(self, stochastic_round=False, learning_rate=0.01, epsilon=1e-6,
                 gradient_clip_norm=None, gradient_clip_value=None,
                 param_clip_value=None, name=None)
Class constructor.

        Arguments:
            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 multiplication coefficent of updates
            epsilon (float): smoothing epsilon to avoid divide by zeros
            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.
        Notes:
            Only constant learning rate is supported currently.
Class constructor.
Class constructor .
def __init__(self, stochastic_round=False, learning_rate=0.01, epsilon=1e-6,
                 gradient_clip_norm=None, gradient_clip_value=None,
                 param_clip_value=None, name=None):
        """
        Class constructor.

        Arguments:
            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 multiplication coefficent of updates
            epsilon (float): smoothing epsilon to avoid divide by zeros
            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.
        Notes:
            Only constant learning rate is supported currently.
        """
        super(Adagrad, self).__init__(name=name)
        self.state_list = None
        self.epsilon = epsilon
        self.learning_rate = learning_rate
        self.gradient_clip_norm = gradient_clip_norm
        self.gradient_clip_value = gradient_clip_value
        self.param_clip_value = param_clip_value
        self.stochastic_round = stochastic_round
def __init__ ( self , stochastic_round = False , learning_rate = 0.01 , epsilon = 1e-6 , gradient_clip_norm = None , gradient_clip_value = None , param_clip_value = None , name = None ) : super ( Adagrad , self ) . __init__ ( name = name ) self . state_list = None self . epsilon = epsilon self . learning_rate = learning_rate self . gradient_clip_norm = gradient_clip_norm self . gradient_clip_value = gradient_clip_value self . param_clip_value = param_clip_value self . stochastic_round = stochastic_round