trueshadow.py 文件源码

def normal_ccdf(x, mu, sigma2):
    """Normal CCDF"""
    # Check for degenerate distributions when sigma2 == 0
    # if x >= mu, n = 0
    # if x < mu, n = 1
    # sigma2_le_0 = tf.less_equal(sigma2, 0.)
    # x_gte_mu = tf.greater_equal(x, mu)
    # x_lt_mu = tf.less(x, mu)

    # Never divide by zero, instead the logic below handles degenerate distribution cases
    # sigma2 = tf.cond(sigma2_le_0, lambda: tf.ones_like(sigma2), lambda: sigma2)

    p = (1. - 0.5 * (1. + tf.erf((x - mu) / tf.sqrt(2. * sigma2))))
    # p = tf.cond(tf.logical_and(sigma2_le_0, x_gte_mu), lambda: tf.zeros_like(p), lambda: p)
    # p = tf.cond(tf.logical_and(sigma2_le_0, x_lt_mu), lambda: tf.ones_like(p), lambda: p)
    return p