fix runtime error

test=develop

paddle/fluid/framework/fleet/fleet_wrapper.cc

@@ -237,6 +237,7 @@ void FleetWrapper::PushDenseParamSync(
   std::vector<paddle::ps::Region> regions;
   for (auto& t : var_names) {
     Variable* var = scope.FindVar(t);
+    CHECK(var != nullptr) << "var[" << t << "] not found";
     LoDTensor* tensor = var->GetMutable<LoDTensor>();
     float* g = tensor->mutable_data<float>(place);
     paddle::ps::Region reg(g, tensor->numel());

paddle/fluid/framework/io/shell.cc

@@ -126,7 +126,7 @@ static int shell_popen_fork_internal(const char* real_cmd, bool do_read,
   }
 
   close_open_fds_internal();
-  if (execl("/bin/sh", "sh", "-c", real_cmd, NULL) < 0) {
+  if (execl("/bin/bash", "bash", "-c", real_cmd, NULL) < 0) {
     return -1;
   }
   exit(127);

python/paddle/fluid/executor.py

@@ -712,7 +712,7 @@ class Executor(object):
         if dataset == None:
             raise RuntimeError("dataset is needed and should be initialized")
 
-        if self.place == paddle.fluid.CUDAPlace():
+        if not isinstance(self.place, core.CPUPlace):
             raise RuntimeError("infer_from_dataset is verified on CPUPlace"
                                "We will open CUDAPlace in the future")
 

python/paddle/fluid/incubate/fleet/parameter_server/__init__.py

@@ -123,18 +123,23 @@ class Fleet(object):
             print("You should run DistributedOptimizer.minimize() first")
             sys.exit(-1)
 
-    def init_worker(self, programs):
+    def init_worker(self, programs, scopes=None):
         """
         init_worker(): will be called by user. When a user knows current process is_server(), he/she
                     should call init_worker() to initialize global information about worker and connect
-                    worker with pserver.
+                    worker with pserver. You should run startup program before init_worker.
 
         Args:
             programs(Program|list): a Program or a list of Programs
-
+            scopes(Scope|list): a Scope or  a list of Scopes, default None.
         """
         if not isinstance(programs, list):
             programs = [programs]
+        if scopes is None:
+            scopes = [fluid.global_scope()] * len(programs)
+        if len(scopes) != len(programs):
+            print("You should make sure len(scopes) == len(programs) or set scopes None")
+            sys.exit(-1)
         if self._opt_info:
             if "fleet_desc" in self._opt_info:
                 self._dist_desc_str = text_format.MessageToString(
@@ -160,7 +165,7 @@ class Fleet(object):
             self.role_maker_._barrier_worker()
             if self.role_maker_._is_first_worker():
                 tables = self._dist_desc.trainer_param.dense_table
-                for prog in programs:
+                for prog, scope in zip(programs, scopes):
                     prog_id = str(id(prog))
                     prog_conf = self._opt_info['program_configs'][prog_id]
                     prog_tables = {}
@@ -174,8 +179,13 @@ class Fleet(object):
                             continue
                         var_name_list = []
                         for i in range(0, len(table.dense_variable_name)):
-                            var_name_list.append(table.dense_variable_name[i])
-                    self._fleet_ptr.init_model(prog.desc,
+                            var_name = table.dense_variable_name[i]
+                            if scope.find_var(var_name) is None:
+                                print("var " + var_name + " not found in scope, "
+                                      "you should run startup program first")
+                                sys.exit(-1)
+                            var_name_list.append(var_name)
+                    self._fleet_ptr.init_model(scope,
                                                int(table.table_id),
                                                var_name_list)
             # barrier for init model done

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

@@ -107,10 +107,12 @@ class TestDataset(unittest.TestCase):
         exe = fluid.Executor(fluid.CPUPlace())
         exe.run(fluid.default_startup_program())
         for i in range(2):
-            try:
+            #try:
             exe.train_from_dataset(fluid.default_main_program(), dataset)
-            except:
-                self.assertTrue(False)
+            #except ImportError as e:
+            #    pass
+            #except Exception as e:
+            #    self.assertTrue(False)
 
         os.remove("./test_in_memory_dataset_run_a.txt")
         os.remove("./test_in_memory_dataset_run_b.txt")
@@ -149,10 +151,12 @@ class TestDataset(unittest.TestCase):
         exe = fluid.Executor(fluid.CPUPlace())
         exe.run(fluid.default_startup_program())
         for i in range(2):
-            try:
+            #try:
             exe.train_from_dataset(fluid.default_main_program(), dataset)
-            except:
-                self.assertTrue(False)
+            #except ImportError as e:
+            #    pass
+            #except Exception as e:
+            #    self.assertTrue(False)
 
         os.remove("./test_queue_dataset_run_a.txt")
         os.remove("./test_queue_dataset_run_b.txt")

python/paddle/fluid/trainer_desc.py

@@ -23,7 +23,7 @@ class TrainerDesc(object):
         with open(proto_file, 'r') as f:
             text_format.Parse(f.read(), self.proto_desc)
         '''
-        from proto import trainer_desc_pb2
+        from .proto import trainer_desc_pb2
         self.proto_desc = trainer_desc_pb2.TrainerDesc()
         import multiprocessing as mp
         # set default thread num == cpu count

python/paddle/fluid/trainer_factory.py

@@ -12,6 +12,9 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+from .trainer_desc import MultiTrainer, DistMultiTrainer
+from .device_worker import Hogwild, DownpourSGD
+
 __all__ = ["TrainerFactory"]
 
 
@@ -20,8 +23,6 @@ class TrainerFactory(object):
         pass
 
     def _create_trainer(self, opt_info=None):
-        from .trainer_desc import MultiTrainer, DistMultiTrainer
-        from .device_worker import Hogwild, DownpourSGD
         trainer = None
         device_worker = None
         if opt_info == None: