                              padding=padding,
                              **kwargs)
          var_x = LeakyReLU(alpha=0.2)(var_x)
          if self.use_reflect_padding:
              var_x = ReflectionPadding2D(stride=1, kernel_size=kernel_size)(var_x)
              padding = "valid"
          var_x = self.conv2d(var_x, filters,
                              kernel_size=kernel_size,
                              padding=padding,
                              **kwargs)
 
</s> remove         var_x = LeakyReLU(alpha=0.2)(var_x)
 </s> add         var_x = LeakyReLU(alpha=0.2, name="{}_leakyrelu_1".format(name))(var_x) </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) </s> remove         var_x = LeakyReLU(alpha=0.2)(inp)
 </s> add         name = self.get_name("residual")
        var_x = LeakyReLU(alpha=0.2, name="{}_leakyrelu_0".format(name))(inp)
            var_x = ReflectionPadding2D(stride=1,
                                        kernel_size=kernel_size,
                                        name="{}_reflectionpadding2d_1".format(name))(var_x)
                              padding=padding,
                              **kwargs)
          var_x = LeakyReLU(alpha=0.2)(var_x)
          if self.use_reflect_padding:
            var_x = ReflectionPadding2D(stride=1,
                                        kernel_size=kernel_size,
                                        name="{}_reflectionpadding2d_1".format(name))(var_x)
              padding = "valid"
          var_x = self.conv2d(var_x, filters,
                              kernel_size=kernel_size,
                              padding=padding,
                              **kwargs)
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