How to get the intermediate features from the pre-trained checkpoint
Hi @titu1994, @VahidooX, thank you for your hard work.

I am trying out an experiment for the knowledge distillation task by utilizing the official pre-trained checkpoint ([stt_en_conformer_ctc_large_ls](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/nemo/models/stt_en_conformer_ctc_large_ls)) for the teacher model.

I would like to extract some intermediate features from this pre-trained teacher model (i.e., the self-attention layers in the conformer blocks), but all the intermediate layers in `ConformerEncoder` module seem to be overwritten with the variable `audio_signal`.

Is there a way to get these intermediate layers from the pre-trained checkpoint you provide?
I'd be grateful if you could provide some tutorials or tips.
Thank you.