                                      kernel_size=self._kernel_size,
                                      strides=self._strides,
                                      relu_alpha=self._relu_alpha,
                                      name=f"{name}_convblk_{i}_1")(var_x)
                  var_x = MaxPool2D(2, name=f"{name}_pool_{i}")(var_x)
          return var_x
  
  
  class FullyConnected():  # pylint:disable=too-few-public-methods
      """ Intermediate Fully Connected layers for Phaze-A Model.
 
</s> remove         return KModel(self._inputs, var_x, name=f"g_block_{self._side}")
 </s> add         return keras.models.Model(self._inputs, var_x, name=f"g_block_{self._side}") </s> remove         var_x = GaussianNoise(1.0)(var_x)
 </s> add         var_x = kl.GaussianNoise(1.0)(var_x) </s> remove     def __call__(self) -> keras.models.Model:
 </s> add     def __call__(self) -> tf.keras.models.Model: </s> remove         input_ = Input(shape=self._input_shape)
 </s> add         input_ = kl.Input(shape=self._input_shape)
                var_x = kl.MaxPool2D(2, name=f"{name}_pool_{i}")(var_x)
                                      kernel_size=self._kernel_size,
                                      strides=self._strides,
                                      relu_alpha=self._relu_alpha,
                                      name=f"{name}_convblk_{i}_1")(var_x)
                var_x = kl.MaxPool2D(2, name=f"{name}_pool_{i}")(var_x)
          return var_x
  
  
  class FullyConnected():  # pylint:disable=too-few-public-methods
      """ Intermediate Fully Connected layers for Phaze-A 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