          self._filters = filters if self._fast else filters - int(filters * sr_ratio)
          self._kernel_size = kernel_size
          self._padding = padding
          self._interpolation = interpolation
          self._res_block_follows = res_block_follows
          self._scale_factor = scale_factor
          self._kwargs = kwargs
  
      def __call__(self, inputs):
          """ Call the Faceswap Upscale 2x Layer.
 
</s> remove         self._use_instance_norm = use_instance_norm
        self._res_block_follows = res_block_follows
 </s> add         self._normalization = normalization
        self._activation = activation </s> remove         self._use_instance_norm = use_instance_norm
        self._res_block_follows = res_block_follows
 </s> add         self._normalization = None if not normalization else normalization.lower()
        self._activation = None if not activation else activation.lower()
        self._use_depthwise = use_depthwise

        self._assert_arguments()

    def _assert_arguments(self):
        """ Validate the given arguments. """
        assert self._normalization in ("batch", "instance", None), (
            "normalization should be 'batch', 'instance' or None")
        assert self._activation in ("leakyrelu", "swish", None), (
            "activation should be 'leakyrelu', 'swish' or None") </s> remove         self._filters = filters
        self._kernel_size = kernel_size
 </s> add         self._args = (kernel_size, ) if use_depthwise else (filters, kernel_size) </s> remove                  res_block_follows=False, sr_ratio=0.5, scale_factor=2, fast=False, **kwargs):
 </s> add                  activation="leakyrelu", sr_ratio=0.5, scale_factor=2, fast=False, **kwargs): </s> remove         initializer = self._get_default_initializer(kwargs.pop("kernel_initializer", None))
 </s> add         initializer = _get_default_initializer(kwargs.pop("kernel_initializer", None))
        self._activation = activation
          self._filters = filters if self._fast else filters - int(filters * sr_ratio)
          self._kernel_size = kernel_size
          self._padding = padding
          self._interpolation = interpolation
        self._activation = activation
          self._scale_factor = scale_factor
          self._kwargs = kwargs
  
      def __call__(self, inputs):
          """ Call the Faceswap Upscale 2x Layer.
keep keep keep keep replace keep keep keep keep keep
 lib.model - Maintenance
  - Add Depthwise option to Conv Block
  - Add Swish Activation function
  - remove res_block_follows and add_instance_norm_args
  - Add explicit normalization and activation args
  - Add K.resize_images layer
plugins.train.model - Inference creation bugfix 
lib/model/nn_blocks.py