import numpy as np
import math


def softmax(scores: list[float]) -> list[float]:
    exp_scores = np.exp(scores)
    probabilities = exp_scores / np.sum(exp_scores)
    return list(np.round(probabilities,4))

if __name__ == "__main__":
    scores = np.array(eval(input()))
    print(softmax(scores))

Numpy实现

Softmax = \frac{e^x}{\sum_{i = 1}^n e^i}