import numpy as np
import math


def softmax(scores: list[float]) -> list[float]:
    length = len(scores)
    probabilities = []
    e = math.e
    sum1 = 0
    for i in range(length):
        sum1 += e**scores[i]
    for i in range(length):
        prob = (e**scores[i])/sum1
        probabilities.append(prob)
    return np.round(probabilities,4).tolist()

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