@zzmig Any update on this?
I am also working on this issue: loading 2 models at once (with Module() class) and running forward pass in parallel on different devices with the same data batch, rather than running in sequence, for better performance with overlapping. I did some searching but didn't find any solution. This architecture should be common in knowledge distillation projects, but they all implement it in sequence. I plan to try Python's `multiprocessing`. --- [Visit Topic](https://discuss.mxnet.io/t/how-to-group-two-models-together-as-one/6014/3) or reply to this email to respond. You are receiving this because you enabled mailing list mode. To unsubscribe from these emails, [click here](https://discuss.mxnet.io/email/unsubscribe/d177d2e14e359ec3c11f25e91495d43fdce5f638f536765d1f408e023e9b7831).
