code: def hyperparameter_optimization(*args, **kwargs):
      """Initializes the hyperparameter optimization context
  
      Example
      -------
      >>> import sys
      >>> with hyperparameter_optimization(objective_key="error", output=sys.stdout) as hp_ctx:
      ...     result = {"error": 3.5, "train_loss": 2.1}
      ...     report_result(result)
      ...
      {"error": 3.5, "train_loss": 2.1, "objective": 3.5}
      """
      hpfit = HyperparameterOptimizationContext(args, kwargs)
      return hpfit
  
imports: import importlib
  import logging
  import json
  import os
  import speechbrain
  import sys
  from datetime import datetime
  from hyperpyyaml import load_hyperpyyaml
label_desc: Use image node_id 3 for calling a global function with example usage: hyperparameter_optimization() and returns: hpfit