There’s too much going on in the initial post.  Start by comparing individual layers, not whole models. That will make things easier to untangle.
My first impression is that you’re not measuring the same thing. Do we know why in the PT model 90% of the GMac comes from the final ConvTrtanspose2d layer, but that’s not listed for tensorflow?
“MAC” is “multiply-add-calculations”. The Conv2 layers are 9 Gflops (TF) or ~4.5 GMac (PT). 2:1 is the exchange rate. So that part makes sense.