              "will be input an image of 112px at 50%% scaling. See the Architecture tooltip for "
              "the minimum and maximum sizes for each encoder. NB: The input size will be rounded "
              "down to the nearest 16 pixels."),
          "datatype": int,
          "min_max": (0, 100),
          "rounding": 1,
          "group": "encoder",
          "fixed": True},
      "enc_load_weights": {
          "default": True,
 
</s> remove         "choices": ["average_pooling", "dense", "max_pooling"],
 </s> add         "choices": ["average_pooling", "dense", "max_pooling", "flatten"], </s> remove             "\n\tmax_pooling: Use a Global Max Pooling 2D layer for the bottleneck."),
 </s> add             "\n\tmax_pooling: Use a Global Max Pooling 2D layer for the bottleneck."
            "\n\flatten: Don't use a bottleneck at all. Some encoders output in a size that make "
            "a bottleneck unnecessary. This option flattens the output from the encoder, with no "
            "further operations"), </s> remove     def _reshape_for_output(self, inputs: Tensor) -> Tensor:
 </s> add     def _reshape_for_output(self, inputs: tf.Tensor) -> tf.Tensor: </s> remove     bottleneck: str
        The type of layer to use for the bottleneck
 </s> add     bottleneck: str or ``None``
        The type of layer to use for the bottleneck. ``None`` to not use a bottleneck
        "min_max": (0, 200),
              "will be input an image of 112px at 50%% scaling. See the Architecture tooltip for "
              "the minimum and maximum sizes for each encoder. NB: The input size will be rounded "
              "down to the nearest 16 pixels."),
          "datatype": int,
        "min_max": (0, 200),
          "rounding": 1,
          "group": "encoder",
          "fixed": True},
      "enc_load_weights": {
          "default": True,
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_defaults.py