  import inspect
  
  import numpy as np
  import tensorflow as tf
  from keras import initializers
  from keras.utils.generic_utils import get_custom_objects
  
  logger = logging.getLogger(__name__)  # pylint: disable=invalid-name
  
 
</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 </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
from keras import backend as K
  import inspect
  
  import numpy as np
  import tensorflow as tf
from keras import backend as K
  from keras import initializers
  from keras.utils.generic_utils import get_custom_objects
  
  logger = logging.getLogger(__name__)  # pylint: disable=invalid-name
  
keep keep keep add 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 
lib/model/initializers.py