From what I understand this a more summarized answer:

Contiguous is the term used to indicate that the memory layout of a tensor does not align with its advertised meta-data or shape information.

In my opinion the word contiguous is a confusing/misleading term since in normal contexts it means when memory is not spread around in disconnected blocks (i.e. its “contiguous/connected/continuous”).
Some operations might need this contiguous property for some reason (most likely efficiency).
Resource:

  
      stackoverflow.com
  
  
      
    
  

  PyTorch - contiguous() 86



  neural-network, deep-learning, lstm, pytorch



  asked by
  
  
    MBT
  
  on 09:30PM - 21 Feb 18 UTC