Training on your own dataset with bilinear downscaling

[Sazoji]

I already have my own 4x dataset to compare model following the REDS structure (and this is using the basicSR VSR loader, so dataloading shouldn't be an issue unless I need to flatten the folders to pretrain SISR), but for the pretraining, I don't know if MFDN needs to pretrain separately before starting a large training session.
Regarding the TOFLOW and EDVR backed models, which networks should be retrained with the pretraining configs when fitting for a new downscale, patch size(depending on the arch), and subject (low noise, computer generated video)?
Secondly, are there other architectures (like RRDB) in this repo that could be used for VSR training? AFAK dcn/EDVR does not pair well with fp16 and AMP training for consumer cards.
Blind VSR seems far more efficient than SOFVSR(which requires deblurring with HINet for satisfactory results) if it can keep flicker low while also upscaling.