diff --git a/paddle/fluid/framework/hogwild_worker.cc b/paddle/fluid/framework/hogwild_worker.cc
index 0c66622ed7b9a6a6e9fb5112001009c2b95e367a..f4660751b582a460f8079173a9bb859e26711344 100644
--- a/paddle/fluid/framework/hogwild_worker.cc
+++ b/paddle/fluid/framework/hogwild_worker.cc
@@ -216,6 +216,7 @@ void HogwildWorker::TrainFiles() {
   // how to accumulate fetched values here
   device_reader_->Start();
   int cur_batch;
+  int batch_cnt = 0;
   while ((cur_batch = device_reader_->Next()) > 0) {
     for (auto &op : ops_) {
       bool need_skip = false;
@@ -230,13 +231,26 @@ void HogwildWorker::TrainFiles() {
       }
     }
 
+    if (need_dump_field_) {
+      DumpField(*thread_scope_, dump_mode_, dump_interval_);
+    }
+    if (need_dump_param_ && thread_id_ == 0) {
+      DumpParam(*thread_scope_, batch_cnt);
+    }
+
     total_ins_num += cur_batch;
+    ++batch_cnt;
     PrintFetchVars();
     thread_scope_->DropKids();
   }
   timeline.Pause();
   VLOG(3) << "worker " << thread_id_ << " train cost " << timeline.ElapsedSec()
           << " seconds, ins_num: " << total_ins_num;
+
+  if (need_dump_field_ || need_dump_param_) {
+    writer_.Flush();
+  }
+
 #if defined PADDLE_WITH_PSCORE
   if (thread_barrier_) {
     paddle::distributed::Communicator::GetInstance()->BarrierTriggerDecrement();
diff --git a/paddle/fluid/framework/multi_trainer.cc b/paddle/fluid/framework/multi_trainer.cc
index c0ccc196348a5761ea4dedf1aab5ce8754eb74b5..2a022ea4bb9efc0cab5ad990a4f45584bb17dab0 100644
--- a/paddle/fluid/framework/multi_trainer.cc
+++ b/paddle/fluid/framework/multi_trainer.cc
@@ -214,7 +214,7 @@ void MultiTrainer::Finalize() {
   if (need_dump_field_ || need_dump_param_) {
     FinalizeDumpEnv();
   }
-#ifdef PADDLE_WITH_HETERPS
+
   for (size_t i = 0; i < need_merge_var_names_.size(); i++) {
     Variable* root_var = root_scope_->FindVar(need_merge_var_names_[i]);
     if (root_var == nullptr) {
@@ -222,7 +222,11 @@ void MultiTrainer::Finalize() {
     }
     LoDTensor* root_tensor = root_var->GetMutable<LoDTensor>();
 
+#ifdef PADDLE_WITH_HETERPS
     for (size_t j = 0; j < places_.size(); j++) {
+#else
+    for (int j = 1; j < thread_num_; j++) {
+#endif
       Scope* cur_thread_scope = workers_[j]->GetThreadScope();
       Variable* thread_var =
           cur_thread_scope->FindVar(need_merge_var_names_[i]);
@@ -246,8 +250,8 @@ void MultiTrainer::Finalize() {
       _ForEachDataType_(MergeCallback);
     }
   }
+#ifdef PADDLE_WITH_HETERPS
   MergeDenseParam();
-
 #endif
   root_scope_->DropKids();
 }
diff --git a/python/paddle/fluid/device_worker.py b/python/paddle/fluid/device_worker.py
index 7fed27ee45978a5b34d1235999875312c292fcd1..a246474e21e20677937ea539a603a5b9c43da950 100644
--- a/python/paddle/fluid/device_worker.py
+++ b/python/paddle/fluid/device_worker.py
@@ -91,7 +91,10 @@ class Hogwild(DeviceWorker):
         trainer_desc.device_worker_name = "HogwildWorker"
         if self._infer:
             # just ignore feed op for inference model
-            trainer_desc.hogwild_param.skip_ops.extend(["feed"])
+            trainer_desc.hogwild_param.skip_ops.extend([
+                "feed", "push_sparse", "push_sparse_v2", "push_dense",
+                "distributed_push_sparse", "send"
+            ])
 
         dense_table_set = set()
         program_id = str(id(self._program))