(self, stochastic_round=False, learning_rate=0.001, beta_1=0.9, beta_2=0.999,
                 epsilon=1e-8, gradient_clip_norm=None, gradient_clip_value=None,
                 param_clip_value=None, name="adam")
Class constructor.

        Args:
            stochastic_round (bool): Set this to True for stochastic rounding.
                                     If False rounding will be to nearest.
                                     If True will perform stochastic rounding using default width.
                                     Only affects the gpu backend.
            learning_rate (float): the multiplicative coefficient of updates
            beta_1 (float): Adam parameter beta1
            beta_2 (float): Adam parameter beta2
            epsilon (float): numerical stability parameter
            gradient_clip_norm (float, optional): Target gradient norm.
                                                  Defaults to None.
            gradient_clip_value (float, optional): Value to element-wise clip gradients.
                                                   Defaults to None.
            param_clip_value (float, optional): Value to element-wise clip parameters.
                                                Defaults to None.
Class constructor.
Class constructor .
def __init__(self, stochastic_round=False, learning_rate=0.001, beta_1=0.9, beta_2=0.999,
                 epsilon=1e-8, gradient_clip_norm=None, gradient_clip_value=None,
                 param_clip_value=None, name="adam"):
        """
        Class constructor.

        Args:
            stochastic_round (bool): Set this to True for stochastic rounding.
                                     If False rounding will be to nearest.
                                     If True will perform stochastic rounding using default width.
                                     Only affects the gpu backend.
            learning_rate (float): the multiplicative coefficient of updates
            beta_1 (float): Adam parameter beta1
            beta_2 (float): Adam parameter beta2
            epsilon (float): numerical stability parameter
            gradient_clip_norm (float, optional): Target gradient norm.
                                                  Defaults to None.
            gradient_clip_value (float, optional): Value to element-wise clip gradients.
                                                   Defaults to None.
            param_clip_value (float, optional): Value to element-wise clip parameters.
                                                Defaults to None.
        """
        super(Adam, self).__init__(name=name)
        self.beta_1 = beta_1
        self.beta_2 = beta_2
        self.epsilon = epsilon
        self.learning_rate = learning_rate
        self.stochastic_round = stochastic_round
        self.gradient_clip_norm = gradient_clip_norm
        self.gradient_clip_value = gradient_clip_value
        self.param_clip_value = param_clip_value
        self.t = 0
def __init__ ( self , stochastic_round = False , learning_rate = 0.001 , beta_1 = 0.9 , beta_2 = 0.999 , epsilon = 1e-8 , gradient_clip_norm = None , gradient_clip_value = None , param_clip_value = None , name = "adam" ) : super ( Adam , self ) . __init__ ( name = name ) self . beta_1 = beta_1 self . beta_2 = beta_2 self . epsilon = epsilon self . learning_rate = learning_rate self . stochastic_round = stochastic_round self . gradient_clip_norm = gradient_clip_norm self . gradient_clip_value = gradient_clip_value self . param_clip_value = param_clip_value self . t = 0