"otherwise.  Experimental."),
      Flag("tf_xla_min_cluster_size",
           &mark_for_compilation_flags->tf_xla_min_cluster_size,
           "Minimum number of operators in an XLA compilation. Ignored for "
           "operators placed on an XLA device or operators explicitly marked "
           "for compilation."),
      Flag("tf_xla_max_cluster_size",
           &mark_for_compilation_flags->tf_xla_max_cluster_size,

  // Minimum number of operators in an XLA compilation. Ignored for operators
  // placed on an XLA device or operators explicitly marked for compilation.
  int32 tf_xla_min_cluster_size;

  // Maximum number of operators in an XLA compilation.
  int32 tf_xla_max_cluster_size;

  // If non-empty, limit XLA clustering to the following TF operations.
  string tf_xla_ops_to_cluster;

  debug_options.deterministic_cluster_names =
      flags->tf_xla_deterministic_cluster_names;
  debug_options.max_cluster_size = flags->tf_xla_max_cluster_size;
  debug_options.min_cluster_size = flags->tf_xla_min_cluster_size;
  debug_options.fuel = GetPointerToFuel(flags->tf_xla_clustering_fuel);
  debug_options.dump_graphs = flags->tf_xla_clustering_debug;

      strdup("--tf_xla_cpu_global_jit=true"));
  args.push_back(enable_global_jit_arg.get());

  std::unique_ptr<char, FreeDeleter> reduce_min_cluster_size_arg(
      strdup("--tf_xla_min_cluster_size=2"));
  args.push_back(reduce_min_cluster_size_arg.get());

  int argc = args.size();

  if (!tensorflow::Flags::Parse(&argc, &args.front(), flag_list)) {
    LOG(ERROR) << "\n" << usage;
    return 2;
  }

    // false, it is safe to keep these flag values as is.
    tensorflow::MarkForCompilationPassFlags* flags =
        tensorflow::GetMarkForCompilationPassFlags();
    flags->tf_xla_cpu_global_jit = true;
    flags->tf_xla_min_cluster_size = 1;
  } else {
    optimizer_options->set_global_jit_level(tensorflow::OptimizerOptions::OFF);
  }
}

unsigned char TF_SetXlaEnableLazyCompilation(unsigned char enable) {