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March 1, 2012 03:05
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Softmax in Python
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#! /usr/bin/env python | |
""" | |
Author: Jeremy M. Stober | |
Program: SOFTMAX.PY | |
Date: Wednesday, February 29 2012 | |
Description: Simple softmax function. | |
""" | |
import numpy as np | |
npa = np.array | |
def softmax(w, t = 1.0): | |
e = np.exp(npa(w) / t) | |
dist = e / np.sum(e) | |
return dist | |
if __name__ == '__main__': | |
w = np.array([0.1,0.2]) | |
print softmax(w) | |
w = np.array([-0.1,0.2]) | |
print softmax(w) | |
w = np.array([0.9,-10]) | |
print softmax(w) |
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It can be simple one liner.
def softmax(x):
return np.exp(x)/np.sum(np.exp(x),axis=0)