          """ Convolution Layer"""
          logger.debug("inp: %s, filters: %s, kernel_size: %s, strides: %s, use_instance_norm: %s, "
                       "kwargs: %s)", inp, filters, kernel_size, strides, use_instance_norm, kwargs)
          if self.use_reflect_padding:
              inp = ReflectionPadding2D(stride=strides, kernel_size=kernel_size)(inp)
              padding = "valid"
          var_x = self.conv2d(inp, filters,
                              kernel_size=kernel_size,
                              strides=strides,
                              padding=padding,
 
</s> remove             inp = ReflectionPadding2D(stride=1, kernel_size=kernel_size)(inp)
 </s> add             inp = ReflectionPadding2D(stride=1,
                                      kernel_size=kernel_size,
                                      name="{}_reflectionpadding2d".format(name))(inp) </s> remove             var_x = ReflectionPadding2D(stride=1, kernel_size=kernel_size)(var_x)
 </s> add             var_x = ReflectionPadding2D(stride=1,
                                        kernel_size=kernel_size,
                                        name="{}_reflectionpadding2d_0".format(name))(var_x)
            inp = ReflectionPadding2D(stride=strides,
                                      kernel_size=kernel_size,
                                      name="{}_reflectionpadding2d".format(name))(inp)
          """ Convolution Layer"""
          logger.debug("inp: %s, filters: %s, kernel_size: %s, strides: %s, use_instance_norm: %s, "
                       "kwargs: %s)", inp, filters, kernel_size, strides, use_instance_norm, kwargs)
          if self.use_reflect_padding:
            inp = ReflectionPadding2D(stride=strides,
                                      kernel_size=kernel_size,
                                      name="{}_reflectionpadding2d".format(name))(inp)
              padding = "valid"
          var_x = self.conv2d(inp, filters,
                              kernel_size=kernel_size,
                              strides=strides,
                              padding=padding,
keep keep keep keep replace keep keep keep keep keep
 Model Structure Changes

Standardize inputs for AutoEncoders
Name outputs from AutoEncoders
Name layers in nn_blocks.py 
lib/model/nn_blocks.py