We read every piece of feedback, and take your input very seriously.
To see all available qualifiers, see our documentation.
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Thank you for opening the source code of this briliant work!
The values of Number of Parameters and FLOPs are shown in the paper.
I'm curious how do you calculate these two values? Which tools/packages do you use for calculation?
Best, Iris
The text was updated successfully, but these errors were encountered:
Hello @iris0329!
For the Number of Parameters we used the built-in functions of Pytorch like so: sum(p.numel() for p in model.parameters() if p.requires_grad)
sum(p.numel() for p in model.parameters() if p.requires_grad)
For the FLOPs we used this package: https://github.com/sovrasov/flops-counter.pytorch
Best, Tiago
Sorry, something went wrong.
@TiagoCortinhal Thank you for your generous reply!
No branches or pull requests
Thank you for opening the source code of this briliant work!
The values of Number of Parameters and FLOPs are shown in the paper.
I'm curious how do you calculate these two values?
Which tools/packages do you use for calculation?
Best,
Iris
The text was updated successfully, but these errors were encountered: