I have a question as the name suggests. Previously I used torch for training a small network with 2 LSTM layer each with 16 memory cells, and the time needed to go through all of my training data once is about 1 to 2 hours on GPU.
Now I switched to Pytorch. And training the same network on the same training data on the same GPU for one epoch only takes about 7 mins. So I was wondering what kinds of changes have you made in Pytorch that make it so much faster than Torch7 in this particular case with LSTM?
I have tested my model trained in Pytorch and it works sensibly. So I think I probably implemented my code correctly, so there is no silly mistake in my code.