class_docstr: A generic hyperparameter fit reporter that outputs the result as
  JSON to an arbitrary data stream, which may be read as a third-party
  tool
  
  Arguments
  ---------
  objective_key: str
      the key from the result dictionary to be used as the objective
code: def __init__(self, reference_date=None, output=None, *args, **kwargs):
      super().__init__(*args, **kwargs)
      self.output = output or sys.stdout
      self.reference_date = reference_date
      self._trial_id = None
  
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 1 to create a new GenericHyperparameterOptimizationReporter object from inherited base classes: HyperparameterOptimizationReporter with example: obj = GenericHyperparameterOptimizationReporter(reference_date, output)