my group leader assigns the task to reduce the compute cost of mobileNetV2, initially did kernel-size refactoring. I thought to use OFA to check what are the possible modification that can be done. OFA doesn't come with mbv2 by default.
can we run custom model on OFA, to get the model which is more efficient on specific dataset?
Thank you.
According to the information provided on OFA github(https://github.com/mit-han-lab/once-for-all/tree/master), you can use your own model, but you need to make sure that the way you construct your model conforms to the OFA reading method.
I would recommend modifying it through MobileNetV3(https://github.com/mit-han-lab/once-for-all/blob/master/ofa/imagenet_classification/networks/mobilenet_v3.py) in OFA github.
Please refer to it. Thank you.