Softmax in Python

softmax.py

#! /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)

labels = [0, 0, 0, 0, 0.68, 0.32, 0, 0, 0, 0]

%timeit softmax = np.exp([element for element in labels]) / np.sum(np.exp([element for element in labels]))
The slowest run took 5.03 times longer than the fastest. This could mean that an intermediate result is being cached.
100000 loops, best of 3: 12.2 µs per loop

It can be simple one liner.

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