(self,
               learning_rate,
               weight_decay_rate=0.0,
               beta_1=0.9,
               beta_2=0.999,
               epsilon=1e-6,
               exclude_from_weight_decay=None,
               include_in_weight_decay=["r_s_bias", "r_r_bias", "r_w_bias"],
               name="AdamWeightDecayOptimizer")
Constructs a AdamWeightDecayOptimizer.
Constructs a AdamWeightDecayOptimizer.
Constructs a AdamWeightDecayOptimizer .
def __init__(self,
               learning_rate,
               weight_decay_rate=0.0,
               beta_1=0.9,
               beta_2=0.999,
               epsilon=1e-6,
               exclude_from_weight_decay=None,
               include_in_weight_decay=["r_s_bias", "r_r_bias", "r_w_bias"],
               name="AdamWeightDecayOptimizer"):
    """Constructs a AdamWeightDecayOptimizer."""
    super(AdamWeightDecayOptimizer, self).__init__(False, name)

    self.learning_rate = learning_rate
    self.weight_decay_rate = weight_decay_rate
    self.beta_1 = beta_1
    self.beta_2 = beta_2
    self.epsilon = epsilon
    self.exclude_from_weight_decay = exclude_from_weight_decay
    self.include_in_weight_decay = include_in_weight_decay
def __init__ ( self , learning_rate , weight_decay_rate = 0.0 , beta_1 = 0.9 , beta_2 = 0.999 , epsilon = 1e-6 , exclude_from_weight_decay = None , include_in_weight_decay = [ "r_s_bias" , "r_r_bias" , "r_w_bias" ] , name = "AdamWeightDecayOptimizer" ) : super ( AdamWeightDecayOptimizer , self ) . __init__ ( False , name ) self . learning_rate = learning_rate self . weight_decay_rate = weight_decay_rate self . beta_1 = beta_1 self . beta_2 = beta_2 self . epsilon = epsilon self . exclude_from_weight_decay = exclude_from_weight_decay self . include_in_weight_decay = include_in_weight_decay