                       self._name, filters, kernel_size, strides, padding, use_instance_norm,
                       res_block_follows, kwargs)
          self._use_reflect_padding = _CONFIG["reflect_padding"]
  
          self._filters = filters
          self._kernel_size = kernel_size
          self._strides = strides
          self._padding = "valid" if self._use_reflect_padding else padding
          self._kwargs = kwargs
          self._use_instance_norm = use_instance_norm
          self._res_block_follows = res_block_follows
 
</s> remove                      "use_instance_norm: %s, res_block_follows: %s, kwargs: %s)",
                     self._name, filters, kernel_size, strides, padding, use_instance_norm,
                     res_block_follows, kwargs)
 </s> add                      "normalization: %s, activation: %s, use_depthwise: %s, kwargs: %s)",
                     self._name, filters, kernel_size, strides, padding, normalization,
                     activation, use_depthwise, kwargs)
 </s> remove                      "use_instance_norm: %s, res_block_follows: %s, kwargs: %s)",
                     self._name, filters, kernel_size, padding, scale_factor, use_instance_norm,
                     res_block_follows, kwargs)
 </s> add                      "normalization: %s, activation: %s, kwargs: %s)",
                     self._name, filters, kernel_size, padding, scale_factor, normalization,
                     activation, kwargs) </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._res_block_follows = res_block_follows
 </s> add         self._activation = activation
        self._args = (kernel_size, ) if use_depthwise else (filters, kernel_size)
                       self._name, filters, kernel_size, strides, padding, use_instance_norm,
                       res_block_follows, kwargs)
          self._use_reflect_padding = _CONFIG["reflect_padding"]
  
        self._args = (kernel_size, ) if use_depthwise else (filters, kernel_size)
        self._args = (kernel_size, ) if use_depthwise else (filters, kernel_size)
          self._strides = strides
          self._padding = "valid" if self._use_reflect_padding else padding
          self._kwargs = kwargs
          self._use_instance_norm = use_instance_norm
          self._res_block_follows = res_block_follows
keep keep keep keep replace 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