From 79ba19ce7a48c443bb0f34077772536d6f47787c Mon Sep 17 00:00:00 2001
From: Dong Daxiang <35550832+guru4elephant@users.noreply.github.com>
Date: Tue, 30 Jul 2019 08:15:45 +0800
Subject: [PATCH] Update fleet_api_howto_cn.rst

test=document_preview
---
 .../howto/training/fleet_api_howto_cn.rst     | 24 -------------------
 1 file changed, 24 deletions(-)

diff --git a/doc/fluid/user_guides/howto/training/fleet_api_howto_cn.rst b/doc/fluid/user_guides/howto/training/fleet_api_howto_cn.rst
index a92d9f1ab..5ceef7b11 100644
--- a/doc/fluid/user_guides/howto/training/fleet_api_howto_cn.rst
+++ b/doc/fluid/user_guides/howto/training/fleet_api_howto_cn.rst
@@ -144,27 +144,10 @@ training通常在GPU多机多卡训练中使用，一般在复杂模型的训练
       print("worker_index: %d, step%d cost = %f" %
            (fleet.worker_index(), i, cost_val[0]))
 
-更多使用示例
-------------
-
-`点击率预估 <>`__
-
-`语义匹配 <>`__
-
-`向量学习 <>`__
-
-`基于Resnet50的图像分类 <>`__
-
-`基于Transformer的机器翻译 <>`__
-
-`基于Bert的语义表示学习 <>`__
 
 Fleet API相关的接口说明
 -----------------------
 
-Fleet API接口
-~~~~~~~~~~~~~
-
 -  init(role\_maker=None)
 -  fleet初始化，需要在使用fleet其他接口前先调用，用于定义多机的环境配置
 -  is\_worker()
@@ -186,8 +169,6 @@ Fleet API接口
 -  distributed\_optimizer(optimizer, strategy=None)
 -  分布式优化算法装饰器，用户可带入单机optimizer，并配置分布式训练策略，返回一个分布式的optimizer
 
-RoleMaker
-~~~~~~~~~
 
 -  MPISymetricRoleMaker
 
@@ -264,17 +245,12 @@ RoleMaker
                    server_endpoints=pserver_endpoints)
        fleet.init(role)
 
-Strategy
-~~~~~~~~
-
 -  Parameter Server Training
 -  Sync\_mode
 -  Collective Training
 -  LocalSGD
 -  ReduceGrad
 
-Fleet Mode
-~~~~~~~~~~
 
 -  Parameter Server Training
 
-- 
GitLab