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layer_norm_and_dropout

Syntologyentry name in harvested coderead from the graph 2026-09-24

layer_norm_and_dropout appears in the code Syntology harvested for 6 papers, as 11 distinct code bodies found in 11 places (a place is one code body under one paper). At least one of them ran in 1 of the papers; 0 of the code bodies carry a behaviour fingerprint.

What this page is not. Routines are grouped here by the exact string of their function or class name. Nothing asserts that two samples named layer_norm_and_dropout do the same thing, share code, or are comparable; the name is a string, not an identity. Behaviour outputs (what a fingerprinted sample returned on the shared battery) are not in this export and are not shown here; the graph at syntology.ai holds them. "Ran" means executed on a synthesized fixture, not that the code is correct or reproduces a paper.

Samples Syntology

Syntology ran 1 of the 11 distinct code bodies named layer_norm_and_dropout; 10 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

1ran · honoured contract
0ran · violated contract
0ran · our draft was wrong
0ran · fixture could not drive it
0ran
10unverified
0fingerprinted

Licence is a property of each copy, so it is counted per place: 4 of the 11 places are pointer only (Syntology does not serve that copy's text). This site shows no code text for any sample; every row below links to the file in its repository where the record names one.

“Ran” means the sample executed on a synthesized input; it does not mean the output is correct. “Honoured” and “violated” refer to a contract Syntology drafted from the code itself; “our draft was wrong” and “fixture could not drive it” are failures of Syntology's instrument, not of the code, and those samples did run. The ran count above is every status except unverified, the same rule as each paper page.

Papers

6 papers shown of 6, newest first; 11 places in the table. A paper with no recorded date is placed by the month its arXiv id encodes, shown in the Date column as YYYY-MM (from id). One row per place: a paper whose repository defines the name more than once appears more than once, and the same code body held for several papers appears once under each, with the same status. Titles and dates are the archive's archive 2025-07-28 for papers in the archive; 2 papers have no page here and are shown by arXiv id only. Status and fingerprint are Syntology's record of each code body; licence is recorded for each place. The File cell ends with the code body's code_sha256, Syntology's identity for that exact code: an agent fetches the stored sample with Syntology's MCP tool get_code(code_sha256="…") (how to connect); click an identity to copy that call.

PaperDateFileStatus SyntologyLicence
StructuralLM: Structural Pre-training for Form Understanding 24 May 2021 alibaba/AliceMind/StructuralLM/modeling.py 58bed10d69223f15 unverified Apache-2.0 (permissive)
Probabilistically Masked Language Model Capable of Autoregressive Generation in Arbitrary Word Order 24 Apr 2020 huawei-noah/Pretrained-Language-Model/PMLM/interactive_conditional_samples_sincos_acrostic.py 15f847b95346c6d2 unverified no licence file found · pointer only
ALBERT: A Lite BERT for Self-supervised Learning of Language Representations 26 Sep 2019 brightmart/albert_zh/modeling_google.py 4e61fb4457fa4a37 unverified no licence file found · pointer only
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding 11 Oct 2018 appcoreopc/berty/modeling.py 80bc5181b671b9a1 ran · honoured contract Apache-2.0 (permissive)
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding 11 Oct 2018 TeamLab/bert-gcn-for-paper-citation/modeling.py 61cb05022cc82f2b unverified no licence file found · pointer only
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding 11 Oct 2018 h4ste/oscar/modeling.py 82dc008a899111c5 unverified Apache-2.0 (permissive)
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding 11 Oct 2018 deepmipt/bert/bert_dp/modeling.py cf1f91679b130b04 unverified Apache-2.0 (permissive)
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding 11 Oct 2018 SCismycat/bert_code_view/modeling.py 92ef7ef36a321f62 unverified Apache-2.0 (permissive)
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding 11 Oct 2018 ricardordb/bert/modeling.py 69ead5ac4ce92603 unverified Apache-2.0 (permissive)
arXiv:2023.acl-long.693 AI4Bharat/IndicBERT/train/modeling.py e49e3e61dc0f7f67 unverified MIT (permissive)
arXiv:2021.acl-long.233 ACL2020SpellGCN/SpellGCN/modeling.py 62a741eb766dea2f unverified no licence file found · pointer only

This site shows no code text; each File cell links to the file on GitHub at the repository's current default branch, which may have changed since the harvest. "Pointer only" means Syntology does not serve that copy's text, for one of four reasons: no licence file was found; the licence was not identified; the licence is recorded as permissive but that copy's record is not marked cleared; or the licence is outside the permissive list Syntology serves text under (MIT, Apache-2.0, BSD and similar). Some licences outside that list permit redistribution, such as WTFPL, and GPL-3.0 under its conditions; they are simply not on the list. Hover a licence cell for the reason. Per-sample records for a paper are on its paper page under "Code Syntology ran".

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections