Hi,
Actually, this is not a skipped bug or something like that. Numpy also has same semantic and it is due to precision of floating point numbers.

  
      stackoverflow.com
  
  
      
    
  

  Float precision breakdown in python/numpy when adding numbers



  python, numpy, precision



  
  answered by
  
    mgilson
  
  on 02:10PM - 11 Jan 13 UTC


  
  
    
    
  
  


You can find some information about dtypes wrt to this post by using
i = torch.finfo(torch.float32)
i.eps  

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