Differences in the Expected and the actual output in a network for Super Resolution

[Arbiter-glitch]

There is a considerable difference between the output and the expected output. Expected output is the output image received while passing the input image through the software model. I use latest FINN branch. I trained the network outside the Finn docker. Then exported the qonnx format to Finn. Most of the nodes are rtl while some are hls.
I have included the intermediate models and the build_dataflow_steps.py in the zip file as well as the output received through finn and the expected output. The notebook for running in Pynq is also included. I don't know whether I am doing anything wrong. Also, I took out the last mul node because it just divides by 255 to get the output between 0 and 1.
check.zip

[Update:]
It works with old layers of v9 but not latest branch of FINN with RTL layers. Since I want more throughput RTL layers are better. Hope this can be solved.