code: def configure(cfg: DictConfig, trial: Trial) -> None:
      x_value = trial.params["x"]
      trial.suggest_float(
          "z",
          x_value - cfg.max_z_difference_from_x,
          x_value + cfg.max_z_difference_from_x,
      )
      trial.suggest_float("+w", 0.0, 1.0)
  
imports: import hydra
  from omegaconf import DictConfig
  from optuna.trial import Trial
label_desc: Use image node_id 2 for calling a global function with example usage: configure(cfg, trial) without return types