diff --git a/python/paddle/fluid/reader.py b/python/paddle/fluid/reader.py
index 4a50b3bc0c7dc581febdaf12ab70c663c0263377..ac924580e17e8885346cab51c696dddb43279ba6 100644
--- a/python/paddle/fluid/reader.py
+++ b/python/paddle/fluid/reader.py
@@ -196,7 +196,7 @@ class DataLoader(object):
             the key of the dict is the name of each fed variables. If 
             :attr:`return_list=True`, the return value on each device would
             be a list(Tensor). :attr:`return_list` can only be True
-            in dynamic graph mode. Default False.
+            in dynamic graph mode. Default True.
         batch_sampler(BatchSampler): an instance of `paddle.io.BatchSampler`
             to generate batch indices to draw samples from :attr:`dataset`
             and combine a batch. Default None.
@@ -308,7 +308,7 @@ class DataLoader(object):
                  dataset,
                  feed_list=None,
                  places=None,
-                 return_list=False,
+                 return_list=True,
                  batch_sampler=None,
                  batch_size=1,
                  shuffle=False,
@@ -403,10 +403,10 @@ class DataLoader(object):
         if self.dataset_kind == _DatasetKind.ITER:
             raise ValueError("length of IterableDataset not supported")
         else:
-            if self.batch_size is None:
-                return len(self.dataset)
-            else:
+            if self.auto_collate_batch:
                 return len(self.batch_sampler)
+            else:
+                return len(self.dataset)
 
     def __iter__(self):
         if self.num_workers == 0:
diff --git a/python/paddle/fluid/tests/unittests/test_multiprocess_dataloader_iterable_dataset_static.py b/python/paddle/fluid/tests/unittests/test_multiprocess_dataloader_iterable_dataset_static.py
index 4615bf85ce69f45cf6d852cdb17e5dff1d533979..fe66f1733546bd3e9296f3355982ae5fa633a7aa 100644
--- a/python/paddle/fluid/tests/unittests/test_multiprocess_dataloader_iterable_dataset_static.py
+++ b/python/paddle/fluid/tests/unittests/test_multiprocess_dataloader_iterable_dataset_static.py
@@ -112,6 +112,7 @@ class TestStaticDataLoader(unittest.TestCase):
                 places=places,
                 num_workers=num_workers,
                 batch_size=BATCH_SIZE,
+                return_list=False,
                 drop_last=True)
             # assert len(dataloader) == int(SAMPLE_NUM / BATCH_SIZE)
 
@@ -199,6 +200,7 @@ class TestStaticDataLoaderWithBatchedDataset(TestStaticDataLoader):
                 places=places,
                 num_workers=num_workers,
                 batch_size=None,
+                return_list=False,
                 drop_last=True)
 
             exe = fluid.Executor(place=places[0])
diff --git a/python/paddle/fluid/tests/unittests/test_multiprocess_dataloader_static.py b/python/paddle/fluid/tests/unittests/test_multiprocess_dataloader_static.py
index 5ec907c290b946dc79ee6f865c42fd8094afbb35..8fd250f2a52c27e2e2fa6a6a6c917e55af292d6c 100644
--- a/python/paddle/fluid/tests/unittests/test_multiprocess_dataloader_static.py
+++ b/python/paddle/fluid/tests/unittests/test_multiprocess_dataloader_static.py
@@ -113,6 +113,7 @@ class TestStaticDataLoader(unittest.TestCase):
                 places=places,
                 num_workers=num_workers,
                 batch_size=BATCH_SIZE,
+                return_list=False,
                 drop_last=True)
             assert len(dataloader) == int(SAMPLE_NUM / BATCH_SIZE)
 
@@ -226,7 +227,8 @@ class RandomBatchedDataset(Dataset):
         labels = []
         for _ in range(BATCH_SIZE):
             image = np.random.random([IMAGE_SIZE]).astype('float32')
-            label = np.random.randint(0, self.class_num - 1, (1, )).astype('int64')
+            label = np.random.randint(0, self.class_num - 1,
+                                      (1, )).astype('int64')
             images.append(image)
             labels.append(label)
         return np.stack(images, axis=0), np.stack(labels, axis=0)
@@ -248,6 +250,7 @@ class TestStaticDataLoaderWithBatchedDataset(TestStaticDataLoader):
                 places=places,
                 num_workers=num_workers,
                 batch_size=None,
+                return_list=False,
                 drop_last=True)
             assert len(dataloader) == int(SAMPLE_NUM / BATCH_SIZE)