They said the dataloaders are using random numbers and thus change the state of rng generators.
So if the validation data is not loaded by DataLoader but something iterable implemented by myself, the training loss (with only One training DataLoader) will be different from the model that the validation data is loaded by the DataLoader (Two DataLoader, one for training, another for validation)? If so, what is the insight behind such design?

  
      github.com/pytorch/pytorch
  
  
    
  
	  
  

  
    
      Data loader will affect the random mechanism even with fixed seed 3
    

    
      
        opened 
        
          
        
        Apr 21, 2020
      
      

        
          closed 
        
          
        
        Apr 21, 2020
      
        

      
        
          
          zhujiangang
        
      
    
  



  🐛 Bug
Data loader will affect the random mechanism even with fixed seed, which will make the code unable to reproduce the...