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get_dataloaders

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

get_dataloaders appears in the code Syntology harvested for 22 papers, as 23 distinct code bodies found in 23 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 get_dataloaders 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 23 distinct code bodies named get_dataloaders; 21 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
21unverified
0fingerprinted

Licence is a property of each copy, so it is counted per place: 3 of the 23 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

22 papers shown of 22, newest first; 23 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, and the graph's for 3 papers added by Syntology; 3 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
GRASP: Gradient-Aligned Sequential Parameter Transfer for Memory-Efficient Multi-Source Learning added by Syntology 2026-06 (from id) Sekeh-Lab/grasp-multisource-transfer/experiments/grasp/run_grasp_experiment.py a425378802b4b531 ran MIT (permissive)
Beyond a Single Explanation of the Adam-SGD Gap added by Syntology 2026-06 (from id) orientino/gap/genomics/data.py 4740a336be8375d0 ran Apache-2.0 (permissive)
On the Infinite Width and Depth Limits of Predictive Coding Networks added by Syntology 2026-02 (from id) thebuckleylab/jpc/experiments/datasets.py 830d4add00e832e7 unverified MIT (permissive)
arXiv:2507.12001 2025-07 (from id) wslh852/AUBlendNet/dataset/data_loader.py 0ba1ca704c85216a unverified MIT (permissive)
CultureCLIP: Empowering CLIP with Cultural Awareness through Synthetic Images and Contextualized Captions 8 Jul 2025 lukahhcm/cultureclip/model_finetune/data.py 10112852bb5ceb00 unverified no licence file found · pointer only
RLVR-World: Training World Models with Reinforcement Learning 20 May 2025 thuml/RLVR-World/vid_wm/ivideogpt/eval_runenv.py 9fdeb5691f697950 unverified MIT (permissive)
RLVR-World: Training World Models with Reinforcement Learning 20 May 2025 thuml/RLVR-World/vid_wm/ivideogpt/eval_vgpt.py 84199c73adefd0fc unverified MIT (permissive)
iVideoGPT: Interactive VideoGPTs are Scalable World Models 24 May 2024 thuml/iVideoGPT/train_gpt.py e8b08bcb092a8f81 unverified MIT (permissive)
Discriminator Guidance for Autoregressive Diffusion Models 24 Oct 2023 filipekstrm/graph_ardm/src/dataset/dataset.py f61613e78442e4b2 unverified no licence file found · pointer only
Interpreting and Correcting Medical Image Classification with PIP-Net 19 Jul 2023 m-nauta/pipnet/util/data.py 595b1dbf510e516b unverified no licence file found · pointer only
PILLAR: How to make semi-private learning more effective 6 Jun 2023 FrancescoPinto/PILLAR/utils.py 44d01d8fe81d5392 unverified MIT (permissive)
Fixing Overconfidence in Dynamic Neural Networks 13 Feb 2023 aaltoml/calibrated-dnn/dataloader.py 6ab6ac3cf72849e7 unverified MIT (permissive)
NeRN -- Learning Neural Representations for Neural Networks 27 Dec 2022 maorash/nern/NeRN/tasks/imagenet_helpers.py f39c3e4ba3afe858 unverified MIT (permissive)
Boosted Dynamic Neural Networks 30 Nov 2022 SHI-Labs/Boosted-Dynamic-Networks/dataloader.py e26baa07200cad5a unverified MIT (permissive)
Compression, Transduction, and Creation: A Unified Framework for Evaluating Natural Language Generation 14 Sep 2021 tanyuqian/ctc-gen-eval/ctc_score/data_utils/data_utils.py e9fc6d93b3c4e519 unverified MIT (permissive)
Large Scale Organization and Inference of an Imagery Dataset for Public Safety 16 Aug 2019 LADI-Dataset/ladi-overview/training/config_dataloader.py 4cf20d9e7e99b470 unverified MIT (permissive)
Continuous Hierarchical Representations with Poincaré Variational Auto-Encoders 17 Jan 2019 omiethescientist/HyperbolicDeepLearning/HVAE/Data.py 82ae9a25c955fb4c unverified MIT (permissive)
Spoken Language Understanding on the Edge 30 Oct 2018 CoraJung/flexible-input-slu/bert/data.py add880586a716006 unverified Apache-2.0 (permissive)
Predict then Propagate: Graph Neural Networks meet Personalized PageRank 14 Oct 2018 klicperajo/ppnp/ppnp/pytorch/training.py a75db933b77e116f unverified MIT (permissive)
Self-Attention Generative Adversarial Networks 21 May 2018 rahulkulhalli/ISIC2019/utils.py ad810d34df32ec81 unverified MIT (permissive)
Multi-Scale Dense Networks for Resource Efficient Image Classification 29 Mar 2017 kalviny/MSDNet-PyTorch/dataloader.py b51a9a4dd721bcbc unverified MIT (permissive)
arXiv:ijcai2024_0102 mRobotit/M2Beats/data_loader.py 16f4a41d3b594606 unverified Apache-2.0 (permissive)
arXiv:Huang_Task-Adaptive_Negative_Envision_for_Few-Shot_Open-Set_Recognition_CVPR_2022_paper shiyuanh/TANE/dataloader/dataloader.py 26d8cf61c5515f20 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".

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