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truncated normal initializer #38

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ruotianluo opened this issue Nov 19, 2018 · 2 comments
Closed

truncated normal initializer #38

ruotianluo opened this issue Nov 19, 2018 · 2 comments

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@ruotianluo
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I have a reasonable truncated normal approximation. (Actually that is what tf does).
https://discuss.pytorch.org/t/implementing-truncated-normal-initializer/4778/16?u=ruotianluo

@thomwolf
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thomwolf commented Nov 20, 2018

We could try that. Not sure how important it is though. Did you try it?

@thomwolf
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Ok I think we will stick to the normal_initializer for now. Thanks for indicating this option!

stevezheng23 added a commit to stevezheng23/transformers that referenced this issue Mar 24, 2020
add coqa runner as basic mt-coqa runner
xloem pushed a commit to xloem/transformers that referenced this issue Apr 9, 2023
* Update trainer and model flows to accommodate sparseml

Disable FP16 on QAT start (huggingface#12)

* Override LRScheduler when using LRModifiers

* Disable FP16 on QAT start

* keep wrapped scaler object for training after disabling

Using QATMatMul in DistilBERT model class (huggingface#41)

Removed double quantization of output of context layer. (huggingface#45)

Fix DataParallel validation forward signatures (huggingface#47)

* Fix: DataParallel validation forward signatures

* Update: generalize forward_fn selection

Best model after epoch (huggingface#46)

fix sclaer check for non fp16 mode in trainer (huggingface#38)

Mobilebert QAT (huggingface#55)

* Remove duplicate quantization of vocabulary.

enable a QATWrapper for non-parameterized matmuls in BERT self attention (huggingface#9)

* Utils and auxillary changes

update Zoo stub loading for SparseZoo 1.1 refactor (huggingface#54)

add flag to signal NM integration is active (huggingface#32)

Add recipe_name to file names

* Fix errors introduced in manual cherry-pick upgrade

Co-authored-by: Benjamin Fineran <bfineran@users.noreply.github.com>
jameshennessytempus pushed a commit to jameshennessytempus/transformers that referenced this issue Jun 1, 2023
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