

  // Register extra TF ops passed as OpDef.
  auto extra_opdefs_status = RegisterExtraTfOpDefs(extra_tf_opdefs);
  if (!extra_opdefs_status.ok()) return extra_opdefs_status;

  GraphdefToMlirOptions graphdef_conversion_options{
      std::string(debug_info_file),
      /*xla_compile_device_type=*/"",
      /*prune_unused_nodes=*/specs.prune_unused_nodes,
      /*convert_legacy_fed_inputs=*/true,