So far it seems like reaching consensus proved to be difficult as both datasets and tasks they’re used for vary a lot.
IMO a good starting point would be to first collect a bunch of contributed datasets someplace, possibly torch hub as you’ve suggested, to get a feel of how they’re used. After that it would be easier to create a robust abstraction.
Because now every research repo has it’s own Datasets and custom DataLoaders. These are often times a pain to work with when you try to combine datasets from several different repos.

  
      github.com/pytorch/vision
  
  
    
  
	  
  

  
    
      Standardization of the datasets 1
    

    
      
        opened 
        
          
        
        Jul 3, 2019
      
      


      
        
          
          pmeier
        
      
    
  



  This is a discussion issue which was kicked of by #1067. Some PRs that contain ideas are #1015 and #1025. I...



    module: datasets
    needs discussion