Polish code

test=develop

paddle/fluid/imperative/tracer.h

@@ -56,10 +56,6 @@ class Tracer {
   std::vector<VarBase*> PyTrace(OpBase* op, const std::vector<VarBase*>& inputs,
                                 bool stop_gradient = false);
 
-  static void StartProfile();
-
-  static void StopProfile();
-
  private:
   platform::Place GetPlace(const VarBasePtrMap& inputs);
 

python/paddle/fluid/framework.py

@@ -290,7 +290,6 @@ class Variable(object):
                                                 dtype='float32')
     """
 
-    #  @profile
     def __init__(self,
                  block,
                  type=core.VarDesc.VarType.LOD_TENSOR,
@@ -646,7 +645,6 @@ class Operator(object):
         'checkpoint_notify', 'gen_nccl_id'
     }
 
-    #  @profile
     def __init__(self,
                  block,
                  desc,
@@ -1241,7 +1239,6 @@ class Block(object):
         return (item[1] for item in six.iteritems(self.vars)
                 if isinstance(item[1], Parameter))
 
-    #  @profile
     def create_var(self, *args, **kwargs):
         var = Variable(block=self, *args, **kwargs)
         if 'initializer' in kwargs:
@@ -1350,7 +1347,6 @@ class Block(object):
                 initializer(param, self)
         return param
 
-    #  @profile
     def append_op(self, *args, **kwargs):
         """
         Appends a new Operator according to the giving arguments.

python/paddle/fluid/imperative/nn.py

@@ -97,7 +97,6 @@ class Conv2D(layers.Layer):
             dtype=self._dtype,
             is_bias=True)
 
-    #  @profile
     def forward(self, input):
         pre_bias = self._helper.create_variable_for_type_inference(
             dtype=self._dtype)
@@ -170,7 +169,6 @@ class Pool2D(layers.Layer):
         self._exclusive = exclusive
         self._l_type = 'pool2d'
 
-    #  @profile
     def forward(self, input):
         pool_out = self._helper.create_variable_for_type_inference(self._dtype)
 
@@ -231,7 +229,6 @@ class FC(layers.Layer):
         else:
             self._b = None
 
-    #  @profile
     def forward(self, input):
         tmp = self._helper.create_variable_for_type_inference(self._dtype)
         self._helper.append_op(