code: def ensemble(subresults: List[Dict[str, torch.Tensor]]) -> torch.Tensor:
      
  
      # Choose the highest average confidence span.
  
      span_start_probs = sum(subresult['span_start_probs'] for subresult in subresults) / len(subresults)
      span_end_probs = sum(subresult['span_end_probs'] for subresult in subresults) / len(subresults)
      return get_best_span(span_start_probs.log(), span_end_probs.log())
docs: Identifies the best prediction given the results from the submodels.
  
      Parameters
      ----------
      subresults : List[Dict[str, torch.Tensor]]
          Results of each submodel.
  
      Returns
      -------
      The index of the best submodel.