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load_net

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

load_net appears in the code Syntology harvested for 10 papers, as 9 distinct code bodies found in 10 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 load_net 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 9 distinct code bodies named load_net; 7 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
7unverified
0fingerprinted

Licence is a property of each copy, so it is counted per place: 1 of the 10 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

10 papers shown of 10, newest first; 10 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; 1 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
Target conversation extraction: Source separation using turn-taking dynamics 15 Jul 2024 chentuochao/target-conversation-extraction/src/utils.py f22b1d22bc27279d ran MIT (permissive)
PowerFlowNet: Power Flow Approximation Using Message Passing Graph Neural Networks 6 Nov 2023 StavrosOrf/PoweFlowNet/speedup_evaluator.py 3ea53c3f92e2f87b ran MIT (permissive)
Deep OC-SORT: Multi-Pedestrian Tracking by Adaptive Re-Identification 23 Feb 2023 gerardmaggiolino/deep-oc-sort/trackers/motdt_tracker/reid_model.py f817f88d2e7ca234 unverified MIT (permissive)
ByteTrack: Multi-Object Tracking by Associating Every Detection Box 13 Oct 2021 ifzhang/ByteTrack/yolox/motdt_tracker/reid_model.py f817f88d2e7ca234 unverified MIT (permissive)
DeepRobust: A PyTorch Library for Adversarial Attacks and Defenses 13 May 2020 I-am-Bot/DeepRobust/deeprobust/image/evaluation_attack.py 055d12d90bb8de9b unverified MIT (permissive)
Locate, Size and Count: Accurately Resolving People in Dense Crowds via Detection 18 Jun 2019 val-iisc/lsc-cnn/utils/logging_tools.py c0b38f026afda7d1 unverified MIT (permissive)
Gradient-free activation maximization for identifying effective stimuli 1 May 2019 willwx/XDream/xdream/net_utils/net_loader.py e98d5e11ca90b8c4 unverified MIT (permissive)
Deep CORAL: Correlation Alignment for Deep Domain Adaptation 6 Jul 2016 armavox/deepcoral-pchelkin/models.py 6d9d07aae0108daf unverified no licence file found · pointer only
EIE: Efficient Inference Engine on Compressed Deep Neural Network 4 Feb 2016 cucapra/fodlam/fodlam.py a1c9b7bced69fd39 unverified MIT (permissive)
arXiv:Seidenschwarz_Simple_Cues_Lead_to_a_Strong_Multi-Object_Tracker_CVPR_2023_paper dvl-tum/GHOST/ReID/net/load_trained_net.py e08880abd17c1bfe 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