fix calling swig_api before import

python/paddle/v2/optimizer.py

+import py_paddle.swig_paddle as swig_api
 import paddle.trainer_config_helpers.config_parser_utils as config_parser_utils
 import paddle.trainer_config_helpers.optimizers as v1_optimizers
 """
@@ -16,7 +17,6 @@ __all__ = [
 
 class Optimizer(object):
     def __init__(self, **kwargs):
-        import py_paddle.swig_paddle as swig_api
         if 'batch_size' in kwargs:
             del kwargs['batch_size']  # not important for python library.
 
@@ -35,7 +35,6 @@ class Optimizer(object):
         For each optimizer(SGD, Adam), GradientMachine should enable different
         buffers.
         """
-        import py_paddle.swig_paddle as swig_api
         tmp = swig_api.ParameterOptimizer.create(self.__opt_conf__)
         assert isinstance(tmp, swig_api.ParameterOptimizer)
         return tmp.getParameterTypes()