  
          dims = self.input_shape[-1] * self.decoder_dim
          var_x = input_
  
          var_x1 = UpscaleBlock(dims * 8, res_block_follows=True)(var_x)
          var_x1 = ResidualBlock(dims * 8)(var_x1)
          var_x1 = ResidualBlock(dims * 8)(var_x1)
          if self.multiscale_count >= 3:
              outputs.append(Conv2DOutput(3, 5, name="face_out_32_{}".format(side))(var_x1))
  
 
</s> remove         var_x2 = UpscaleBlock(dims * 4, res_block_follows=True)(var_x1)
 </s> add         var_x2 = UpscaleBlock(dims * 4, activation=None)(var_x1) </s> remove         var_x3 = UpscaleBlock(dims * 2, res_block_follows=True)(var_x2)
 </s> add         var_x3 = UpscaleBlock(dims * 2, activation=None)(var_x2) </s> remove         var_x1 = Conv2DBlock(self.encoder_filters * 4)(var_x)
 </s> add         var_x1 = Conv2DBlock(self.encoder_filters * 4, 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 * 8)(var_x)
 </s> add         var_x1 = Conv2DBlock(self.encoder_filters * 8, activation="leakyrelu")(var_x)
        var_x1 = UpscaleBlock(dims * 8, activation=None)(var_x)
  
          dims = self.input_shape[-1] * self.decoder_dim
          var_x = input_
  
        var_x1 = UpscaleBlock(dims * 8, activation=None)(var_x)
          var_x1 = ResidualBlock(dims * 8)(var_x1)
          var_x1 = ResidualBlock(dims * 8)(var_x1)
          if self.multiscale_count >= 3:
              outputs.append(Conv2DOutput(3, 5, name="face_out_32_{}".format(side))(var_x1))
  
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 
plugins/train/model/dfl_sae.py