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'''
http://eli.thegreenplace.net/2016/the-softmax-function-and-its-derivative/
'''


    

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import numpy as np


    

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def softmax_overflow(x):
    exps = np.exp(x)
    return exps / np.sum(exps)


    

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softmax_overflow([1000, 2000, 5000])


    

    




C:\Users\shuhua\AppData\Local\Continuum\Anaconda3\envs\tensorflow\lib\site-packages\ipykernel\__main__.py:2: RuntimeWarning: overflow encountered in exp
  from ipykernel import kernelapp as app
C:\Users\shuhua\AppData\Local\Continuum\Anaconda3\envs\tensorflow\lib\site-packages\ipykernel\__main__.py:3: RuntimeWarning: invalid value encountered in true_divide
  app.launch_new_instance()






    
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array([ nan,  nan,  nan])

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def softmax(x):
    shiftx = x - np.max(x)
    exps = np.exp(shiftx)
    return exps / np.sum(exps)


    

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softmax([1000, 2000, 5000])


    

    
Out[13]:





array([ 0.,  0.,  1.])

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