@SimonW , Thanks. If we run the model in a server, then I found pytorch based programs are easily killed due to out of memory during training (I can run the code at the beginning, while it got killed after several hundreds iterations). So I’d like to occupy enough memory at the beginning, as tf based programs rarely get killed because of memory issue during training…