Replies: 2 comments 1 reply
-
Did you manage to find any way around this? I'm looking into implementing something similar to what you described. |
Beta Was this translation helpful? Give feedback.
1 reply
-
Oh, sure. I'll look into it one of these days.
…On Fri, Dec 30, 2022, 11:30 PM Lyle Hopkins ***@***.***> wrote:
I ended up working on some separate things so never go around to
implementing. However I may be circling back to it this coming year. Let me
know how you get on.
—
Reply to this email directly, view it on GitHub
<#104 (reply in thread)>,
or unsubscribe
<https://github.com/notifications/unsubscribe-auth/AH5CXQYGAQ2STRRFN4L4H73WP5PBZANCNFSM5KRK3RYQ>
.
You are receiving this because you commented.Message ID:
<TorchEnsemble-Community/Ensemble-Pytorch/repo-discussions/104/comments/4558180
@github.com>
|
Beta Was this translation helpful? Give feedback.
0 replies
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
-
Hello,
I'm looking to build an ensemble of different PyTorch models. I can across your module, and from what I can tell (without running any code) the ensembles are based on the same NN model design? The ensembles are also tied to the training process (in that, to make predictions you start with untrained models that must go through the training process).
I was initially planning on building an ensemble from some pre-trained models I have which are based on different NN designs. This was to see what results I would get from different combinations of the models.
I'm assuming that if I look through the code I could probably find a way of using Ensemble-Pytorch to achieve what I want, rather than rolling my own code.
Maybe someone could offer some advice?
Beta Was this translation helpful? Give feedback.
All reactions