                              padding=padding,
                              name="{}_conv2d".format(name),
                              **kwargs)
          if self.use_icnr_init:
              self.switch_kernel_initializer(kwargs, original_init)
          if use_instance_norm:
              var_x = InstanceNormalization(name="{}_instancenorm".format(name))(var_x)
          if not res_block_follows:
              var_x = LeakyReLU(0.1, name="{}_leakyrelu".format(name))(var_x)
          if self.use_subpixel:
 
</s> remove             self.switch_kernel_initializer(kwargs, original_init)
        var_x = Add()([var_x, inp])
 </s> add             self._switch_kernel_initializer(kwargs, original_init)
        var_x = Add()([var_x, input_tensor]) </s> remove         var_x = self.conv2d(inp, filters * scale_factor * scale_factor,
 </s> add         var_x = self.conv2d(input_tensor, filters * scale_factor * scale_factor, </s> remove     def upscale(self, inp, filters, kernel_size=3, padding="same",
 </s> add     def upscale(self, input_tensor, filters, kernel_size=3, padding="same", </s> remove         var_x = self.conv2d(inp, filters,
 </s> add         var_x = self.conv2d(input_tensor, filters, </s> remove             original_init = self.switch_kernel_initializer(
 </s> add             original_init = self._switch_kernel_initializer(
            self._switch_kernel_initializer(kwargs, original_init)
                              padding=padding,
                              name="{}_conv2d".format(name),
                              **kwargs)
          if self.use_icnr_init:
            self._switch_kernel_initializer(kwargs, original_init)
          if use_instance_norm:
              var_x = InstanceNormalization(name="{}_instancenorm".format(name))(var_x)
          if not res_block_follows:
              var_x = LeakyReLU(0.1, name="{}_leakyrelu".format(name))(var_x)
          if self.use_subpixel:
keep keep keep keep replace keep keep keep keep keep
 Simple backend unit tests (#1020)

* Add simple backend tests for lib.model
* Document lib.model
* Fix GMSD Loss for AMD
* Remove obsolete code from lib.model 
lib/model/nn_blocks.py