code: def run(self, data, max_epochs=1):
          
  
          self.state = State(dataloader=data, epoch=0, max_epochs=max_epochs, metrics={})
  
          try:
              self._logger.info("Engine run starting with max_epochs={}.".format(max_epochs))
              start_time = time.time()
              self._fire_event(Events.STARTED)
              while self.state.epoch < max_epochs and not self.should_terminate:
                  self.state.epoch += 1
                  self._fire_event(Events.EPOCH_STARTED)
                  hours, mins, secs = self._run_once_on_dataset()
                  self._logger.info("Epoch[%s] Complete. Time taken: %02d:%02d:%02d", self.state.epoch, hours, mins, secs)
                  if self.should_terminate:
                      break
                  self._fire_event(Events.EPOCH_COMPLETED)
  
              self._fire_event(Events.COMPLETED)
              time_taken = time.time() - start_time
              hours, mins, secs = _to_hours_mins_secs(time_taken)
              self._logger.info("Engine run complete. Time taken %02d:%02d:%02d" % (hours, mins, secs))
  
          except BaseException as e:
              self._logger.error("Engine run is terminating due to exception: %s.", str(e))
              self._handle_exception(e)
  
          return self.state
docs: Runs the process_function over the passed data.
  
          Args:
              data (Iterable): Collection of batches allowing repeated iteration (e.g., list or `DataLoader`).
              max_epochs (int, optional): max epochs to run for (default: 1).
  
          Returns:
              State: output state.