code: def add_numba_configvars():
      config.add(
          "numba__vectorize_target",
          ("Default target for numba.vectorize."),
          EnumStr("cpu", ["parallel", "cuda"], mutable=True),
          in_c_key=False,
      )
      config.add(
          "numba__fastmath",
          ("If True, use Numba's fastmath mode."),
          BoolParam(True),
          in_c_key=False,
      )
      config.add(
          "numba__cache",
          ("If True, use Numba's file based caching."),
          BoolParam(True),
          in_c_key=False,
      )
  
imports: import errno
  import logging
  import os
  import platform
  import re
  import socket
  import sys
  import textwrap
  import numpy
  from setuptools._distutils.spawn import find_executable
  import pytensor
  from pytensor.configparser import BoolParam, ConfigParam, DeviceParam, EnumStr, FloatParam, IntParam, StrParam, _create_default_config
  from pytensor.utils import LOCAL_BITWIDTH, PYTHON_INT_BITWIDTH, call_subprocess_Popen, maybe_add_to_os_environ_pathlist, output_subprocess_Popen
label_desc: Use image node_id 34 for calling a global function with example usage: add_numba_configvars() without return types