                              strides=(1, 1),
                              padding=self._padding,
                              normalization=self._normalization,
                              activation=self._activation,
                              name="{}_conv2d".format(self._name),
                              check_icnr_init=_CONFIG["icnr_init"],
                              **self._kwargs)(inputs)
          var_x = PixelShuffler(name="{}_pixelshuffler".format(self._name),
                                size=self._scale_factor)(var_x)
          return var_x
 
</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", </s> remove                 var_x = Concatenate(name="{}_concatenate".format(self._name))([var_x_sr, var_x2])
 </s> add                 var_x = Concatenate(name=f"{self._name}_concatenate")([var_x_sr, var_x2]) </s> remove                                 name="{}_seperableconv2d".format(self._name),
 </s> add                                 name=f"{self._name}_seperableconv2d", </s> remove         var_x = Activation("relu", name="{}_relu".format(self._name))(var_x)
 </s> add         var_x = Activation("relu", name=f"{self._name}_relu")(var_x)
                            name=f"{self._name}_conv2d",
                              strides=(1, 1),
                              padding=self._padding,
                              normalization=self._normalization,
                              activation=self._activation,
                            name=f"{self._name}_conv2d",
                              check_icnr_init=_CONFIG["icnr_init"],
                              **self._kwargs)(inputs)
          var_x = PixelShuffler(name="{}_pixelshuffler".format(self._name),
                                size=self._scale_factor)(var_x)
          return 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