diff --git a/paddle/fluid/framework/data_set.cc b/paddle/fluid/framework/data_set.cc
index f0c8ccc243c596cb04ea60320fc510478bbbf354..114496085429b18607ff84178e181c36bd2d1adb 100644
--- a/paddle/fluid/framework/data_set.cc
+++ b/paddle/fluid/framework/data_set.cc
@@ -352,8 +352,6 @@ void DatasetImpl<T>::CreateReaders() {
   VLOG(3) << "Filelist size in Dataset: " << filelist_.size();
   VLOG(3) << "channel num in Dataset: " << channel_num_;
   CHECK(thread_num_ > 0) << "thread num should > 0";
-  CHECK(thread_num_ <= filelist_.size())
-      << "thread num should <= filelist size";
   CHECK(channel_num_ > 0) << "channel num should > 0";
   CHECK(channel_num_ <= thread_num_) << "channel num should <= thread num";
   VLOG(3) << "readers size: " << readers_.size();
diff --git a/paddle/fluid/framework/pull_dense_worker.cc b/paddle/fluid/framework/pull_dense_worker.cc
index 20d7f98e93695107637107c60f5ef42b8ce9293d..3fe0d516e2d5417b958dbfc1c6b13d15ed2be127 100644
--- a/paddle/fluid/framework/pull_dense_worker.cc
+++ b/paddle/fluid/framework/pull_dense_worker.cc
@@ -80,6 +80,9 @@ void PullDenseWorker::Stop() {
   if (running_) {
     running_ = false;
     t_.join();
+    // pull dense when stop, to make sure local dense params are same as
+    // pserver, so save paddle model will save dense model same as pserver
+    PullDense(true);
   }
 }
 
diff --git a/python/paddle/fluid/dataset.py b/python/paddle/fluid/dataset.py
index 902a33b614675eeac0d6bf643b3b519325fd150d..20ffd13d605779a5298efd10d947cf55868905f3 100644
--- a/python/paddle/fluid/dataset.py
+++ b/python/paddle/fluid/dataset.py
@@ -246,6 +246,8 @@ class InMemoryDataset(DatasetBase):
         """
         if self.thread_num > len(self.filelist):
             self.thread_num = len(self.filelist)
+        if self.thread_num == 0:
+            self.thread_num = 1
         self.dataset.set_thread_num(self.thread_num)
         if self.queue_num is None:
             self.queue_num = self.thread_num
@@ -545,6 +547,20 @@ class QueueDataset(DatasetBase):
         super(QueueDataset, self).__init__()
         self.proto_desc.name = "MultiSlotDataFeed"
 
+    def _prepare_to_run(self):
+        """
+        Set data_feed_desc/thread num/filelist before run,
+        user no need to call this function.
+        """
+        if self.thread_num > len(self.filelist):
+            self.thread_num = len(self.filelist)
+        if self.thread_num == 0:
+            self.thread_num = 1
+        self.dataset.set_thread_num(self.thread_num)
+        self.dataset.set_filelist(self.filelist)
+        self.dataset.set_data_feed_desc(self.desc())
+        self.dataset.create_readers()
+
     def local_shuffle(self):
         """
         Local shuffle data.
diff --git a/python/paddle/fluid/incubate/fleet/base/fleet_base.py b/python/paddle/fluid/incubate/fleet/base/fleet_base.py
index a52970fad1220b150fd56b365358cdab9a8ae199..ac9b0f232761b66b3a74a938ceadb9adc2ee8e31 100644
--- a/python/paddle/fluid/incubate/fleet/base/fleet_base.py
+++ b/python/paddle/fluid/incubate/fleet/base/fleet_base.py
@@ -148,8 +148,10 @@ class Fleet(object):
     def split_files(self, files):
         """
         split files before distributed training,
-        for example, files is [a, b, c ,d, e]  and trainer_num = 2,
-        then trainer 0 gets [a, b, c] and trainer 1 gets [d, e]
+        example 1: files is [a, b, c ,d, e]  and trainer_num = 2, then trainer
+                   0 gets [a, b, c] and trainer 1 gets [d, e].
+        example 2: files is [a, b], and trainer_num = 3, then trainer 0 gets
+                   [a], trainer 1 gets [b],  trainer 2 gets []
 
         Args:
             files(list): file list need to be read.
@@ -160,9 +162,6 @@ class Fleet(object):
         trainer_id = self.worker_index()
         trainers = self.worker_num()
 
-        if len(files) < trainers:
-            raise ValueError("file number must gather or equal trainer number")
-
         remainder = len(files) % trainers
         blocksize = len(files) / trainers