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@stober
Created March 1, 2012 03:05
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Softmax in Python
#! /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)
@rajans
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rajans commented Mar 21, 2018

It can be simple one liner.

def softmax(x):
return np.exp(x)/np.sum(np.exp(x),axis=0)

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