add freeze, unfreeze methods with experimental tag#15729
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Signed-off-by: nithinraok <nithinrao.koluguri@gmail.com>
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/ok to test 1fc31e0 |
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/claude review |
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Signed-off-by: nithinraok <nithinrao.koluguri@gmail.com>
pzelasko
approved these changes
May 26, 2026
| x = x.transpose(1, 2) # (B, T, D) -> (B, D, T) | ||
| return x, length | ||
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| def freeze(self): |
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nitpick but maybe this should be either a mixin, or a standalone module ModelFreezer or free function freeze(module) / unfreeze(module, partial)? the logic seems quite generic, not sure if it should be included in class definition. this class could just do
def freeze(self):
return freeze(self)
def unfreeze(self, partial):
return unfreeze(self, partial=partial)
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Yeah actually, It is part of NeuralModule but since we not inheriting I added these methods separately for now.
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/ok to test e1f0bc4 |
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[🤖]: Hi @nithinraok 👋, We wanted to let you know that a CICD pipeline for this PR just finished successfully. So it might be time to merge this PR or get some approvals. |
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What does this PR do ?
Add
freeze()/unfreeze()methods to the ASR TransformerEncoder and mark the class as experimental.Collection: ASR
Changelog
freeze()method toTransformerEncoder: setsrequires_grad=Falseon all parameters and switches the module to eval mode.unfreeze(partial: bool = False)method toTransformerEncoder: sets requires_grad=Trueon all parameters; switches to train mode unless partial=True.TransformerEncoderwith@experimentalfromnemo.utils.decoratorsto signal API stability is not yet guaranteed.GitHub Actions CI
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