layers.py 文件源码

def __init__(self, incoming, RMAX,DMAX,axes='auto', epsilon=1e-4, alpha=0.1,
                 beta=lasagne.init.Constant(0), gamma=lasagne.init.Constant(1),
                 mean=lasagne.init.Constant(0), inv_std=lasagne.init.Constant(1), **kwargs):
        super(BatchReNormDNNLayer, self).__init__(
                incoming, axes, epsilon, alpha, beta, gamma, mean, inv_std,
                **kwargs)
        all_but_second_axis = (0,) + tuple(range(2, len(self.input_shape)))

        self.RMAX,self.DMAX = RMAX,DMAX

        if self.axes not in ((0,), all_but_second_axis):
            raise ValueError("BatchNormDNNLayer only supports normalization "
                             "across the first axis, or across all but the "
                             "second axis, got axes=%r" % (axes,))