diff --git a/python/paddle/fluid/dataloader/dataloader_iter.py b/python/paddle/fluid/dataloader/dataloader_iter.py
index 3deff6e2d4055524343adde90f80ddbf4a3927e6..b57f43aaeb8ecf76ac46e1cfbdd75cb674624bc7 100644
--- a/python/paddle/fluid/dataloader/dataloader_iter.py
+++ b/python/paddle/fluid/dataloader/dataloader_iter.py
@@ -276,13 +276,12 @@ class _DataLoaderIterSingleProcess(_DataLoaderIterBase):
                         data = self._reader.read_next_list()
                         for i in range(len(data)):
                             data[i] = data[i]._move_to_list()
-                        data = [
-                            _restore_batch(d, s)
-                            for d, s in zip(data, self._structure_infos[:len(
-                                self._places)])
+                        structs = [
+                            self._structure_infos.pop(0)
+                            for _ in range(len(self._places))
                         ]
-                        self._structure_infos = self._structure_infos[len(
-                            self._places):]
+                        data = [_restore_batch(d, s) \
+                                for d, s in zip(data, structs)]
                         # static graph organized data on multi-device with list, if
                         # place number is 1, there is only 1 device, extra the data
                         # from list for devices to be compatible with dygraph mode
@@ -751,13 +750,12 @@ class _DataLoaderIterMultiProcess(_DataLoaderIterBase):
                         data = self._reader.read_next_list()
                         for i in range(len(data)):
                             data[i] = data[i]._move_to_list()
-                        data = [
-                            _restore_batch(d, s)
-                            for d, s in zip(data, self._structure_infos[:len(
-                                self._places)])
+                        structs = [
+                            self._structure_infos.pop(0)
+                            for _ in range(len(self._places))
                         ]
-                        self._structure_infos = self._structure_infos[len(
-                            self._places):]
+                        data = [_restore_batch(d, s) \
+                                for d, s in zip(data, structs)]
                         # static graph organized data on multi-device with list, if
                         # place number is 1, there is only 1 device, extra the data
                         # from list for devices to be compatible with dygraph mode
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 9f73ee041e0e2434521c3cc86b3d87324a153c42..ff280375499c8108b664a4935303bde735109d7d 100644
--- a/python/paddle/fluid/tests/unittests/test_multiprocess_dataloader_static.py
+++ b/python/paddle/fluid/tests/unittests/test_multiprocess_dataloader_static.py
@@ -22,6 +22,7 @@ import unittest
 import multiprocessing
 import numpy as np
 
+import paddle
 import paddle.fluid as fluid
 from paddle.io import Dataset, BatchSampler, DataLoader
 
@@ -181,7 +182,7 @@ class TestStaticDataLoader(unittest.TestCase):
 
 
 class TestStaticDataLoaderReturnList(unittest.TestCase):
-    def test_single_place(self):
+    def run_single_place(self, num_workers):
         scope = fluid.Scope()
         image = fluid.data(
             name='image', shape=[None, IMAGE_SIZE], dtype='float32')
@@ -191,7 +192,7 @@ class TestStaticDataLoaderReturnList(unittest.TestCase):
             dataloader = DataLoader(
                 dataset,
                 feed_list=[image, label],
-                num_workers=0,
+                num_workers=num_workers,
                 batch_size=BATCH_SIZE,
                 drop_last=True,
                 return_list=True)
@@ -202,7 +203,7 @@ class TestStaticDataLoaderReturnList(unittest.TestCase):
                 assert not isinstance(d[0], list)
                 assert not isinstance(d[1], list)
 
-    def test_multi_place(self):
+    def run_multi_place(self, num_workers):
         scope = fluid.Scope()
         image = fluid.data(
             name='image', shape=[None, IMAGE_SIZE], dtype='float32')
@@ -212,7 +213,7 @@ class TestStaticDataLoaderReturnList(unittest.TestCase):
             dataloader = DataLoader(
                 dataset,
                 feed_list=[image, label],
-                num_workers=0,
+                num_workers=num_workers,
                 batch_size=BATCH_SIZE,
                 places=[fluid.CPUPlace()] * 2,
                 drop_last=True,
@@ -224,6 +225,12 @@ class TestStaticDataLoaderReturnList(unittest.TestCase):
                 assert isinstance(d[0], list)
                 assert isinstance(d[1], list)
 
+    def test_main(self):
+        paddle.enable_static()
+        for num_workers in [0, 2]:
+            self.run_single_place(num_workers)
+            self.run_multi_place(num_workers)
+
 
 class RandomBatchedDataset(Dataset):
     def __init__(self, sample_num, class_num):