code: def test_param_example() -> None:
      # DOC_PARAM_0
      import nevergrad as ng
  
      # build a parameter providing a dict value:
      param = ng.p.Dict(
          # logarithmically distributed float
          log=ng.p.Log(lower=0.01, upper=1.0),
          # one-dimensional array of length 2
          array=ng.p.Array(shape=(2,)),
          # character, either "a" or "b or "c".
          char=ng.p.Choice(["a", "b", "c"]),
      )
  
      print(param.value)
      # {'log': 0.01,
      #  'array': array([0., 0.]),
      #  'char': 'a'}
      # DOC_PARAM_1
  
      # DOC_PARAM_10
      # create a new instance
      child = param.spawn_child()
      # update its value
      child.value = {
          "log": 0.2,
          "array": np.array([12.0, 13.0]),
          "char": "c",
      }
  
      # export to standardized space
      data = child.get_standardized_data(reference=param)
      print(data)
      # np.array([12., 13.,  0.,  0., 0.69, 0.90])
      # DOC_PARAM_11
  
      # DOC_PARAM_100
      param.mutate()
      print(param.value)
      # {'log': 0.155,
      #  'array': np.array([-0.966, 0.045]),
      #  'char': 'a'}
  
      # increase the step/sigma for array
      # (note that it's advised to to this during the creation
      #  of the variable:
      #  array=ng.p.Array(shape=(2,)).set_mutation(sigma=10))
      param["array"].set_mutation(sigma=10)  # type: ignore
      param.mutate()
      print(param.value)
      # {'log': 0.155,
      #  'array': np.array([-9.47, 8.38]),  # larger mutation
      #  'char': 'a'}
  
      # DOC_PARAM_101
  
      # DOC_PARAM_1000
      param.random_state.seed(12)
  
label_desc: Use image node_id 2 for calling a global function with example usage: test_param_example() without return types