masahi commented on issue #13296: URL: https://github.com/apache/tvm/issues/13296#issuecomment-1306127542
This is a common problem when using TVM on Windows. Can you identify which pass is causing the stack overflow? I think the stack overflow is coming from https://github.com/apache/tvm/blob/main/src/ir/transform.cc#L453, where different relay and TIR passes are applied. So you can add debug statements before / after this line to identify what pass is running when the stack overflow happens. The name of a pass can be printed by `LOG(INFO) << pass_info->name`. > Would be good to understand the kind of tools /process to debug such/similar issues For this one I did a very dumb thing: I knew that outputs were correct up to some point in the model. Starting from there, I repeated modifying `torchvision/models/detection/ssd.py` and gradually add more pytorch operations until the output became different. I noticed that the lines https://github.com/pytorch/vision/blob/main/torchvision/models/detection/ssd.py#L433-L435 were converted incorrectly - indexing by mask results in a dynamic shape while the converted Relay model didn't have any dynamism around there. -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
