why fix all parameters except self attention parameters? about openlongtailrecognition-oltr

[zhmiao]

Hello @RainbowShirlley , thanks for asking and sorry for the late reply. The reason why we did not fix self attention is that this module is not trained in the first stage. It is totally random in the beginning of the second stage. We will have to train it during the second stage. Does that make sense?

[valencebond]

hi @RainbowShirlley @zhmiao , according to stage_2_meta_embedding.py, feature model params are not fixed, just learning with a samll learning rate.

[zhmiao]

@RainbowShirlley Yes, but for Places experiments, the backbone features are fixed in the second stage, because of the limitation of computational resource.

[zhmiao]

As it has been over two months, I will close this issue for now. If you have any more questions, you are welcome to reopen it. Thanks.