I’m working on a project which requires me to rewrite the implementation of backpropagation, so I’d like to modify the current implementation of pytorch backprop. I took a look at the source code and found that it uses:
Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass...
However I’m stuck here as I can’t seem to find where this function is defined. Anyone know where the code for backprop is?
Also, is this recommended? Would modifying backprop cause a lot of issues for regular gpu training (doesn’t need to work for distributed cases)?