              var_y = self.blocks.upscale(var_y, self.encoder_dim // 4)
              var_y = self.blocks.conv2d(var_y, 1,
                                         kernel_size=5,
                                         padding="same",
                                         activation="sigmoid")
              outputs.append(var_y)
          return KerasModel(input_, outputs=outputs)
 
</s> remove                                        activation="sigmoid")
 </s> add                                        activation="sigmoid",
                                       name="mask_out") </s> remove                                        activation="sigmoid")
 </s> add                                        activation="sigmoid",
                                       name="mask_out") </s> remove                                        activation="sigmoid")
 </s> add                                        activation="sigmoid",
                                       name="mask_out") </s> remove                                        activation="sigmoid")
 </s> add                                        activation="sigmoid",
                                       name="mask_out") </s> remove                                        activation="sigmoid")
 </s> add                                        activation="sigmoid",
                                       name="mask_out")

                                       activation="sigmoid",
                                       name="mask_out")
              var_y = self.blocks.upscale(var_y, self.encoder_dim // 4)
              var_y = self.blocks.conv2d(var_y, 1,
                                         kernel_size=5,
                                         padding="same",
                                       activation="sigmoid",
                                       name="mask_out")
              outputs.append(var_y)
          return KerasModel(input_, outputs=outputs)
keep keep keep keep replace keep keep
 Model Structure Changes

Standardize inputs for AutoEncoders
Name outputs from AutoEncoders
Name layers in nn_blocks.py 
plugins/train/model/dfl_h128.py