[question] computation of val_wer when validation_ds contains multiple manifest files
It seems that if one uses multiple manifest files for validation_ds the `val_wer` used in `checkpoint_callback` is based on the first manifest file, or computed as the average over all manifest files. This has an obvious influence on which checkpoints are retained `save_top_k`. Is this intended by design? 

If not; having two manifests, one small and one big will give an unfairly large influence to the small manifest in case of averaging, or exclude one if based on manifest with index 0. I believe the correct approach would be to do a division between the sum of numerators and sum of denominators over individual manifests (hence the same result if the two manifests were merged into one) as mentioned in https://github.com/NVIDIA/NeMo/blob/2aa68822bbfb8e7e8c221817b66de28928d6443b/nemo/collections/asr/metrics/wer.py#L75, but I do not see this happening. 

Browsing through code I can see https://github.com/NVIDIA/NeMo/blob/2aa68822bbfb8e7e8c221817b66de28928d6443b/nemo/collections/asr/models/asr_model.py#L40-L45, but my Tensorboard apart from `val_wer` contains also `<manifestfile>_val_wer` and `val_wer==<manifestfile#0>_val_wer`. This value is also used for checkpoints. I am unable to find where in the code the individual `<manifestfile>_val_wer` are appended.