      def __init__(self,
                   input_shape: tuple[int, ...],
                   scale: int,
                   name: str,
                   *args, **kwargs) -> None:
          super().__init__(name=name, *args, **kwargs)
          self._input_shape = input_shape
          self._scale = scale
          self._var: tf.Variable
  
      def build(self, input_shape: tuple[int, ...]) -> None:
 
</s> remove         self._name = kwargs.pop("name") if "name" in kwargs else _get_name(
 </s> add         self._name = _get_name(kwargs.pop("name")) if "name" in kwargs else _get_name( </s> remove                                                                dtype=self.compute_dtype),
 </s> add                                                                dtype=self.dtype), </s> remove                                   name=self._name.lower())
 </s> add                                   name="visual")
                 *args,
                 dtype="float32",
                 **kwargs) -> None:
        super().__init__(name=name, dtype=dtype, *args, **kwargs)
      def __init__(self,
                   input_shape: tuple[int, ...],
                   scale: int,
                   name: str,
                 *args,
                 dtype="float32",
                 **kwargs) -> None:
        super().__init__(name=name, dtype=dtype, *args, **kwargs)
                 *args,
                 dtype="float32",
                 **kwargs) -> None:
        super().__init__(name=name, dtype=dtype, *args, **kwargs)
          self._input_shape = input_shape
          self._scale = scale
          self._var: tf.Variable
  
      def build(self, input_shape: tuple[int, ...]) -> None:
keep keep keep keep replace replace keep keep keep keep keep
 fixes
  - Farl weight name fix
  - Embedding layers to fp32
  - nn_blocks - unique names for conv_output
  - Phaze-A - Add clipfaker presets 
lib/model/networks/clip.py