      AdaInstanceNormalization, GroupNormalization, InstanceNormalization, LayerNormalization,
      RMSNormalization)
  from lib.utils import get_backend, get_tf_version, FaceswapError
  
  from ._base import KerasModel, ModelBase, logger, _get_all_sub_models
  
  if get_backend() == "amd":
      from keras import applications as kapp, backend as K
      from keras.layers import (
          Add, BatchNormalization, Concatenate, Dense, Dropout, Flatten, GaussianNoise, MaxPool2D,
 
</s> remove from ._base import ModelBase, KerasModel, logger
 </s> add from ._base import ModelBase, KerasModel </s> remove from ._base import ModelBase, KerasModel, logger
 </s> add from ._base import ModelBase, KerasModel </s> remove from ._base import ModelBase, KerasModel, logger
 </s> add from ._base import ModelBase, KerasModel </s> remove     from keras.initializers import RandomNormal
 </s> add     from keras.initializers import RandomNormal  # pylint:disable=no-name-in-module </s> remove     from keras.initializers import RandomNormal
 </s> add     from keras.initializers import RandomNormal  # pylint:disable=no-name-in-module
from ._base import KerasModel, ModelBase, get_all_sub_models

logger = logging.getLogger(__name__)  # pylint: disable=invalid-name

      AdaInstanceNormalization, GroupNormalization, InstanceNormalization, LayerNormalization,
      RMSNormalization)
  from lib.utils import get_backend, get_tf_version, FaceswapError
  
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 (
          Add, BatchNormalization, Concatenate, Dense, Dropout, Flatten, GaussianNoise, MaxPool2D,
keep keep keep keep replace keep keep keep keep keep
 Refactoring and TravisCI to Github Actions (#1239)

* refactor training

* travis to actions 
plugins/train/model/phaze_a.py