      Based on the original https://www.reddit.com/r/deepfakes/
          code sample + contribs """
  
  from keras.initializers import RandomNormal
  from keras.layers import Conv2D, Dense, Flatten, Input, Reshape, SpatialDropout2D
  from keras.models import Model as KerasModel
  
  from .original import logger, Model as OriginalModel
  
  
 
</s> remove from keras.layers import Conv2D, Dense, Flatten, Input, Reshape
 </s> add from keras.layers import Dense, Flatten, Input, Reshape
 </s> remove from keras.layers import Conv2D, Dense, Flatten, Input, Reshape
 </s> add from keras.layers import Dense, Flatten, Input, Reshape </s> remove from keras.layers import Conv2D, Input
 </s> add from keras.layers import Input </s> remove from keras.layers import Conv2D, Dense, Flatten, Input, Reshape
 </s> add from keras.layers import Dense, Flatten, Input, Reshape </s> remove from keras.initializers import he_uniform, Constant, VarianceScaling
from .initializers import ICNR
 </s> add from keras.initializers import he_uniform, VarianceScaling
from .initializers import ICNR, ConvolutionAware
from keras.layers import Dense, Flatten, Input, Reshape, SpatialDropout2D
      Based on the original https://www.reddit.com/r/deepfakes/
          code sample + contribs """
  
  from keras.initializers import RandomNormal
from keras.layers import Dense, Flatten, Input, Reshape, SpatialDropout2D
  from keras.models import Model as KerasModel
  
  from .original import logger, Model as OriginalModel
  
  
keep keep keep keep replace keep keep keep keep keep
 Add Convolutional Aware Initialization (#795)

* Training: Add Convolutional Aware Initialization config option

* Centralize Conv2D layer for handling initializer

* Add 'is-output' to NNMeta to indicate that network is an output to the Model 
plugins/train/model/unbalanced.py