remove some comments

paddle/fluid/API.spec

@@ -37,14 +37,14 @@ paddle.fluid.DataFeedDesc.desc ArgSpec(args=['self'], varargs=None, keywords=Non
 paddle.fluid.DataFeedDesc.set_batch_size ArgSpec(args=['self', 'batch_size'], varargs=None, keywords=None, defaults=None)
 paddle.fluid.DataFeedDesc.set_dense_slots ArgSpec(args=['self', 'dense_slots_name'], varargs=None, keywords=None, defaults=None)
 paddle.fluid.DataFeedDesc.set_use_slots ArgSpec(args=['self', 'use_slots_name'], varargs=None, keywords=None, defaults=None)
-paddle.fluid.AsyncExecutor.__init__ ArgSpec(args=['self', 'place'], varargs=None, keywords=None, defaults=(None,))
+paddle.fluid.AsyncExecutor.__init__ ArgSpec(args=['self', 'place', 'run_mode'], varargs=None, keywords=None, defaults=(None, ''))
 paddle.fluid.AsyncExecutor.config_distributed_nodes ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
 paddle.fluid.AsyncExecutor.download_data ArgSpec(args=['self', 'afs_path', 'local_path', 'fs_default_name', 'ugi', 'file_cnt', 'hadoop_home', 'process_num'], varargs=None, keywords=None, defaults=('$HADOOP_HOME', 12))
 paddle.fluid.AsyncExecutor.get_instance ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
 paddle.fluid.AsyncExecutor.init_model ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
 paddle.fluid.AsyncExecutor.init_server ArgSpec(args=['self', 'dist_desc'], varargs=None, keywords=None, defaults=None)
 paddle.fluid.AsyncExecutor.init_worker ArgSpec(args=['self', 'dist_desc', 'startup_program'], varargs=None, keywords=None, defaults=None)
-paddle.fluid.AsyncExecutor.run ArgSpec(args=['self', 'program', 'data_feed', 'filelist', 'thread_num', 'fetch', 'debug'], varargs=None, keywords=None, defaults=(False,))
+paddle.fluid.AsyncExecutor.run ArgSpec(args=['self', 'program', 'data_feed', 'filelist', 'thread_num', 'fetch', 'mode', 'debug'], varargs=None, keywords=None, defaults=('', False))
 paddle.fluid.AsyncExecutor.save_model ArgSpec(args=['self', 'save_path'], varargs=None, keywords=None, defaults=None)
 paddle.fluid.AsyncExecutor.stop ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
 paddle.fluid.io.save_vars ArgSpec(args=['executor', 'dirname', 'main_program', 'vars', 'predicate', 'filename'], varargs=None, keywords=None, defaults=(None, None, None, None))

python/paddle/fluid/distributed/helper.py

@@ -28,7 +28,7 @@ class FileSystem(object):
 
     def __init__(self,
                  fs_type="afs",
-                 uri="afs://tianqi.afs.baidu.com:9902",
+                 uri="afs://xx",
                  user=None,
                  passwd=None,
                  hadoop_bin=""):
@@ -37,10 +37,6 @@ class FileSystem(object):
         assert hadoop_bin != None
         import ps_pb2 as pslib
         self.fs_client = pslib.FsClientParameter()
-        #if fs_type == "afs":
-        #    fs_client.fs_type = pslib.FsApiType.AFS
-        #else:
-        #    fs_client.fs_type = pslib.FsApiType.HDFS
         self.fs_client.uri = uri
         self.fs_client.user = user
         self.fs_client.passwd = passwd

python/paddle/fluid/distributed/node.py

@@ -75,8 +75,6 @@ class DownpourServer(Server):
         table.accessor.embedx_dim = 8
         table.accessor.embedx_threshold = 5
         table.accessor.fea_dim = 11
-        #table.accessor.fea_dim = abs(reduce(lambda x, y: x * y, 
-        #                                    slot_value_var[0].shape, 1))
         table.accessor.downpour_accessor_param.nonclk_coeff = 0.1
         table.accessor.downpour_accessor_param.click_coeff = 2
         table.accessor.downpour_accessor_param.base_threshold = 0.2
@@ -134,8 +132,6 @@ class DownpourWorker(Worker):
     def __init__(self, window):
         self.window = window
         self.worker_ = pslib.DownpourTrainerParameter()
-        #self.worker_.pull_dense_per_batch = window
-        #self.worker_.push_dense_per_batch = window
 
     def add_sparse_table(self, table_id, learning_rate, slot_key_vars,
                          slot_value_vars):

python/paddle/fluid/distributed/ps_instance.py

@@ -59,9 +59,6 @@ class PaddlePSInstance(object):
         else:
             self._node_type = -1
 
-        #if self._rankid == 0:
-        #print "node type: ", self._node_type
-
     def _split_comm(self):
         if self.is_server():
             self._comm = self.dh.comm.Split(self._node_type)