a744b600e94ae00fbec71ef493afdff48bc3816b,keras/layers/normalization.py,LRN2D,get_output,#LRN2D#Any#,97

Before Change

        input_sqr = T.sqr(X)
        extra_channels = T.alloc(0., b, ch + 2*half_n, r, c)
        // TODO: use concatenate instead
        input_sqr = T.set_subtensor(extra_channels[:, half_n:half_n+ch, :, :], input_sqr)
        scale = self.k
        for i in range(self.n):
            scale += self.alpha * input_sqr[:, i:i+ch, :, :]
        scale = scale ** self.beta

After Change

        half_n = self.n // 2
        input_sqr = K.square(X)
        extra_channels = K.zeros((b, ch + 2*half_n, r, c))
        input_sqr = K.concatenate([extra_channels[:, :half_n, :, :],
                                   input_sqr,
                                   extra_channels[:, half_n+ch:, :, :]],
                                  axis=1)
        scale = self.k
        for i in range(self.n):
            scale += self.alpha * input_sqr[:, i:i+ch, :, :]
        scale = scale ** self.beta

Instances