distributions.py 文件源码

def discretized_logistic(mean, logscale, binsize=1 / 256.0, sample=None):
    scale = tf.exp(logscale)
    sample = (tf.floor(sample / binsize) * binsize - mean) / scale
    logp = tf.log(tf.sigmoid(sample + binsize / scale) - tf.sigmoid(sample) + 1e-7)
    return tf.reduce_sum(logp, [1, 2, 3])