AxBy-ViT

AxBy-ViT: Reconfigurable Approximate Computation Bypass for Vision Transformers

Required Python Packages

• pytorch
• pytorch-pretrained-vit
• bitstring
• PIL
• numpy

To run AxBy-ViT

1. Install required packages.
2. Prepare ImageNet dataset and put the inference set at ./val_imagenet. Each class must have its individual directories matching the synset names (as indicated in the python script)
3. Initialize your GPU. By default GPU 0 is used.
4. Configure approximate bypass settings by changing the argument of axby_config()

To-do

1. Refraction.

• The current code repo is actually from a Jupyter notebook therefore requires quite refraction to make it more accessible.

3. Directly manipulating on original transformer object rather than defining custom classes.

• Currently using new classes inherited from the original transformer class for legacy designing issues however this can be avoided since pytorch already provides interface.