fix ut merge error

Author: yi.wu

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

@@ -21,7 +21,7 @@
 import six
 import signal
 import subprocess
-import six
+import argparse
 
 
 class TestDistRunnerBase(object):
@@ -30,7 +30,7 @@ def get_model(self, batch_size=2):
             "get_model should be implemented by child classes.")
 
     def get_transpiler(self, trainer_id, main_program, pserver_endpoints,
-                       trainers):
+                       trainers, sync_mode):
         # NOTE: import fluid until runtime, or else forking processes will cause error.
         import paddle
         import paddle.fluid as fluid
@@ -39,33 +39,35 @@ def get_transpiler(self, trainer_id, main_program, pserver_endpoints,
             trainer_id=trainer_id,
             program=main_program,
             pservers=pserver_endpoints,
-            trainers=trainers)
+            trainers=trainers,
+            sync_mode=sync_mode)
         return t
 
-    def run_pserver(self, pserver_endpoints, trainers, current_endpoint,
-                    trainer_id):
+    def run_pserver(self, args):
         import paddle
         import paddle.fluid as fluid
         self.get_model(batch_size=2)
-        t = self.get_transpiler(trainer_id,
-                                fluid.default_main_program(), pserver_endpoints,
-                                trainers)
-        pserver_prog = t.get_pserver_program(current_endpoint)
-        startup_prog = t.get_startup_program(current_endpoint, pserver_prog)
+        t = self.get_transpiler(args.trainer_id,
+                                fluid.default_main_program(), args.endpoints,
+                                args.trainers, args.sync_mode)
+        pserver_prog = t.get_pserver_program(args.current_endpoint)
+        startup_prog = t.get_startup_program(args.current_endpoint,
+                                             pserver_prog)
         place = fluid.CPUPlace()
         exe = fluid.Executor(place)
         exe.run(startup_prog)
         exe.run(pserver_prog)
 
-    def run_trainer(self, place, endpoints, trainer_id, trainers, is_dist=True):
+    def run_trainer(self, place, args):
         import paddle
         import paddle.fluid as fluid
         test_program, avg_cost, train_reader, test_reader, batch_acc, predict = \
         self.get_model(batch_size=2)
-        if is_dist:
-            t = self.get_transpiler(trainer_id,
-                                    fluid.default_main_program(), endpoints,
-                                    trainers)
+        if args.is_dist:
+            t = self.get_transpiler(args.trainer_id,
+                                    fluid.default_main_program(),
+                                    args.endpoints, args.trainers,
+                                    args.sync_mode)
             trainer_prog = t.get_trainer_program()
         else:
             trainer_prog = fluid.default_main_program()
@@ -132,18 +134,21 @@ def runtime_main(test_class):
     args = parser.parse_args()
 
     model = test_class()
-    if role == "pserver":
-        model.run_pserver(endpoints, trainers, current_endpoint, trainer_id)
+    if args.role == "pserver":
+        model.run_pserver(args)
     else:
         p = fluid.CUDAPlace(0) if core.is_compiled_with_cuda(
         ) else fluid.CPUPlace()
-        model.run_trainer(p, endpoints, trainer_id, trainers, is_dist)
+        model.run_trainer(p, args)
 
 
 import paddle.compat as cpt
 
 
 class TestDistBase(unittest.TestCase):
+    def _setup_config(self):
+        raise NotImplementedError("tests should have _setup_config implemented")
+
     def setUp(self):
         self._trainers = 2
         self._pservers = 2
@@ -221,9 +226,7 @@ def check_with_place(self, model_file, delta=1e-3, check_error_log=False):
         # Run local to get a base line
         env_local = {"CUDA_VISIBLE_DEVICES": "0"}
         env_local.update(required_envs)
-        local_cmd = "%s %s trainer %s 0 %s %d FLASE" % \
-            (self._python_interp, model_file,
-             "127.0.0.1:1234", "127.0.0.1:1234", 1)
+        local_cmd = "%s %s --role trainer" % (self._python_interp, model_file)
         if not check_error_log:
             local_proc = subprocess.Popen(
                 local_cmd.split(" "),