          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))
 
</s> remove             var_x = Conv2DBlock(encoder_complexity * 2**idx, activation="leakyrelu")(var_x)
 </s> add             var_x = Conv2DBlock(encoder_complexity * 2**idx, activation=None)(var_x)
            var_x = LeakyReLU(alpha=0.2)(var_x) </s> remove         var_xy = UpscaleBlock(self.dense_filters, activation="leakyrelu")(var_xy)
 </s> add         var_xy = UpscaleBlock(self.dense_filters, activation=None)(var_xy) </s> remove         var_xy = UpscaleBlock(dense_filters, activation="leakyrelu")(var_xy)
 </s> add         var_xy = UpscaleBlock(dense_filters, activation=None)(var_xy)
        var_x1 = LeakyReLU(alpha=0.2)(var_x1)
          dims = self.input_shape[-1] * self.decoder_dim
          var_x = input_
  
          var_x1 = UpscaleBlock(dims * 8, activation=None)(var_x)
        var_x1 = LeakyReLU(alpha=0.2)(var_x1)
          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 add keep keep keep keep
 Fixups:
  - lib.gui.display - Catch error when trying to delete non-existant notebook tabs
  - lib.model.nn_blocks.ResidualBlock: Remove first LeakyReLU (explicit > implicit)
  - lib.model.nn_blocks._get_default_initializer - Always use ConvAware if selected
  - plugins.model.model - Add explicit leakyReLUs for ResBlocks 
plugins/train/model/dfl_sae.py