numpy log normalization and log softmax implementation

log_softmax.py

import numpy as np

def log_softmax(x):
    e_x = np.exp(x - np.max(x))
    return np.log(e_x / e_x.sum())

def lognormalize(x):
    a = np.logaddexp.reduce(x)
    return np.exp(x - a)
    
scores = [3.0, 1.0, 0.2]
sm = log_softmax(scores)
print(sm)