You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Hi, from the paper I thought that the most important parameters are shared across different experts. However, in the code I did n't see how to ensure the parameters are the same in the training process. I see in utils.py, expert_list[i].fc1.weight.data = fc1_weight_data[idx, :].clone(), but the variable created by clone will not be the same as the old one.
I also do experiments to check my assumption. After several steps, the parameters in experts are no longer the same.
Can you give more highlights on that? Thanks.
The text was updated successfully, but these errors were encountered:
Hi, from the paper I thought that the most important parameters are shared across different experts. However, in the code I did n't see how to ensure the parameters are the same in the training process. I see in
utils.py
,expert_list[i].fc1.weight.data = fc1_weight_data[idx, :].clone()
, but the variable created by clone will not be the same as the old one.I also do experiments to check my assumption. After several steps, the parameters in experts are no longer the same.
Can you give more highlights on that? Thanks.
The text was updated successfully, but these errors were encountered: