code: def test_categorical_transform():
      categories = ["apple", "orange", "banana", None, True, False, 3]
      cat = Categorical(categories)
  
      apple = [1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
      orange = [0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0]
      banana = [0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0]
      none = [0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0]
      true = [0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0]
      false = [0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0]
      three = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0]
  
      assert_equal(cat.transformed_size, 7)
      assert_equal(cat.transformed_size, cat.transform(["apple"]).size)
      assert_array_equal(
          cat.transform(categories),
          [apple, orange, banana, none, true, false, three],
      )
      assert_array_equal(
          cat.transform(["apple", "orange"]), [apple, orange]
      )
      assert_array_equal(
          cat.transform(["apple", "banana"]), [apple, banana]
      )
      assert_array_equal(
          cat.inverse_transform([apple, orange]), ["apple", "orange"]
      )
      assert_array_equal(
          cat.inverse_transform([apple, banana]), ["apple", "banana"]
      )
      ent_inverse = cat.inverse_transform(
          [apple, orange, banana, none, true, false, three]
      )
      assert_array_equal(ent_inverse, categories)
  
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 9 for calling a global function with example usage: test_categorical_transform() without return types