1. 修复Tester测试过程中出现异常model不能重置为Training状态的bug; 2. FitlogCallback, EvaluateCallback在遭遇exception时直接raise，防止出现metric没有重新归零的问题

fastNLP/core/callback.py

@@ -592,9 +592,10 @@ class FitlogCallback(Callback):
                     fitlog.add_metric(eval_result, name=key, step=self.step, epoch=self.epoch)
                     if better_result:
                         fitlog.add_best_metric(eval_result, name=key)
-                except Exception:
+                except Exception as e:
                     self.pbar.write("Exception happens when evaluate on DataSet named `{}`.".format(key))
-    
+                    raise e
+
     def on_train_end(self):
         fitlog.finish()
     
@@ -660,9 +661,9 @@ class EvaluateCallback(Callback):
                     eval_result = tester.test()
                     self.logger.info("EvaluateCallback evaluation on {}:".format(key))
                     self.logger.info(tester._format_eval_results(eval_result))
-                except Exception:
+                except Exception as e:
                     self.logger.error("Exception happens when evaluate on DataSet named `{}`.".format(key))
-
+                    raise e
 
 class LRScheduler(Callback):
     """

fastNLP/core/tester.py

@@ -189,10 +189,10 @@ class Tester(object):
             _check_loss_evaluate(prev_func_signature=prev_func_signature, func_signature=e.func_signature,
                                  check_res=e.check_res, pred_dict=pred_dict, target_dict=batch_y,
                                  dataset=self.data, check_level=0)
-        
+        finally:
+            self._mode(network, is_test=False)
         if self.verbose >= 1:
             logger.info("[tester] \n{}".format(self._format_eval_results(eval_results)))
-        self._mode(network, is_test=False)
         return eval_results
     
     def _mode(self, model, is_test=False):