questions regarding multiplicative constant for flow & correlation max_displacement in multi-levels

[InnovArul]

I am trying to understand the code and the design decisions made while designing this model. In this regard, I have two doubts as below:

1. The correlation max_displacement is kept constant at 4 for all the levels of feature maps. https://github.com/anuragranj/back2future.pytorch/blob/a3b619a9eb11c91866160565a8593dda690c2da9/back2future.py#L73

In your opinion, do you think we have to have different max_displacement for different levels of the network?

2. I would like to get an intuition regarding the multiplication factors used for flow: 0.625 for level-6 flow https://github.com/anuragranj/back2future.pytorch/blob/a3b619a9eb11c91866160565a8593dda690c2da9/back2future.py#L178-L179

1.25 for level-5 flow https://github.com/anuragranj/back2future.pytorch/blob/a3b619a9eb11c91866160565a8593dda690c2da9/back2future.py#L196-L197

2.5 for level-4 flow https://github.com/anuragranj/back2future.pytorch/blob/a3b619a9eb11c91866160565a8593dda690c2da9/back2future.py#L213-L214

5 for level-3 flow https://github.com/anuragranj/back2future.pytorch/blob/a3b619a9eb11c91866160565a8593dda690c2da9/back2future.py#L230-L231

Could you please let me know why do we need these multiplicative factors? I am sorry if this is a basic question to be asked. As the network is learnable, isn't it possible that the network learns this multiplicative factor automatically as well?

Thanks in advance!