本文介绍了用numpy数组实现softmax函数的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！
问题描述
我当前的功能如下:
def soft_max(z):
t = np.exp(z)
a = np.exp(z) / np.sum(t, axis=1)
return a
但是我收到错误:ValueError: operands could not be broadcast together with shapes (20,10) (20,)，因为np.sum(t，axis = 1)不是标量.
However I get the error: ValueError: operands could not be broadcast together with shapes (20,10) (20,) since np.sum(t, axis=1) isn't a scalar.
我想拥有t / the sum of each row，但是我不知道该怎么做.
I want to have t / the sum of each row but I don't know how to do this.
推荐答案
从1.2.0版开始，scipy包含softmax作为特殊功能:
As of version 1.2.0, scipy includes softmax as a special function:
https://scipy.github.io/devdocs/genic /scipy.special.softmax.html
使用axis参数可以在行上运行它.
Use the axis argument do run it over rows.
from scipy.special import softmax
softmax(arr, axis=0)
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