python - numpy.random.multinomial bad outputs? -


I have this function: 

  import as np def unhot (vec) Do: "" "takes one warm vector and emphasizes related integer" np.sum "(vec) == 1 # This statement should not be unsuccessful, but it did ... return list (vec) .index (1)   
 that I call the call output:  
  numpy.random.multinomial (1, coe)   
 And I got an error at some point when I ran it. How is this possible? Numpy.random.multinomial's output is not guaranteed to be a hot-vector?  
 Then I deleted the claim error, and now I have:  
  ValueError: 1 is not in the list   
 I'm getting some special print, or is it just broken?   
 
 
 OK, this is a problem, and I should have realized, because I have encountered it earlier  
  np.random.multinomial (1, a ([0., 0., np. Nn, 0.])   
 returns  
  array ([0, 0, - 9223372036854775807,0])   
 I was using an unstable softmax implementation that was given to Nens. I was trying to make sure that I had a symmetrical & lt; = 1 in the parameters passed on the polynomial But I did it like this:  
  coe = softmax (coeffs) while np.sum (coe) & gt; 1-1e-9: coe / = (1 + 1e-5)   
 and with the Nyan of it, whenever the statement begins, I think.

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