code: def learn_mealy_machine(self):
          
          logging.info('Initializing learning procedure.')
          self._init_table()
  
          logging.info('Generating a closed and consistent observation table.')
          while True:
  
              closed = False
              # Make sure that the table is closed and consistent
              while not closed:
  
                  logging.debug('Checking if table is closed.')
                  closed, string = self.observation_table.is_closed()
                  if not closed:
                      logging.debug('Closing table.')
                      self._ot_make_closed(string)
                  else:
                      logging.debug('Table closed.')
  
              # Create conjecture
              mma = self.get_mealy_conjecture()
  
              logging.info('Generated conjecture machine with %d states.',
                           len(list(mma.states)))
  
              # _check correctness
              logging.debug('Running equivalence query.')
              found, counter_example = self._equivalence_query(mma)
  
              # Are we done?
              if found:
                  logging.info('No counterexample found. Hypothesis is correct!')
                  break
  
              # Add the new experiments into the table to reiterate the
              # learning loop
              logging.info(
                  'Processing counterexample %input_string with length %d.',
                  counter_example,
                  len(counter_example))
              self._process_counter_example(mma, counter_example)
  
          logging.info('Learning complete.')
          return mma
docs: Implements the high level loop of the algorithm for learning a
          Mealy machine.
          Args:
              None
          Returns:
              MealyMachine: The learned mealy machine