                         kernel_size=self._kernel_size,
                         padding=self._padding,
                         name="{}_conv2d_0".format(self._name),
                         **self._kwargs)(var_x)
          var_x = LeakyReLU(alpha=0.2, name="{}_leakyrelu_1".format(self._name))(var_x)
          if self._use_reflect_padding:
              var_x = ReflectionPadding2D(stride=1,
                                          kernel_size=self._kernel_size,
                                          name="{}_reflectionpadding2d_1".format(self._name))(var_x)
  
 
</s> remove                        name="{}_conv2d_0".format(self._name),
 </s> add                        name=f"{self._name}_conv2d_0", </s> remove                                         name="{}_reflectionpadding2d_0".format(self._name))(var_x)
 </s> add                                         name=f"{self._name}_reflectionpadding2d_0")(var_x) </s> remove                                         name="{}_reflectionpadding2d_1".format(self._name))(var_x)
 </s> add                                         name=f"{self._name}_reflectionpadding2d_1")(var_x) </s> remove                        name="{}_conv2d_1".format(self._name),
 </s> add                        name=f"{self._name}_conv2d_1", </s> remove                                   name="{}_upsampling2D".format(self._name))(var_x2)
 </s> add                                   name=f"{self._name}_upsampling2D")(var_x2)
        var_x = LeakyReLU(alpha=0.2, name=f"{self._name}_leakyrelu_1")(var_x)
                         kernel_size=self._kernel_size,
                         padding=self._padding,
                         name="{}_conv2d_0".format(self._name),
                         **self._kwargs)(var_x)
        var_x = LeakyReLU(alpha=0.2, name=f"{self._name}_leakyrelu_1")(var_x)
          if self._use_reflect_padding:
              var_x = ReflectionPadding2D(stride=1,
                                          kernel_size=self._kernel_size,
                                          name="{}_reflectionpadding2d_1".format(self._name))(var_x)
  
keep keep keep keep replace keep keep keep keep keep
 Update all Keras Imports to be conditional (#1214)

* Remove custom keras importer

* first round keras imports fix

* launcher.py: Remove KerasFinder references

* 2nd round keras imports update (lib and extract)

* 3rd round keras imports update (train)

* remove KerasFinder from tests

* 4th round keras imports update (tests) 
lib/model/nn_blocks.py