LadderNetwork.py 文件源码

def skip_connect(self, input, layer_index):
        if ([] == self.noisy_z):
            raise ValueError('Error: noisy_z is an empty list, noisy_fprop must be run before skip_connect')

        MU = self.compute_mu(input, self.As[layer_index])
        V  = self.compute_v(input, self.As[layer_index])

        reconstruction = (self.noisy_z[-1] - MU) * V + MU

#        # Non trainable Batchnormalisation
#        mean = reconstruction.mean(0)
#        std  = reconstruction.std(0) + 1e-10
#
#        # Only batchnormalise for a batchsize > 1
#        mean = ifelse(T.gt(input.shape[0], 1), mean, T.zeros(mean.shape, dtype=mean.dtype))
#        std  = ifelse(T.gt(input.shape[0], 1), std, T.ones(std.shape, dtype=std.dtype))

#        reconstruction = (reconstruction - mean) / std
        self.tmp = reconstruction

        # To caluclate the reconstruction error later
        self.reconstructions.append(reconstruction)
        self.noisy_z = self.noisy_z[0:-1]

        return reconstruction