  
  model.losses module
  ===================
  
  The losses listed here are generated from the docstrings in :mod:`lib.model.losses_tf`, however
  the functions are exactly the same for :mod:`lib.model.losses_plaid`. The correct loss module will
  be imported as :mod:`lib.model.losses` depending on the backend in use.
  
  .. rubric:: Module Summary
  
  .. autosummary::
     :nosignatures:
  
 
</s> remove         A list of all :class:`keras.models.Model` objects found within the given model. The
        provided model will always be returned in the first position
 </s> add         A list of all :class:`tensorflow.keras.models.Model` objects found within the given model.
        The provided model will always be returned in the first position </s> remove     :class:`SubPixelUpscaling` layer to speed up the learning process. However, if you are stacking
    multiple :class:`SubPixelUpscaling` blocks, it may increase the number of parameters greatly,
    so the Convolution layer after :class:`SubPixelUpscaling` layer can be removed.
 </s> add     :class:`PixelShuffler` layer to speed up the learning process. However, if you are stacking
    multiple :class:`PixelShuffler` blocks, it may increase the number of parameters greatly,
    so the Convolution layer after :class:`PixelShuffler` layer can be removed. </s> remove     def get_config(self):
 </s> add     def get_config(self) -> dict[str, T.Any]: </s> remove     def get_config(self):
 </s> add     def get_config(self) -> dict[str, T.Any]:
  
  model.losses module
  ===================
  




  .. rubric:: Module Summary
  
  .. autosummary::
     :nosignatures:
  
keep keep keep keep replace replace replace replace keep keep keep keep keep
 Training fixes:
  - Fix mixed precision layer storing and switching
  - typofix in _requirements_base.txt
  - lib.model.layers - cleanup, docs and tests fixes
  - lib.model.nn_blocks - typing fixes 
docs/full/lib/model.rst