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This repository was archived by the owner on May 20, 2026. It is now read-only.
If my model's structure differs slightly between training and inference phases, is it still suitable to use ONNX Runtime Training? For instance, during training, my model has two outputs ( D_q and D_q_), but during inference, it only has one output (D_q).
In this case, can I finish training on the device, export the inference model, and then remove D_q_ and any unused nodes from the inference model?
Hello,
If my model's structure differs slightly between training and inference phases, is it still suitable to use ONNX Runtime Training? For instance, during training, my model has two outputs ( D_q and D_q_), but during inference, it only has one output (D_q).
In this case, can I finish training on the device, export the inference model, and then remove D_q_ and any unused nodes from the inference model?
Thanks!
Here is a sample image.

(Model with two output)
(Model Only One output)