      @staticmethod
      def switch_kernel_initializer(kwargs, initializer):
          """ Switch the initializer in the given kwargs to the given initializer
              and return the previous initializer to caller """
          original = kwargs["kernel_initializer"]
          kwargs["kernel_initializer"] = initializer
          logger.debug("Switched kernel_initializer from %s to %s", original, initializer)
          return original
  
      def conv2d(self, inp, filters, kernel_size, strides=(1, 1), padding="same",
 
</s> remove                             force_initializer=True,
 </s> add  </s> remove         self.switch_kernel_initializer(kwargs, original_init)
 </s> add  </s> remove         original_init = self.switch_kernel_initializer(kwargs, VarianceScaling(
            scale=0.2,
            mode="fan_in",
            distribution="uniform"))
 </s> add  </s> remove from keras.initializers import he_uniform, VarianceScaling
 </s> add from keras.initializers import he_uniform
        original = kwargs.get("kernel_initializer", None)
      @staticmethod
      def switch_kernel_initializer(kwargs, initializer):
          """ Switch the initializer in the given kwargs to the given initializer
              and return the previous initializer to caller """
        original = kwargs.get("kernel_initializer", None)
          kwargs["kernel_initializer"] = initializer
          logger.debug("Switched kernel_initializer from %s to %s", original, initializer)
          return original
  
      def conv2d(self, inp, filters, kernel_size, strides=(1, 1), padding="same",
keep keep keep keep replace keep keep keep keep keep
 Remove he_uniform from init from res block and use FS default 
lib/model/nn_blocks.py