          -------
          :class:`keras.models.Model`
              The Decoder model
          """
          inputs = Input(shape=self._input_shape)
  
          num_ups_in_fc = self._config["dec_upscales_in_fc"]
  
          if self._config["learn_mask"] and num_ups_in_fc:
              # Mask has already been created in FC and is an output of that model
 
</s> remove             inputs = [inputs, Input(shape=self._input_shape)]
 </s> add             inputs = [inputs, kl.Input(shape=self._input_shape)] </s> remove         input_ = Input(shape=self._input_shape)
 </s> add         input_ = kl.Input(shape=self._input_shape) </s> remove         input_ = Input(shape=self._input_shape)
 </s> add         input_ = kl.Input(shape=self._input_shape) </s> remove     def _reshape_for_output(self, inputs: Tensor) -> Tensor:
 </s> add     def _reshape_for_output(self, inputs: tf.Tensor) -> tf.Tensor:
        inputs = kl.Input(shape=self._input_shape)
          -------
          :class:`keras.models.Model`
              The Decoder model
          """
        inputs = kl.Input(shape=self._input_shape)
  
          num_ups_in_fc = self._config["dec_upscales_in_fc"]
  
          if self._config["learn_mask"] and num_ups_in_fc:
              # Mask has already been created in FC and is an output of that model
keep keep keep keep replace keep keep keep keep keep
 Updates:
    - Remove clipfaker
    - Add clip to Phaze-A
    - streamline clip to vision only
    - update lib.model.networks
    - Docs and tests update
    - Phaze-A - add option to flatten bottleneck 
plugins/train/model/phaze_a.py