Inquiry on Online Class-IL scenario about online-continual-learning HOT 1 CLOSED

Sorry for the delayed reply. You are right. The size of the final FC layer should be NxK, where N is the output size from the previous layer and K is the number of classes the model has met. K will increase when the model meets more classes. In this repo, we simplify this process by setting the size of the FC layer to NxM, where M is the total number of classes in the dataset. This simplification is based on empirical observation. Let W with size NxM be the weights of the FC layer. When the model processes the first K classes, W[:, :K] part is being updated and W[:, (M-K):] part almost remains intact. Therefore, we simply assume the number of classes is known beforehand.

If you want to change the size of the FC layer dynamically, you can simply initialize W with size NxK and add new weights to W whenever the model meets a new task.

Hope I have answered your question, and please don't hesitate to reach out for further questions. Also, if you use this repo in your research, please consider citing use.

from online-continual-learning.