code: def _objective_func(trial: optuna.trial.Trial) -> float:
      x = trial.suggest_float("x", -1.0, 1.0)
      y = trial.suggest_float("y", 20, 30, log=True)
      z = trial.suggest_categorical("z", (-1.0, 1.0))
      trial.set_user_attr("my_user_attr", "my_user_attr_value")
      return (x - 2) ** 2 + (y - 25) ** 2 + z
  
imports: from typing import Callable
  from typing import List
  from typing import Optional
  from typing import Tuple
  from typing import Union
  import numpy
  import py
  import pytest
  import optuna
  from optuna._imports import try_import
  from optuna.integration.mlflow import MLflowCallback
label_desc: Use image node_id 1 for calling a global function with example usage: _objective_func(trial) and returns: unknown