variational_dropout.py 文件源码

def dkl_qp(log_alpha):
    k1, k2, k3 = 0.63576, 1.8732, 1.48695; C = -k1
    mdkl = k1 * tf.nn.sigmoid(k2 + k3 * log_alpha) - 0.5 * tf.log1p(tf.exp(-log_alpha)) + C
    return -tf.reduce_sum(mdkl)

# handy function to keep track of sparsity