Merge pull request #170 from ShenYuhan/release/v1.2

add windows fake fcntl dependency

paddlehub/common/lock.py

-import fcntl
 import os
+if os.name == "posix":
+    import fcntl
 
 
 class WinLock(object):
@@ -15,23 +16,22 @@ class Lock(object):
     _owner = None
 
     def __init__(self):
-        self.LOCK_EX = fcntl.LOCK_EX
-        self.LOCK_UN = fcntl.LOCK_UN
-        self.LOCK_TE = ""
         if os.name == "posix":
             self.lock = fcntl
         else:
             self.lock = WinLock()
         _lock = self.lock
+        self.LOCK_EX = self.lock.LOCK_EX
+        self.LOCK_UN = self.lock.LOCK_UN
 
     def get_lock(self):
         return self.lock
 
     def flock(self, fp, cmd):
-        if cmd == fcntl.LOCK_UN:
+        if cmd == self.lock.LOCK_UN:
             Lock._owner = None
             self.lock.flock(fp, cmd)
-        elif cmd == fcntl.LOCK_EX:
+        elif cmd == self.lock.LOCK_EX:
             if Lock._owner is None:
                 Lock._owner = os.getpid()
                 self.lock.flock(fp, cmd)

tutorial/autofinetune.md

@@ -64,7 +64,7 @@ finetunee.py用于接受PaddleHub搜索到的超参进行一次优化过程，
  ```python
  print("AutoFinetuneEval"+"\t" + str(eval_acc))
  ```
- 
+
 * 输出的评价效果取值范围应该为`(-∞, 1]`，取值越高，表示效果越好。
 
 ### 示例
@@ -132,7 +132,7 @@ $ hub autofinetune finetunee.py --param_file=hparam.yaml --cuda=['1','2'] --pops
 * round0 ~ roundn记录了每一轮的数据，在每个round目录下，还存在以下文件：
 
   * log-0.info ~ log-m.info记录了每个搜索方向的日志
-  
+
   * model-0 ~ model-m记录了对应搜索的参数
 
 ## 五、可视化