Well, I am just want to ask how pytorch shuffle the data set. And this question probably is a very silly question.
I mean I set shuffle as True in data loader. And I just wonder how this function influence the data set. For example, I put the whole MNIST data set which have 60000 data into the data loader and set shuffle as true. Does it possible that if I only use 30000 to train the model but the model cannot identify number 6 to 9 because I shuffled the data loader and all the sample of number 6 to 9 were shuffled into the last 30000 which I did not use?
I mean does it possible that the shuffle operation will lead to models that use partial training sets are not able to get all features of the whole data set?