                      layer.rate = rate
                      updated = True
          if updated:
              logger.debug("Dropout rate updated. Cloning model")
              new_model = clone_model(model)
              new_model.set_weights(model.get_weights())
              del model
              model = new_model
          return model
  
 
</s> remove                 if not isinstance(layer, Dropout):
 </s> add                 if not isinstance(layer, kl.Dropout): </s> remove         inputs = Input(shape=self._input_shape)
 </s> add         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         self.input_shape = self._get_input_shape()
 </s> add         self.input_shape: tuple[int, int, int] = self._get_input_shape()
            new_model = keras.models.clone_model(model)
                      layer.rate = rate
                      updated = True
          if updated:
              logger.debug("Dropout rate updated. Cloning model")
            new_model = keras.models.clone_model(model)
              new_model.set_weights(model.get_weights())
              del model
              model = new_model
          return 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