distributions.py 文件源码

def _chollogdet(L):
    """Log det of a cholesky, where L is (..., D, D)."""
    ldiag = pos(tf.matrix_diag_part(L))  # keep > 0, and no vanashing gradient
    logdet = 2. * tf.reduce_sum(tf.log(ldiag))
    return logdet