                                  strides=self._strides,
                                  padding="same",
                                  name="{}_seperableconv2d".format(self._name),
                                  **self._kwargs)(inputs)
          var_x = Activation("relu", name="{}_relu".format(self._name))(var_x)
          return var_x
  
  
  #  << UPSCALING >>
  
 
</s> remove                                 name="{}_seperableconv2d".format(self._name),
 </s> add                                 name=f"{self._name}_seperableconv2d", </s> remove             var_x = PReLU(name="{}_prelu".format(self._name))(var_x)
 </s> add             var_x = PReLU(name=f"{self._name}_prelu")(var_x) </s> remove                      name="{}_{}conv2d".format(self._name, "dw" if self._use_depthwise else ""),
 </s> add                      name=f"{self._name}_{'dw' if self._use_depthwise else ''}conv2d", </s> remove         var_x = PixelShuffler(name="{}_pixelshuffler".format(self._name),
 </s> add         var_x = PixelShuffler(name=f"{self._name}_pixelshuffler", </s> remove                        name="{}_conv2d".format(self._name),
 </s> add                        name=f"{self._name}_conv2d",
        var_x = Activation("relu", name=f"{self._name}_relu")(var_x)
                                  strides=self._strides,
                                  padding="same",
                                  name="{}_seperableconv2d".format(self._name),
                                  **self._kwargs)(inputs)
        var_x = Activation("relu", name=f"{self._name}_relu")(var_x)
          return var_x
  
  
  #  << UPSCALING >>
  
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