code: def test_real_log_sampling_in_bounds():
      dim = Real(
          low=1, high=32, prior="log-uniform", transform="normalize"
      )
  
      # round trip a value that is within the bounds of the space
      #
      # x = dim.inverse_transform(dim.transform(31.999999999999999))
      for n in (32.0, 31.999999999999999):
          round_tripped = dim.inverse_transform(dim.transform([n]))
          assert np.allclose([n], round_tripped)
          assert n in dim
          assert round_tripped in dim
  
imports: import pytest
  import numbers
  import numpy
  import os
  import yaml
  from tempfile import NamedTemporaryFile
  from numpy.testing import assert_array_almost_equal
  from numpy.testing import assert_array_equal
  from numpy.testing import assert_equal
  from numpy.testing import assert_raises_regex
  from skopt import Optimizer
  from skopt.space import Space
  from skopt.space import Real
  from skopt.space import Integer
  from skopt.space import Categorical
  from skopt.space import check_dimension
  from skopt.utils import normalize_dimensions
label_desc: Use image node_id 5 for calling a global function with example usage: test_real_log_sampling_in_bounds() without return types