math.py 文件源码

def log_softmax(vec):
    """Robust version of the log of softmax values

    Args:
        vec: vector of log-odds

    Returns:
        A vector whose exponential sums to one with lgo of softmax values log(exp(x_k)/sum_i (exp(x_i)))

    Examples:
        >>> print(log_softmax(np.array([1.0, 1.0, 1.0, 1.0])))
        [-1.38629436 -1.38629436 -1.38629436 -1.38629436]
        >>> print(log_softmax(np.array([-1.0, -1.0, -1.0, -1.0])))
        [-1.38629436 -1.38629436 -1.38629436 -1.38629436]
        >>> print(log_softmax(np.array([1.0, 0.0, -1.0, 1.1])))
        [-0.9587315 -1.9587315 -2.9587315 -0.8587315]

    """
    return vec - logsumexp(vec)