parameters: (self, inputs, training, **kwargs)
return_statement: return class_outputs
docstring: Call ClassNet.
docstring_summary: Call ClassNet.
docstring_tokens: Call ClassNet .
function: def call(self, inputs, training, **kwargs):
          """Call ClassNet."""
          class_outputs = []
          for level_id in range(0, self.max_level - self.min_level + 1):
              image = inputs[level_id]
              for i in range(self.repeats):
                  image = self._conv_bn_act(image, i, level_id, training)
  
              class_outputs.append(self.classes(image))
  
          return class_outputs
function_tokens: def call ( self , inputs , training , * * kwargs ) : class_outputs = [ ] for level_id in range ( 0 , self . max_level - self . min_level + 1 ) : image = inputs [ level_id ] for i in range ( self . repeats ) : image = self . _conv_bn_act ( image , i , level_id , training ) class_outputs . append ( self . classes ( image ) ) return class_outputs