Question about Diarization inference
Hi guys

I have couple of questions about Diarization inference script

1. https://github.com/NVIDIA/NeMo/blob/f964e1c17c3922d6f35b5e453aa712f2be153e6d/nemo/collections/asr/parts/utils/nmesc_clustering.py#L723 

Here, we are trying to marge clustering outputs together using ```torch.mode```.  But it seems wrong, because at each trial the output class indices are different. So majority voting will not produce any benefits. Can you explain how it works? 


https://github.com/NVIDIA/NeMo/blob/f964e1c17c3922d6f35b5e453aa712f2be153e6d/nemo/collections/asr/parts/utils/nmesc_clustering.py#L895
2. Why are you making graph fully connected after binarization? Are there any corner cases in which fully connected graph is necessary? 


Thanks