  
      def __init__(self, learning_rate=0.001, beta_1=0.9, beta_2=0.999, epsilon=1e-14,
                   weight_decay=0.0, rectify=True, amsgrad=False, sma_threshold=5.0, total_steps=0,
                   warmup_proportion=0.1, min_lr=0.0, name="AdaBeliefOptimizer", **kwargs):
          super().__init__(name, **kwargs)
          self._set_hyper("learning_rate", kwargs.get("lr", learning_rate))
          self._set_hyper("beta_1", beta_1)
          self._set_hyper("beta_2", beta_2)
          self._set_hyper("decay", self._initial_decay)
          self._set_hyper("weight_decay", weight_decay)
 
</s> remove             self.data_format = K.normalize_data_format(data_format)
 </s> add             self.data_format = K.normalize_data_format(data_format)  # pylint:disable=no-member </s> remove         super(SubPixelUpscaling, self).__init__(**kwargs)
 </s> add         super().__init__(**kwargs) </s> remove             self.data_format = K.normalize_data_format(data_format)
 </s> add             self.data_format = K.normalize_data_format(data_format)  # pylint:disable=no-member </s> remove         super(L2_normalize, self).__init__(**kwargs)
 </s> add         super().__init__(**kwargs)
        # pylint:disable=too-many-arguments
  
      def __init__(self, learning_rate=0.001, beta_1=0.9, beta_2=0.999, epsilon=1e-14,
                   weight_decay=0.0, rectify=True, amsgrad=False, sma_threshold=5.0, total_steps=0,
                   warmup_proportion=0.1, min_lr=0.0, name="AdaBeliefOptimizer", **kwargs):
        # pylint:disable=too-many-arguments
          super().__init__(name, **kwargs)
          self._set_hyper("learning_rate", kwargs.get("lr", learning_rate))
          self._set_hyper("beta_1", beta_1)
          self._set_hyper("beta_2", beta_2)
          self._set_hyper("decay", self._initial_decay)
          self._set_hyper("weight_decay", weight_decay)
keep keep keep add keep 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/model/optimizers_tf.py