code: def convert_reduce_sum(params, w_name, scope_name, inputs, layers, weights, names):
      
      print('Converting reduce_sum ...')
  
      keepdims = params['keepdims'] > 0
      axis = params['axes']
  
      def target_layer(x, keepdims=keepdims, axis=axis):
          import keras.backend as K
          return K.sum(x, keepdims=keepdims, axis=axis)
  
      lambda_layer = keras.layers.Lambda(target_layer)
      layers[scope_name] = lambda_layer(layers[inputs[0]])
docs: Convert reduce_sum layer.
  
      Args:
          params: dictionary with layer parameters
          w_name: name prefix in state_dict
          scope_name: pytorch scope name
          inputs: pytorch node inputs
          layers: dictionary with keras tensors
          weights: pytorch state_dict
          names: use short names for keras layers