[fleet_executor] handle empty addr for single card train

paddle/fluid/distributed/fleet_executor/fleet_executor.cc

@@ -43,24 +43,30 @@ void FleetExecutor::InitMessageBus() {
   std::unordered_map<int64_t, std::string> rank_to_addr;
   std::string addr;
   for (const auto& rank_info : exe_desc_.cluster_info()) {
+    // init the dns map
     int64_t rank = rank_info.rank();
     std::string ip_port = rank_info.ip_port();
     ss << rank << "\t->\t" << ip_port << "\n";
-    // TODO(Yuang): replace the first 'rank' with real interceptor id
+    // TODO(Yuang): init interceptor_id_to_rank out of this loop
     interceptor_id_to_rank.insert(std::make_pair(rank, rank));
     rank_to_addr.insert(std::make_pair(rank, ip_port));
     if (rank == cur_rank) {
       addr = ip_port;
     }
   }
-  PADDLE_ENFORCE_NE(
-      addr, "",
-      platform::errors::NotFound(
-          "Current rank is %s, which ip_port cannot be found in the config.",
-          cur_rank));
-  VLOG(3) << "Current rank is " << cur_rank << " and the ip_port is " << addr
-          << ".";
-  VLOG(3) << "The number of ranks are " << interceptor_id_to_rank.size() << ".";
+  if (addr == "") {
+    PADDLE_ENFORCE_EQ(
+        rank_to_addr.size(), 0,
+        platform::errors::NotFound("Empty address is not valid for "
+                                   "paddle.distributed.launch method."));
+    PADDLE_ENFORCE_EQ(
+        cur_rank, 0,
+        platform::errors::NotFound("Address is empty but cur rank is not 0."));
+  }
+  VLOG(3) << "Current rank is " << cur_rank << " and the ip_port is "
+          << (addr == "" ? "empty" : addr) << ".";
+  VLOG(3) << "The number of ranks are "
+          << (rank_to_addr.size() == 0 ? 1 : rank_to_addr.size()) << ".";
   VLOG(5) << ss.str();
   MessageBus& message_bus_instance = MessageBus::Instance();
   if (!message_bus_instance.IsInit()) {

paddle/fluid/distributed/fleet_executor/message_bus.cc

@@ -89,6 +89,10 @@ bool MessageBus::Send(const InterceptorMessage& interceptor_message) {
 }
 
 void MessageBus::ListenPort() {
+  if (addr_ == "") {
+    VLOG(3) << "No need listen to port since training on single card.";
+    return;
+  }
 #if defined(PADDLE_WITH_DISTRIBUTE) && defined(PADDLE_WITH_PSCORE) && \
     !defined(PADDLE_WITH_ASCEND_CL)
   // function keep listen the port and handle the message
@@ -125,6 +129,10 @@ bool MessageBus::IsSameRank(int64_t src_id, int64_t dst_id) {
       dst_rank, interceptor_id_to_rank_.end(),
       platform::errors::NotFound(
           "Cannot find rank for dst interceptor id %lld. Init error.", dst_id));
+  if (addr_ == "") {
+    // single card training, must be same rank
+    return true;
+  }
   const auto& src_ip = rank_to_addr_.find(src_rank->second);
   PADDLE_ENFORCE_NE(src_ip, rank_to_addr_.end(),
                     platform::errors::NotFound(

python/paddle/fluid/tests/unittests/CMakeLists.txt

@@ -141,6 +141,7 @@ if(((NOT WITH_ROCM) AND (NOT WITH_GPU)) OR WIN32)
     LIST(REMOVE_ITEM TEST_OPS test_fleet_gradient_scale)
     LIST(REMOVE_ITEM TEST_OPS test_disable_signal_handler)
     LIST(REMOVE_ITEM TEST_OPS test_fleet_executor)
+    LIST(REMOVE_ITEM TEST_OPS test_fleet_executor_multi_devices)
 endif()
 
 # Temporally disable test_deprecated_decorator

python/paddle/fluid/tests/unittests/test_fleet_executor.py

@@ -13,7 +13,6 @@
 # limitations under the License.
 
 import unittest
-import os
 import paddle
 import paddle.fluid as fluid
 
@@ -32,17 +31,7 @@ def run_fleet_executor(self, place):
         }
         exe.run(empty_program, feed={'x': [1]})
 
-    def test_executor_on_multi_devices(self):
-        places = [fluid.CPUPlace()]
-        if fluid.is_compiled_with_cuda():
-            places.append(fluid.CUDAPlace(0))
-        for place in places:
-            self.run_fleet_executor(place)
-
-    def test_dist_executor_on_multi_devices(self):
-        os.environ["PADDLE_TRAINER_ID"] = "0"
-        os.environ[
-            "PADDLE_TRAINER_ENDPOINTS"] = "127.0.0.1:7000,127.0.0.1:7001,127.0.0.1:7002"
+    def test_executor_on_single_device(self):
         places = [fluid.CPUPlace()]
         if fluid.is_compiled_with_cuda():
             places.append(fluid.CUDAPlace(0))

python/paddle/fluid/tests/unittests/test_fleet_executor_multi_devices.py

@@ -0,0 +1,47 @@
+# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import unittest
+import os
+import paddle
+import paddle.fluid as fluid
+
+paddle.enable_static()
+
+
+class TestFleetExecutor(unittest.TestCase):
+    def run_fleet_executor(self, place):
+        exe = paddle.static.Executor(place)
+        empty_program = paddle.static.Program()
+        with fluid.program_guard(empty_program, empty_program):
+            x = fluid.layers.data(name='x', shape=[1], dtype=paddle.float32)
+        empty_program._pipeline_opt = {
+            "fleet_opt": True,
+            "section_program": empty_program
+        }
+        exe.run(empty_program, feed={'x': [1]})
+
+    def test_dist_executor_on_multi_devices(self):
+        os.environ["PADDLE_TRAINER_ID"] = "0"
+        os.environ[
+            "PADDLE_TRAINER_ENDPOINTS"] = "127.0.0.1:7000,127.0.0.1:7001,127.0.0.1:7002"
+        places = [fluid.CPUPlace()]
+        if fluid.is_compiled_with_cuda():
+            places.append(fluid.CUDAPlace(0))
+        for place in places:
+            self.run_fleet_executor(place)
+
+
+if __name__ == "__main__":
+    unittest.main()