      def decoder(self, side):
          """ Decoder Network """
          input_ = Input(shape=(8, 8, 256))
          var_x = input_
          var_x = UpscaleBlock(512)(var_x)
          var_x = UpscaleBlock(256)(var_x)
          var_x = UpscaleBlock(128)(var_x)
          var_x = Conv2DOutput(3, 5, activation="sigmoid", name="face_out_{}".format(side))(var_x)
          outputs = [var_x]
  
          if self.config.get("learn_mask", False):
              var_y = input_
 
</s> remove         var_x = UpscaleBlock(512)(var_x)
        var_x = UpscaleBlock(256)(var_x)
        var_x = UpscaleBlock(128)(var_x)
        var_x = UpscaleBlock(64)(var_x)
 </s> add         var_x = UpscaleBlock(512, activation="leakyrelu")(var_x)
        var_x = UpscaleBlock(256, activation="leakyrelu")(var_x)
        var_x = UpscaleBlock(128, activation="leakyrelu")(var_x)
        var_x = UpscaleBlock(64, activation="leakyrelu")(var_x) </s> remove         var_x = UpscaleBlock(256)(var_x)
 </s> add         var_x = UpscaleBlock(256, activation="leakyrelu")(var_x)
 </s> remove         var_x = UpscaleBlock(256)(var_x)
        var_x = UpscaleBlock(128)(var_x)
        var_x = UpscaleBlock(64)(var_x)
 </s> add         var_x = UpscaleBlock(256, activation="leakyrelu")(var_x)
        var_x = UpscaleBlock(128, activation="leakyrelu")(var_x)
        var_x = UpscaleBlock(64, activation="leakyrelu")(var_x)
 </s> remove         var_x = UpscaleBlock(self.encoder_dim)(var_x)
        var_x = UpscaleBlock(self.encoder_dim // 2)(var_x)
        var_x = UpscaleBlock(self.encoder_dim // 4)(var_x)
 </s> add         var_x = UpscaleBlock(self.encoder_dim, activation="leakyrelu")(var_x)
        var_x = UpscaleBlock(self.encoder_dim // 2, activation="leakyrelu")(var_x)
        var_x = UpscaleBlock(self.encoder_dim // 4, activation="leakyrelu")(var_x) </s> remove         var_x = UpscaleBlock(64)(var_x)
 </s> add         var_x = UpscaleBlock(64, activation="leakyrelu")(var_x)
        var_x = UpscaleBlock(512, activation="leakyrelu")(var_x)
        var_x = UpscaleBlock(256, activation="leakyrelu")(var_x)
        var_x = UpscaleBlock(128, activation="leakyrelu")(var_x)

      def decoder(self, side):
          """ Decoder Network """
          input_ = Input(shape=(8, 8, 256))
          var_x = input_
        var_x = UpscaleBlock(512, activation="leakyrelu")(var_x)
        var_x = UpscaleBlock(256, activation="leakyrelu")(var_x)
        var_x = UpscaleBlock(128, activation="leakyrelu")(var_x)
        var_x = UpscaleBlock(512, activation="leakyrelu")(var_x)
        var_x = UpscaleBlock(256, activation="leakyrelu")(var_x)
        var_x = UpscaleBlock(128, activation="leakyrelu")(var_x)
        var_x = UpscaleBlock(512, activation="leakyrelu")(var_x)
        var_x = UpscaleBlock(256, activation="leakyrelu")(var_x)
        var_x = UpscaleBlock(128, activation="leakyrelu")(var_x)
          var_x = Conv2DOutput(3, 5, activation="sigmoid", name="face_out_{}".format(side))(var_x)
          outputs = [var_x]
  
          if self.config.get("learn_mask", False):
              var_y = input_
keep keep keep keep replace replace 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/lightweight.py