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return_data

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

return_data 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 2 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 return_data 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 2 of the 11 distinct code bodies named return_data; 9 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

0ran · honoured contract
0ran · violated contract
0ran · our draft was wrong
0ran · fixture could not drive it
2ran
9unverified
0fingerprinted

Licence is a property of each copy, so it is counted per place: 1 of the 11 places is 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. 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
Compositional Image Decomposition with Diffusion Models 27 Jun 2024 1Konny/Beta-VAE/dataset.py d920047f26420214 ran MIT (permissive)
Minimum Description Length and Generalization Guarantees for Representation Learning 5 Feb 2024 piotrkrasnowski/mdl_and_generalization_guarantees_for_representation_learning/datasets.py 05d0b6602a883bd3 unverified MIT (permissive)
Latent Noise Segmentation: How Neural Noise Leads to the Emergence of Segmentation and Grouping 28 Sep 2023 ZhengqingUUU/LatentNoiseSegmentation/dataloaders.py 75b9f9771c727b95 ran GPL-3.0 (copyleft) · pointer only
Measuring Massive Multitask Language Understanding 7 Sep 2020 sanjass/MultiTaskLearning/036questions/filtering.py 69e44b454bef1c76 unverified MIT (permissive)
Measuring Massive Multitask Language Understanding 7 Sep 2020 sanjass/MultiTaskLearning/036questions/filtering2.py b441fdbef0a06567 unverified MIT (permissive)
Measuring Massive Multitask Language Understanding 7 Sep 2020 sanjass/MultiTaskLearning/036questions/gradientdescent.py bddd1344d4501303 unverified MIT (permissive)
Measuring Massive Multitask Language Understanding 7 Sep 2020 sanjass/MultiTaskLearning/036questions/gradientdescent2.py 5dfa113ed2d4f658 unverified MIT (permissive)
Measuring Massive Multitask Language Understanding 7 Sep 2020 sanjass/MultiTaskLearning/036questions/logisticregression.py de6faacbeb0eb06d unverified MIT (permissive)
Measuring Massive Multitask Language Understanding 7 Sep 2020 sanjass/MultiTaskLearning/036questions/rnn.py 69930c08eceb6a88 unverified MIT (permissive)
Relevance Factor VAE: Learning and Identifying Disentangled Factors 5 Feb 2019 ThomasMrY/RF-VAE/dataset.py f48944b54ecf0097 unverified MIT (permissive)
Disentangling by Factorising 16 Feb 2018 1Konny/FactorVAE/dataset.py 8752210a3f89714d unverified MIT (permissive)

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