BatchNorm don't work as expected #2650
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laggui
wangjiawen2013
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Answered by
laggui
Jan 2, 2025
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The result is not wrong 🙂 The difference lies in the training vs inference computation for a batchnorm module. If you use With burn you have to be explicit when using autodiff. In pytorch it's kind of the opposite, it will track the gradients and keep the autodiff graph by default unless you use This is also explained in the autodiff section. |
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The result is not wrong 🙂
The difference lies in the training vs inference computation for a batchnorm module. If you use
m.eval()
instead for the pytorch module you should get equivalent results.With burn you have to be explicit when using autodiff. In pytorch it's kind of the opposite, it will track the gradients and keep the autodiff graph by default unless you use
with torch.no_grad()
context.This is also explained in the autodiff section.