                  var_x1 = UpscaleBlock(self._filters,
                                        kernel_size=self._kernel_size,
                                        padding=self._padding,
                                        scale_factor=self._scale_factor,
                                        res_block_follows=self._res_block_follows,
                                        **self._kwargs)(var_x)
                  var_x = Add()([var_x2, var_x1])
              else:
                  var_x = Concatenate(name="{}_concatenate".format(self._name))([var_x_sr, var_x2])
          else:
 
</s> remove                                     res_block_follows=self._res_block_follows,
 </s> add                                     activation=self._activation, </s> remove         var_x1 = Conv2DBlock(self.encoder_filters)(var_x)
 </s> add         var_x1 = Conv2DBlock(self.encoder_filters, activation="leakyrelu")(var_x) </s> remove         var_x1 = Conv2DBlock(self.encoder_filters * 8)(var_x)
 </s> add         var_x1 = Conv2DBlock(self.encoder_filters * 8, activation="leakyrelu")(var_x) </s> remove         var_x1 = Conv2DBlock(self.encoder_filters * 2)(var_x)
 </s> add         var_x1 = Conv2DBlock(self.encoder_filters * 2, activation="leakyrelu")(var_x) </s> remove         var_x1 = Conv2DBlock(self.encoder_filters * 4)(var_x)
 </s> add         var_x1 = Conv2DBlock(self.encoder_filters * 4, activation="leakyrelu")(var_x)
                                      activation=self._activation,
                  var_x1 = UpscaleBlock(self._filters,
                                        kernel_size=self._kernel_size,
                                        padding=self._padding,
                                        scale_factor=self._scale_factor,
                                      activation=self._activation,
                                        **self._kwargs)(var_x)
                  var_x = Add()([var_x2, var_x1])
              else:
                  var_x = Concatenate(name="{}_concatenate".format(self._name))([var_x_sr, var_x2])
          else:
keep keep keep keep replace keep keep keep keep keep
 lib.model - Maintenance
  - Add Depthwise option to Conv Block
  - Add Swish Activation function
  - remove res_block_follows and add_instance_norm_args
  - Add explicit normalization and activation args
  - Add K.resize_images layer
plugins.train.model - Inference creation bugfix 
lib/model/nn_blocks.py