[cherry-pick 2.2 heterps]bug fix for launch_utils.py (#37521) (#37570)

* fix. test=develop

* fix. test=develop

* fix. test=develop

* fix. test=develop

* fix. test=develop

* [heterps]bug fix for _run_from_dataset

* fix heter_server.cc

* fix launch_utils.py

* fix heter_section_worker.cc

* fix. test=develop

* fix. test=develop

paddle/fluid/distributed/service/heter_server.cc

@@ -43,11 +43,11 @@ void HeterServer::StartHeterService() {
 
   {
     std::lock_guard<std::mutex> lock(this->mutex_ready_);
+    stoped_ = false;
     ready_ = 1;
   }
   condition_ready_.notify_all();
   std::unique_lock<std::mutex> running_lock(mutex_);
-  stoped_ = false;
   cv_.wait(running_lock, [&] {
     VLOG(1) << "Heter Server is Stop? " << stoped_;
     return stoped_;

paddle/fluid/framework/heter_section_worker.cc

@@ -350,7 +350,7 @@ void HeterSectionWorker::BatchPostProcess() {
     DumpParam(*((*microbatch_scopes_)[0]), batch_num_);
   }
   // print each op time
-  if (thread_id_ == 0) {
+  if (debug_ && thread_id_ == 0) {
     size_t total_ops_size = forward_ops_.size() + backward_ops_.size();
     if (batch_num_ > 0 && batch_num_ % 100 == 0) {
       for (size_t i = 0; i < total_ops_size; ++i) {

python/paddle/distributed/fleet/launch_utils.py

@@ -979,8 +979,6 @@ class ParameterServerLauncher(object):
                 heter_worker_endpoints_list = args.heter_workers.split(";")
                 self.heter_worker_endpoints = ""
                 for i in range(len(heter_worker_endpoints_list)):
-                    if self.heter_worker_endpoints != "":
-                        self.heter_worker_endpoints += ","
                     heter_worker_endpoints = heter_worker_endpoints_list[
                         i].split(",")
                     self.stage_heter_trainer_num.append(
@@ -1073,15 +1071,18 @@ class ParameterServerLauncher(object):
                 _, self.current_node_ip = get_host_name_ip()
             else:
                 self.current_node_ip = pod_ip
-            assert self.current_node_ip in self.node_ips, "Can't find your local ip {%s} in args.servers and args.workers ips: {%s}" \
-                % (self.current_node_ip, self.node_ips)
-        self.node_rank = self.node_ips.index(self.current_node_ip)
-
-        logger.debug(
-            "parsed from args: node_ips:{} current_node_ip:{} node_rank:{}".
-            format(self.node_ips, self.current_node_ip, self.node_rank))
+            if not self.distribute_mode == DistributeMode.PS_HETER:
+                assert self.current_node_ip in self.node_ips, "Can't find your local ip {%s} in args.servers and args.workers ips: {%s}" \
+                      % (self.current_node_ip, self.node_ips)
+        if self.current_node_ip in self.node_ips:
+            self.node_rank = self.node_ips.index(self.current_node_ip)
+            logger.debug(
+                "parsed from args: node_ips:{} current_node_ip:{} node_rank:{}".
+                format(self.node_ips, self.current_node_ip, self.node_rank))
 
     def start_ps(self):
+        if not self.current_node_ip in self.node_ips:
+            return
         cluster = Cluster(hdfs=None)
         server_rank = 0
         worker_rank = 0

python/paddle/fluid/executor.py

@@ -1673,12 +1673,8 @@ class Executor(object):
                 for var in program.global_block().vars.values():
                     if var.is_data:
                         data_vars.append(var)
-                if core.is_compiled_with_npu():
-                    dataset = paddle.fluid.DatasetFactory().create_dataset(
-                        'InMemoryDataset')
-                else:
-                    dataset = paddle.fluid.DatasetFactory().create_dataset(
-                        'FileInstantDataset')
+                dataset = paddle.fluid.DatasetFactory().create_dataset(
+                    'InMemoryDataset')
                 dataset.set_batch_size(1)
                 dataset.set_thread(1)
                 dataset.set_filelist(['None'])