diff --git a/fastNLP/core/trainer.py b/fastNLP/core/trainer.py
index f4f8a093..f90070c1 100644
--- a/fastNLP/core/trainer.py
+++ b/fastNLP/core/trainer.py
@@ -558,7 +558,7 @@ def __init__(self, train_data, model, optimizer=None, loss=None,
                     check_batch_size = max(len(self.model.device_ids), check_batch_size)
             _check_code(dataset=train_data, model=self.model, losser=losser, forward_func=self._forward_func, metrics=metrics,
                         dev_data=dev_dataset, metric_key=self.metric_key, check_level=check_code_level,
-                        batch_size=check_batch_size)
+                        batch_size=check_batch_size, pin_memory=self.pin_memory)
 
         self.train_data = train_data
         self.dev_data = dev_data  # If None, No validation.
@@ -950,7 +950,7 @@ def _get_value_info(_dict):
     return strs
 
 
-def _check_code(dataset, model, losser, metrics, forward_func, batch_size=DEFAULT_CHECK_BATCH_SIZE,
+def _check_code(dataset, model, losser, metrics, forward_func, pin_memory, batch_size=DEFAULT_CHECK_BATCH_SIZE,
                 dev_data=None, metric_key=None, check_level=0):
     # check get_loss 方法
     model_device = _get_model_device(model=model)
@@ -1010,7 +1010,7 @@ def _check_code(dataset, model, losser, metrics, forward_func, batch_size=DEFAUL
     
     if dev_data is not None:
         tester = Tester(data=dev_data[:batch_size * DEFAULT_CHECK_NUM_BATCH], model=model, metrics=metrics,
-                        batch_size=batch_size, verbose=-1, use_tqdm=False)
+                        batch_size=batch_size, verbose=-1, use_tqdm=False, pin_memory=pin_memory)
         evaluate_results = tester.test()
         _check_eval_results(metrics=evaluate_results, metric_key=metric_key, metric_list=metrics)