original_docstring: 
          Adds a saver to the saver map.
          All subclasses should still use severs_map even if they do not store a tensorflow saver
          :param name: The key of the saver
          :param variable_list: The list of variables to save
          :return: None
          
docstring: Adds a saver to the saver map.
  All subclasses should still use severs_map even if they do not store a tensorflow saver
docstring_tokens: Adds a saver to the saver map . All subclasses should still use severs_map even if they do not store a tensorflow saver
code: def add_saver(self, name, variable_list):
          """
          Adds a saver to the saver map.
          All subclasses should still use severs_map even if they do not store a tensorflow saver
          :param name: The key of the saver
          :param variable_list: The list of variables to save
          :return: None
          """
          if len(variable_list) == 0:
              print('no variables for saver ', name)
              return
          try:
              self.savers_map[name] = tf.train.Saver(variable_list)
          except Exception as e:
              print('error for saver ', name)
              raise e
code_tokens: def add_saver ( self , name , variable_list ) : if len ( variable_list ) == 0 : print ( 'no variables for saver ' , name ) return try : self . savers_map [ name ] = tf . train . Saver ( variable_list ) except Exception as e : print ( 'error for saver ' , name ) raise e
short_docstring: Adds a saver to the saver map.
short_docstring_tokens: Adds a saver to the saver map .
comment: """
          Adds a saver to the saver map.
          All subclasses should still use severs_map even if they do not store a tensorflow saver
          :param name: The key of the saver
          :param variable_list: The list of variables to save
          :return: None
          """