parameters: (self, optimizer, constraint_optimizer=None)
docstring: Constructs a new `AdditiveSwapRegretOptimizer`.
  
      Args:
        optimizer: tf.compat.v1.train.Optimizer, used to optimize the objective
          and proxy_constraints portion of ConstrainedMinimizationProblem. If
          constraint_optimizer is not provided, this will also be used to optimize
          the Lagrange multiplier analogues.
        constraint_optimizer: optional tf.compat.v1.train.Optimizer, used to
          optimize the Lagrange multiplier analogues.
  
      Returns:
        A new `AdditiveSwapRegretOptimizer`.
docstring_summary: Constructs a new `AdditiveSwapRegretOptimizer`.
docstring_tokens: Constructs a new AdditiveSwapRegretOptimizer .
function: def __init__(self, optimizer, constraint_optimizer=None):
      """Constructs a new `AdditiveSwapRegretOptimizer`.
  
      Args:
        optimizer: tf.compat.v1.train.Optimizer, used to optimize the objective
          and proxy_constraints portion of ConstrainedMinimizationProblem. If
          constraint_optimizer is not provided, this will also be used to optimize
          the Lagrange multiplier analogues.
        constraint_optimizer: optional tf.compat.v1.train.Optimizer, used to
          optimize the Lagrange multiplier analogues.
  
      Returns:
        A new `AdditiveSwapRegretOptimizer`.
      """
      # TODO(acotter): add a parameter determining the initial values of the
      # matrix elements (like initial_multiplier_radius in
      # MultiplicativeSwapRegretOptimizer).
      super(AdditiveSwapRegretOptimizer, self).__init__(
          optimizer=optimizer, constraint_optimizer=constraint_optimizer)
function_tokens: def __init__ ( self , optimizer , constraint_optimizer = None ) : # TODO(acotter): add a parameter determining the initial values of the # matrix elements (like initial_multiplier_radius in # MultiplicativeSwapRegretOptimizer). super ( AdditiveSwapRegretOptimizer , self ) . __init__ ( optimizer = optimizer , constraint_optimizer = constraint_optimizer )