code: def minimize(self, *args, **kwargs):
          '''Optimize our loss exhaustively.
  
          This method is a thin wrapper over the :func:`iterate` method. It simply
          exhausts the iterative optimization process and returns the final
          monitor values.
  
          Returns
          -------
          train_monitors : dict
              A dictionary mapping monitor names to values, evaluated on the
              training dataset.
          valid_monitors : dict
              A dictionary containing monitor values evaluated on the validation
              dataset.
          '''
          monitors = None
          for monitors in self.iterate(*args, **kwargs):
              pass
          return monitorf minimize(self, *args, **kwargs):
          '''Optimize our loss exhaustively.
  
          This method is a thin wrapper over the :func:`iterate` method. It simply
          exhausts the iterative optimization process and returns the final
          monitor values.
  
          Returns
          -------
          train_monitors : dict
              A dictionary mapping monitor names to values, evaluated on the
              training dataset.
          valid_monitors : dict
              A dictionary containing monitor values evaluated on the validation
              dataset.
          '''
          monitors = None
          for monitors in self.iterate(*args, **kwargs):
              pass
          return monitors
docs: Optimize our loss exhaustively.
  
          This method is a thin wrapper over the :func:`iterate` method. It simply
          exhausts the iterative optimization process and returns the final
          monitor values.
  
          Returns
          -------
          train_monitors : dict
              A dictionary mapping monitor names to values, evaluated on the
              training dataset.
          valid_monitors : dict
              A dictionary containing monitor values evaluated on the validation
              dataset.