HaitaoWen
commented
2 hours ago Hi @1259666087, We first use the following function to warp the teacher model into a multi-branch structure https://github.com/HaitaoWen/CLearning/blob/ce0789a40bda9e566a1e0432d3ac320937ca48f0/scheme/replay/mtd/mtd.py#L779 then find appropriate multiple teachers in the procedure of class balanced finetuning https://github.com/HaitaoWen/CLearning/blob/ce0789a40bda9e566a1e0432d3ac320937ca48f0/scheme/replay/mtd/mtd.py#L979 then save this model in the 'memory' variable https://github.com/HaitaoWen/CLearning/blob/ce0789a40bda9e566a1e0432d3ac320937ca48f0/scheme/replay/mtd/mtd.py#L112 and use the model in the 'memory' for distillation during the new task. https://github.com/HaitaoWen/CLearning/blob/ce0789a40bda9e566a1e0432d3ac320937ca48f0/scheme/replay/mtd/mtd.py#L238
Hello, could you please explain how your multi-teacher model method conducts experiments with PODNet and AFC? It seems that this is not clearly indicated in your code.