Thank you for your comments!
So there are two parts: - What do we represent in Relay, - what will be the function in the runtime. I guess I'm reading agreement here that TorchScript functions are a reasonably good fit for the runtime. If we determine this function during the (currently trivial) byoc phase, this would mean that we want to change the representation in relay to be at the op level (I guess). For this I need to do more figuring out how to best represent an arbitrary op in PyTorch, probably symbol (=name) and signature plus non-tensor inputs in attributes. Does the variable number of args handling in type inference look reasonable to you? --- [Visit Topic](https://discuss.tvm.apache.org/t/pytorch-libtorch-torchscript-as-a-backend/9043/9) to respond. You are receiving this because you enabled mailing list mode. To unsubscribe from these emails, [click here](https://discuss.tvm.apache.org/email/unsubscribe/fc51b77e260709fcbcbf060c736f745c6abc3c4c008cad5b439e29b1b348ee50).
