code: def test_dtype_setting(
      getter: Callable[[], type],
      setter: Callable[[type], None],
      valid_type_1: type,
      valid_type_2: type,
  ) -> None:
      if valid_type_1 == valid_type_2:
          raise ValueError(
              "cannot test config setting/getting when both types are equal"
          )
      setter(valid_type_1)
      assert getter() == valid_type_1
      setter(valid_type_2)
      assert getter() == valid_type_2
  
imports: import os
  from typing import Any, Callable, Iterable
  from unittest import mock
  import numpy
  import pytest
  import tensorflow
  import gpflow
  from gpflow.base import TensorData
  from gpflow.config import config, default_float, default_int, default_jitter, default_likelihood_positive_minimum, default_positive_bijector, default_positive_minimum, default_summary_fmt, set_config, set_default_float, set_default_int, set_default_jitter, set_default_likelihood_positive_minimum, set_default_positive_bijector, set_default_positive_minimum, set_default_summary_fmt
  from gpflow.utilities import to_default_float, to_default_int
label_desc: Use image node_id 4 for calling a global function with example usage: test_dtype_setting(getter, setter, valid_type_1, valid_type_2) without return types