  from ._base import KerasModel, ModelBase, get_all_sub_models
  
  logger = logging.getLogger(__name__)  # pylint: disable=invalid-name
  
  
  if get_backend() == "amd":
      from keras import applications as kapp, backend as K
      from keras.layers import (
 
</s> remove if sys.version_info < (3, 8):
    from typing_extensions import Literal
else:
    from typing import Literal

 </s> add  </s> remove           flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics
 </s> add           flake8 . --select=E9,F63,F7,F82 --show-source </s> remove           flake8 . --count --exit-zero --max-complexity=10 --max-line-length=100 --statistics
 </s> add           flake8 . --exit-zero </s> remove         face_loss = self._loss_dict[self._config["loss_function"]]
 </s> add         face_losses = [(self._loss_dict[v], self._config.get(f"loss_weight_{k[-1]}", 100))
                       for k, v in sorted(self._config.items())
                       if k.startswith("loss_function")
                       and self._config.get(f"loss_weight_{k[-1]}", 100) != 0
                       and v is not None]
if sys.version_info < (3, 8):
    from typing_extensions import Literal
else:
    from typing import Literal

  from ._base import KerasModel, ModelBase, get_all_sub_models
  
if sys.version_info < (3, 8):
    from typing_extensions import Literal
else:
    from typing import Literal

  logger = logging.getLogger(__name__)  # pylint: disable=invalid-name
  
  
  if get_backend() == "amd":
      from keras import applications as kapp, backend as K
      from keras.layers import (
keep add keep keep keep keep keep keep
 Training updates
  - Add multiple selected loss functions
  - Unlock loss as a model configuration
  - Phaze-A remove encoder scaling max xap 
plugins/train/model/phaze_a.py