In [1]:

    

import numpy as np 
import matplotlib.pyplot as plt
%matplotlib inline


    

In [11]:

    

a = np.random.randn(10)
print (a)
softmax_a = np.exp(a)/(np.exp(a)).sum()


    

    




[-0.75012973 -0.18956858  1.51197011 -0.33174648 -0.2694382  -0.37770367
  0.62610047  1.21066731 -0.81823531  0.41159655]

In [12]:

    

plt.subplot(1, 2, 1)
plt.scatter(np.arange(0,len(a),1),a,color='red')
plt.subplot(1, 2, 2)
plt.scatter(np.arange(0,len(a),1),softmax_a,color='blue')
plt.show()


    

In [9]:

    

b = np.random.randn(100,2)
expb = np.exp(b)
softmax_b = expb/expb.sum(axis=1,keepdims=True)


    

In [10]:

    

softmax_b


    

    
Out[10]:





array([[ 0.35750486,  0.64249514],
       [ 0.19555827,  0.80444173],
       [ 0.53055452,  0.46944548],
       [ 0.7761232 ,  0.2238768 ],
       [ 0.21138047,  0.78861953],
       [ 0.63550496,  0.36449504],
       [ 0.68436883,  0.31563117],
       [ 0.15569814,  0.84430186],
       [ 0.80364596,  0.19635404],
       [ 0.3476126 ,  0.6523874 ],
       [ 0.65752491,  0.34247509],
       [ 0.61311472,  0.38688528],
       [ 0.16574904,  0.83425096],
       [ 0.3930068 ,  0.6069932 ],
       [ 0.59859201,  0.40140799],
       [ 0.50577143,  0.49422857],
       [ 0.89693007,  0.10306993],
       [ 0.52342696,  0.47657304],
       [ 0.42442864,  0.57557136],
       [ 0.36940257,  0.63059743],
       [ 0.28305826,  0.71694174],
       [ 0.72315451,  0.27684549],
       [ 0.89954178,  0.10045822],
       [ 0.75519784,  0.24480216],
       [ 0.26612509,  0.73387491],
       [ 0.80852512,  0.19147488],
       [ 0.68416325,  0.31583675],
       [ 0.03307317,  0.96692683],
       [ 0.21722068,  0.78277932],
       [ 0.91672443,  0.08327557],
       [ 0.70196835,  0.29803165],
       [ 0.68216145,  0.31783855],
       [ 0.20112925,  0.79887075],
       [ 0.28954934,  0.71045066],
       [ 0.31177354,  0.68822646],
       [ 0.82962645,  0.17037355],
       [ 0.47444812,  0.52555188],
       [ 0.26555047,  0.73444953],
       [ 0.70177587,  0.29822413],
       [ 0.81570155,  0.18429845],
       [ 0.63703838,  0.36296162],
       [ 0.37021558,  0.62978442],
       [ 0.8988664 ,  0.1011336 ],
       [ 0.1836353 ,  0.8163647 ],
       [ 0.8501772 ,  0.1498228 ],
       [ 0.3266048 ,  0.6733952 ],
       [ 0.82310144,  0.17689856],
       [ 0.8503917 ,  0.1496083 ],
       [ 0.39810817,  0.60189183],
       [ 0.90085117,  0.09914883],
       [ 0.07806474,  0.92193526],
       [ 0.29331349,  0.70668651],
       [ 0.11028056,  0.88971944],
       [ 0.31239047,  0.68760953],
       [ 0.66248275,  0.33751725],
       [ 0.53678111,  0.46321889],
       [ 0.97721598,  0.02278402],
       [ 0.51967683,  0.48032317],
       [ 0.73667322,  0.26332678],
       [ 0.22534681,  0.77465319],
       [ 0.6268907 ,  0.3731093 ],
       [ 0.43629279,  0.56370721],
       [ 0.66701673,  0.33298327],
       [ 0.83970087,  0.16029913],
       [ 0.84390822,  0.15609178],
       [ 0.68848223,  0.31151777],
       [ 0.71783503,  0.28216497],
       [ 0.44774958,  0.55225042],
       [ 0.52428795,  0.47571205],
       [ 0.42239925,  0.57760075],
       [ 0.40707987,  0.59292013],
       [ 0.26241217,  0.73758783],
       [ 0.75435635,  0.24564365],
       [ 0.76041059,  0.23958941],
       [ 0.1751494 ,  0.8248506 ],
       [ 0.2115111 ,  0.7884889 ],
       [ 0.33498929,  0.66501071],
       [ 0.5563039 ,  0.4436961 ],
       [ 0.5702084 ,  0.4297916 ],
       [ 0.81746059,  0.18253941],
       [ 0.73049817,  0.26950183],
       [ 0.82725613,  0.17274387],
       [ 0.2892864 ,  0.7107136 ],
       [ 0.08020346,  0.91979654],
       [ 0.53995019,  0.46004981],
       [ 0.76699566,  0.23300434],
       [ 0.21584237,  0.78415763],
       [ 0.7839562 ,  0.2160438 ],
       [ 0.26331428,  0.73668572],
       [ 0.06349098,  0.93650902],
       [ 0.37812357,  0.62187643],
       [ 0.467999  ,  0.532001  ],
       [ 0.75328223,  0.24671777],
       [ 0.60988451,  0.39011549],
       [ 0.17355685,  0.82644315],
       [ 0.32794276,  0.67205724],
       [ 0.62194676,  0.37805324],
       [ 0.56737758,  0.43262242],
       [ 0.13106675,  0.86893325],
       [ 0.13607513,  0.86392487]])

In [35]:

    

softmax_b.sum(axis=1)


    

    
Out[35]:





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

In [ ]: