What is the right way of handling this now that Tensor also tracks history?
I migrated to PyTorch 0.4 (e.g., removed some code wrapping tensors into variables), and now the training loop is getting progressily slower. I’m not sure where this problem is coming from. Is there a way of drawing the computational graphs that are currently being tracked by Pytorch? These issues seem hard to debug.