diff --git a/ppdet/data/loader.py b/ppdet/data/loader.py
index a2c6fdd0e284769abe8ec038f4972f4789e0f722..29bf8a5b090dd57b62519dc8ae1d97f97902505f 100644
--- a/ppdet/data/loader.py
+++ b/ppdet/data/loader.py
@@ -66,55 +66,6 @@ class Compose(object):
         return data
 
 
-class Prefetcher(threading.Thread):
-    def __init__(self, iterator, prefetch_num=1):
-        threading.Thread.__init__(self)
-        self.queue = Queue.Queue(prefetch_num)
-        self.iterator = iterator
-        self.daemon = True
-        self.start()
-
-    def run(self):
-        for item in self.iterator:
-            self.queue.put(item)
-        self.queue.put(None)
-
-    def next(self):
-        next_item = self.queue.get()
-        if next_item is None:
-            raise StopIteration
-        return next_item
-
-    # Python 3 compatibility
-    def __next__(self):
-        return self.next()
-
-    def __iter__(self):
-        return self
-
-
-class DataLoaderPrefetch(DataLoader):
-    def __init__(self,
-                 dataset,
-                 batch_sampler,
-                 collate_fn,
-                 num_workers,
-                 places,
-                 return_list,
-                 prefetch_num=1):
-        super(DataLoaderPrefetch, self).__init__(
-            dataset=dataset,
-            batch_sampler=batch_sampler,
-            collate_fn=collate_fn,
-            num_workers=num_workers,
-            places=places,
-            return_list=return_list)
-        self.prefetch_num = prefetch_num
-
-    def __iter__(self):
-        return Prefetcher(super().__iter__(), self.prefetch_num)
-
-
 class BaseDataLoader(object):
     __share__ = ['num_classes']
     __inject__ = ['dataset']
@@ -159,26 +110,16 @@ class BaseDataLoader(object):
                  worker_num,
                  device,
                  return_list=False,
-                 use_prefetch=False,
-                 prefetch_num=None):
-        if use_prefetch:
-            loader = DataLoaderPrefetch(
-                dataset=self._dataset,
-                batch_sampler=self._batch_sampler,
-                collate_fn=self._batch_transforms,
-                num_workers=worker_num,
-                places=device,
-                return_list=return_list,
-                prefetch_num=prefetch_num
-                if prefetch_num is not None else self.batch_size)
-        else:
-            loader = DataLoader(
-                dataset=self._dataset,
-                batch_sampler=self._batch_sampler,
-                collate_fn=self._batch_transforms,
-                num_workers=worker_num,
-                places=device,
-                return_list=return_list)
+                 use_prefetch=False):
+
+        loader = DataLoader(
+            dataset=self._dataset,
+            batch_sampler=self._batch_sampler,
+            collate_fn=self._batch_transforms,
+            num_workers=worker_num,
+            use_buffer_reader=use_prefetch,
+            places=device,
+            return_list=return_list)
 
         return loader, len(self._batch_sampler)