  
      @staticmethod
      def set_vars():
          """ Override to return a dict of page specific variables """
          return dict()
  
      def on_tab_select(self):  # pylint:disable=no-self-use
          """ Override for specific actions when the current tab is selected """
          logger.debug("Returning as 'on_tab_select' not implemented for %s",
                       self.__class__.__name__)
 
</s> remove                 text=_("Enable or disable {} display").format(self.tabname),
 </s> add                 text=_(f"Enable or disable {self.tabname} display"), </s> remove         self._trace_vars = dict()
 </s> add         self._trace_vars = {} </s> remove     def call(self, inputs, **kwargs):
 </s> add     def call(self, inputs, *args, **kwargs): </s> remove         state_file = os.path.join(self._model_dir, "{}_state.json".format(self._model_name))
 </s> add         state_file = os.path.join(self._model_dir, f"{self._model_name}_state.json") </s> remove         self.c_1 = (self.k_1 * self.max_value) ** 2
        self.c_2 = (self.k_2 * self.max_value) ** 2
        self.dim_ordering = K.image_data_format()

    @staticmethod
    def _int_shape(input_tensor):
        """ Returns the shape of tensor or variable as a tuple of int or None entries.

        Parameters
        ----------
        input_tensor: tensor or variable
            The input to return the shape for

        Returns
        -------
        tuple
            A tuple of integers (or None entries)
        """
        return K.int_shape(input_tensor)
 </s> add 
        return {}
  
      @staticmethod
      def set_vars():
          """ Override to return a dict of page specific variables """
        return {}
  
      def on_tab_select(self):  # pylint:disable=no-self-use
          """ Override for specific actions when the current tab is selected """
          logger.debug("Returning as 'on_tab_select' not implemented for %s",
                       self.__class__.__name__)
keep keep keep keep replace keep keep keep keep keep
 Update code to support Tensorflow versions up to 2.8 (#1213)

* Update maximum tf version in setup + requirements

* - bump max version of tf version in launcher
- standardise tf version check

* update keras get_custom_objects  for tf>2.6

* bugfix: force black text in GUI file dialogs (linux)

* dssim loss - Move to stock tf.ssim function

* Update optimizer imports for compatibility

* fix logging for tf2.8

* Fix GUI graphing for TF2.8

* update tests

* bump requirements.txt versions

* Remove limit on nvidia-ml-py

* Graphing bugfixes
  - Prevent live graph from displaying if data not yet available

* bugfix: Live graph. Collect loss labels correctly

* fix: live graph - swallow inconsistent loss errors

* Bugfix: Prevent live graph from clearing during training

* Fix graphing for AMD 
lib/gui/display_page.py