          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"
          original_init = self.switch_kernel_initializer(kwargs, VarianceScaling(
              scale=0.2,
              mode="fan_in",
              distribution="uniform"))
          var_x = self.conv2d(var_x, filters,
                              kernel_size=kernel_size,
                              padding=padding,
                              force_initializer=True,
                              **kwargs)
 
</s> remove                             force_initializer=True,
 </s> add  </s> remove         self.switch_kernel_initializer(kwargs, original_init)
 </s> add  </s> remove         original = kwargs["kernel_initializer"]
 </s> add         original = kwargs.get("kernel_initializer", None) </s> remove from keras.initializers import he_uniform, VarianceScaling
 </s> add from keras.initializers import he_uniform
          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,
                              force_initializer=True,
                              **kwargs)
keep keep keep keep replace replace replace replace keep keep keep keep keep
 Remove he_uniform from init from res block and use FS default 
lib/model/nn_blocks.py