diff --git a/python/paddle/fluid/dataloader/dataloader_iter.py b/python/paddle/fluid/dataloader/dataloader_iter.py
index ac6e05248f72d5a0499138586b25f6f35c4822af..6753c18da464926dbc5c18d71046cd95b88d441b 100644
--- a/python/paddle/fluid/dataloader/dataloader_iter.py
+++ b/python/paddle/fluid/dataloader/dataloader_iter.py
@@ -128,8 +128,10 @@ class _DataLoaderIterSingleProcess(_DataLoaderIterBase):
         self._need_check_feed = [
             v.desc.need_check_feed() for v in self._feed_list
         ]
+        # if only 1 place, do not need to keep order
         self._blocking_queue = core.init_lod_tensor_blocking_queue(
-            core.Variable(), self._blocking_queue_capacity, True)
+            core.Variable(), self._blocking_queue_capacity,
+            len(self._places) > 1)
         self._reader = core.create_py_reader(
             self._blocking_queue, self._var_names, self._shapes, self._dtypes,
             self._need_check_feed, self._places, self._use_buffer_reader, True)
@@ -280,8 +282,9 @@ class _DataLoaderIterMultiProcess(_DataLoaderIterBase):
         self._need_check_feed = [
             v.desc.need_check_feed() for v in self._feed_list
         ]
+        # if only 1 place, do not need to keep order
         self._blocking_queue = core.init_lod_tensor_blocking_queue(
-            core.Variable(), self._outstanding_capacity, True)
+            core.Variable(), self._outstanding_capacity, len(self._places) > 1)
         self._reader = core.create_py_reader(
             self._blocking_queue, self._var_names, self._shapes, self._dtypes,
             self._need_check_feed, self._places, self._use_buffer_reader, True)
@@ -442,6 +445,11 @@ class _DataLoaderIterMultiProcess(_DataLoaderIterBase):
                 #    get data again
                 data = self._data_queue.get(timeout=self._timeout)
             except Exception as e:
+                # check if thread done event set when waiting data
+                if self._thread_done_event.is_set():
+                    continue
+
+                # check failed workers
                 failed_workers = []
                 for i, w in enumerate(self._workers):
                     if self._worker_status[i] and not w.is_alive():
diff --git a/python/paddle/fluid/tests/unittests/test_multiprocess_dataloader_dynamic.py b/python/paddle/fluid/tests/unittests/test_multiprocess_dataloader_dynamic.py
index 6af273faf3942f19e0612811f644f6606417394c..0706eb53d537da58a5a248e060759b748b30af19 100644
--- a/python/paddle/fluid/tests/unittests/test_multiprocess_dataloader_dynamic.py
+++ b/python/paddle/fluid/tests/unittests/test_multiprocess_dataloader_dynamic.py
@@ -28,12 +28,7 @@ from paddle.fluid.dygraph.nn import Linear
 from paddle.fluid.dygraph.base import to_variable
 
 from test_multiprocess_dataloader_static import RandomDataset, prepare_places
-
-EPOCH_NUM = 5
-BATCH_SIZE = 16
-IMAGE_SIZE = 784
-SAMPLE_NUM = 400
-CLASS_NUM = 10
+from test_multiprocess_dataloader_static import EPOCH_NUM, BATCH_SIZE, IMAGE_SIZE, SAMPLE_NUM, CLASS_NUM
 
 
 class SimpleFCNet(fluid.dygraph.Layer):
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 6b5996f3283e5e31dd640088cba1dbdabbd40ef9..38497f91fc18847e40efa691a65c2a7adc20e51c 100644
--- a/python/paddle/fluid/tests/unittests/test_multiprocess_dataloader_static.py
+++ b/python/paddle/fluid/tests/unittests/test_multiprocess_dataloader_static.py
@@ -25,10 +25,10 @@ import numpy as np
 import paddle.fluid as fluid
 from paddle.io import Dataset, BatchSampler, DataLoader
 
-EPOCH_NUM = 5
-BATCH_SIZE = 16
-IMAGE_SIZE = 784
-SAMPLE_NUM = 400
+EPOCH_NUM = 3
+BATCH_SIZE = 8
+IMAGE_SIZE = 32
+SAMPLE_NUM = 100
 CLASS_NUM = 10
 
 
@@ -157,10 +157,6 @@ class TestStaticDataLoader(unittest.TestCase):
         return ret
 
     def test_main(self):
-        # FIXME(dkp): disable for random fail in Py35 cloud, 
-        #             should be fixed ASAP
-        if sys.version[:3] == '3.5':
-            return
         for p in prepare_places(True):
             results = []
             for num_workers in [0, 2]: