  from keras.layers.convolutional import Conv2D
  from keras.layers.core import Activation
  from keras.initializers import he_uniform, VarianceScaling
  from .initializers import ICNR, ConvolutionAware
  from .layers import PixelShuffler, SubPixelUpscaling, ReflectionPadding2D
  from .normalization import InstanceNormalization
  
  logger = logging.getLogger(__name__)  # pylint: disable=invalid-name
  
  
 
</s> remove _PARAMS = ["use_subpixel", "use_icnr_init", "use_convaware_init", "use_reflect_padding"]
 </s> add _PARAMS = ["use_icnr_init", "use_convaware_init", "use_reflect_padding"] </s> remove                  use_subpixel=False,
 </s> add  </s> remove         if self.use_subpixel:
            var_x = SubPixelUpscaling(name="{}_subpixel".format(name),
                                      scale_factor=scale_factor)(var_x)
        else:
            var_x = PixelShuffler(name="{}_pixelshuffler".format(name), size=scale_factor)(var_x)
 </s> add         var_x = PixelShuffler(name="{}_pixelshuffler".format(name), size=scale_factor)(var_x) </s> remove             # NB: Clipnorm is ballooning VRAM usage, which is not expected behavior
            # and may be a bug in Keras/TF.
            # PlaidML has a bug regarding the clipnorm parameter
 </s> add             # NB: Clip-norm is ballooning VRAM usage, which is not expected behavior
            # and may be a bug in Keras/Tensorflow.
            # PlaidML has a bug regarding the clip-norm parameter </s> remove         self.state.config["subpixel_upscaling"] = False
 </s> add 
from .layers import PixelShuffler, ReflectionPadding2D
  from keras.layers.convolutional import Conv2D
  from keras.layers.core import Activation
  from keras.initializers import he_uniform, VarianceScaling
  from .initializers import ICNR, ConvolutionAware
from .layers import PixelShuffler, ReflectionPadding2D
  from .normalization import InstanceNormalization
  
  logger = logging.getLogger(__name__)  # pylint: disable=invalid-name
  
  
keep keep keep keep replace keep keep keep keep keep
 Remove subpixel upscaling option (#1024) 
lib/model/nn_blocks.py