learning_rule.py 文件源码

def __init__(self,
                 init_momentum=0.9,
                 averaging_coeff=0.99,
                 stabilizer=1e-4,
                 update_param_norm_ratio=0.003,
                 gradient_clipping=None):
        init_momentum = float(init_momentum)
        assert init_momentum >= 0.
        assert init_momentum <= 1.
        averaging_coeff = float(averaging_coeff)
        assert averaging_coeff >= 0.
        assert averaging_coeff <= 1.
        stabilizer = float(stabilizer)
        assert stabilizer >= 0.

        self.__dict__.update(locals())
        del self.self
        self.momentum = sharedX(self.init_momentum)
        self.update_param_norm_ratio = update_param_norm_ratio

        self.gradient_clipping = gradient_clipping
        if gradient_clipping is not None:
            self.gradient_clipping = np.cast[config.floatX](gradient_clipping)