深度学习入门 （4）softmax函数的实现

softmax函数实现

import numpy as np

a = np.array([0.3,2.9,4.0])
exp_a = np.exp(a)
print(exp_a)

sum_exp_a = np.sum(exp_a)
print(sum_exp_a)

y = exp_a / sum_exp_a
print(y)

def softmax(a):
    exp_a = np.exp(a)
    sum_exp_a = np.sum(exp_a)
    y = exp_a / sum_exp_a
    return y

a = np.array([1010,1000,990])
# np.exp(a)
c = np.max(a)
a-c

y=np.exp(a-c)/np.sum(np.exp(a-c))

def softmax_2(a):
    c = np.max(a)
    exp_a = np.exp(a-c)
    sum_exp_a = np.sum(exp_a)
    y = exp_a / sum_exp_a
    
    return y
a = np.array([0.3,2.9,0.4])
y = softmax_2(a)
print(y)