adjusted target code files

src/test/resources/target_code/CNNCreator_Alexnet.py

@@ -4,7 +4,6 @@ import os
 
 from CNNNet_Alexnet import Net_0
 
-
 class CNNCreator_Alexnet:
     _model_dir_ = "model/Alexnet/"
     _model_prefix_ = "model"
@@ -52,8 +51,8 @@ class CNNCreator_Alexnet:
         self.networks[0] = Net_0(data_mean=data_mean, data_std=data_std)
         self.networks[0].collect_params().initialize(self.weight_initializer, ctx=context)
         self.networks[0].hybridize()
-        self.networks[0](mx.nd.zeros((1,3,224,224,), ctx=context))
-
+        self.networks[0](
+        mx.nd.zeros((1,3,224,224,), ctx=context) )
 
         if not os.path.exists(self._model_dir_):
             os.makedirs(self._model_dir_)

src/test/resources/target_code/CNNCreator_CifarClassifierNetwork.py

@@ -4,7 +4,6 @@ import os
 
 from CNNNet_CifarClassifierNetwork import Net_0
 
-
 class CNNCreator_CifarClassifierNetwork:
     _model_dir_ = "model/CifarClassifierNetwork/"
     _model_prefix_ = "model"
@@ -52,8 +51,8 @@ class CNNCreator_CifarClassifierNetwork:
         self.networks[0] = Net_0(data_mean=data_mean, data_std=data_std)
         self.networks[0].collect_params().initialize(self.weight_initializer, ctx=context)
         self.networks[0].hybridize()
-        self.networks[0](mx.nd.zeros((1,3,32,32,), ctx=context))
-
+        self.networks[0](
+        mx.nd.zeros((1,3,32,32,), ctx=context) )
 
         if not os.path.exists(self._model_dir_):
             os.makedirs(self._model_dir_)

src/test/resources/target_code/CNNCreator_VGG16.py

@@ -4,7 +4,6 @@ import os
 
 from CNNNet_VGG16 import Net_0
 
-
 class CNNCreator_VGG16:
     _model_dir_ = "model/VGG16/"
     _model_prefix_ = "model"
@@ -52,8 +51,8 @@ class CNNCreator_VGG16:
         self.networks[0] = Net_0(data_mean=data_mean, data_std=data_std)
         self.networks[0].collect_params().initialize(self.weight_initializer, ctx=context)
         self.networks[0].hybridize()
-        self.networks[0](mx.nd.zeros((1,3,224,224,), ctx=context))
-
+        self.networks[0](
+        mx.nd.zeros((1,3,224,224,), ctx=context) )
 
         if not os.path.exists(self._model_dir_):
             os.makedirs(self._model_dir_)

src/test/resources/target_code/ddpg/reinforcement_learning/CNNCreator_CriticNetwork.py

 import mxnet as mx
 import logging
 import os
+
 from CNNNet_CriticNetwork import Net_0
 
 class CNNCreator_CriticNetwork:
@@ -50,7 +51,9 @@ class CNNCreator_CriticNetwork:
         self.networks[0] = Net_0(data_mean=data_mean, data_std=data_std)
         self.networks[0].collect_params().initialize(self.weight_initializer, ctx=context)
         self.networks[0].hybridize()
-        self.networks[0](mx.nd.zeros((1,8,), ctx=context), mx.nd.zeros((1,3,), ctx=context))
+        self.networks[0](
+        mx.nd.zeros((1,8,), ctx=context) , 
+        mx.nd.zeros((1,3,), ctx=context) )
 
         if not os.path.exists(self._model_dir_):
             os.makedirs(self._model_dir_)

src/test/resources/target_code/ros-ddpg/reinforcement_learning/CNNCreator_RosCriticNetwork.py

 import mxnet as mx
 import logging
 import os
+
 from CNNNet_RosCriticNetwork import Net_0
 
 class CNNCreator_RosCriticNetwork:
@@ -50,7 +51,9 @@ class CNNCreator_RosCriticNetwork:
         self.networks[0] = Net_0(data_mean=data_mean, data_std=data_std)
         self.networks[0].collect_params().initialize(self.weight_initializer, ctx=context)
         self.networks[0].hybridize()
-        self.networks[0](mx.nd.zeros((1,8,), ctx=context), mx.nd.zeros((1,3,), ctx=context))
+        self.networks[0](
+        mx.nd.zeros((1,8,), ctx=context) , 
+        mx.nd.zeros((1,3,), ctx=context) )
 
         if not os.path.exists(self._model_dir_):
             os.makedirs(self._model_dir_)

src/test/resources/target_code/td3/reinforcement_learning/CNNCreator_CriticNetwork.py

 import mxnet as mx
 import logging
 import os
+
 from CNNNet_CriticNetwork import Net_0
 
 class CNNCreator_CriticNetwork:
@@ -50,7 +51,9 @@ class CNNCreator_CriticNetwork:
         self.networks[0] = Net_0(data_mean=data_mean, data_std=data_std)
         self.networks[0].collect_params().initialize(self.weight_initializer, ctx=context)
         self.networks[0].hybridize()
-        self.networks[0](mx.nd.zeros((1,8,), ctx=context), mx.nd.zeros((1,3,), ctx=context))
+        self.networks[0](
+        mx.nd.zeros((1,8,), ctx=context) , 
+        mx.nd.zeros((1,3,), ctx=context) )
 
         if not os.path.exists(self._model_dir_):
             os.makedirs(self._model_dir_)