题解 | Log Softmax函数的实现

import numpy as np

def log_softmax(scores: list) -> np.ndarray:
    score_max = max(scores)
    exp_sum = sum([np.exp(score-score_max) for score in scores])
    probs = [np.log(np.exp(socre-score_max)/exp_sum) for socre in scores]
    return np.array(probs)

if __name__ == "__main__":
    scores = eval(input())
    print(log_softmax(scores))