          base_config = super(ICNR, self).get_config()
          return dict(list(base_config.items()) + list(config.items()))
  
  
  class ConvolutionAware(initializers.Initializer):
      """
      Initializer that generates orthogonal convolution filters in the Fourier space. If this
      initializer is passed a shape that is not 3D or 4D, orthogonal initialization will be used.
  
      Adapted, fixed and optimized from:
 
</s> remove         base_config = super(ICNR, self).get_config()
 </s> add         base_config = super().get_config() </s> remove         base_config = super(PixelShuffler, self).get_config()
 </s> add         base_config = super().get_config() </s> remove         base_config = super(_GlobalPooling2D, self).get_config()
 </s> add         base_config = super().get_config() </s> remove         base_config = super(ReflectionPadding2D, self).get_config()
 </s> add         base_config = super().get_config() </s> remove         base_config = super(SubPixelUpscaling, self).get_config()
 </s> add         base_config = super().get_config()
class ConvolutionAware(initializers.Initializer):  # pylint: disable=no-member
          base_config = super(ICNR, self).get_config()
          return dict(list(base_config.items()) + list(config.items()))
  
  
class ConvolutionAware(initializers.Initializer):  # pylint: disable=no-member
      """
      Initializer that generates orthogonal convolution filters in the Fourier space. If this
      initializer is passed a shape that is not 3D or 4D, orthogonal initialization will be used.
  
      Adapted, fixed and optimized from:
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/model/initializers.py