softmax函数实现
import numpy as npa = 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_areturn 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_areturn y
a = np.array([0.3,2.9,0.4])
y = softmax_2(a)
print(y)