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get_same_padding

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

get_same_padding appears in the code Syntology harvested for 16 papers, as 8 distinct code bodies found in 17 places (a place is one code body under one paper). At least one of them ran in 13 of the papers; 3 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_same_padding 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 4 of the 8 distinct code bodies named get_same_padding; 4 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

3ran · honoured contract
0ran · violated contract
0ran · our draft was wrong
0ran · fixture could not drive it
1ran
4unverified
3fingerprinted

Licence is a property of each copy, so it is counted per place: 5 of the 17 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

16 papers shown of 16, newest first; 17 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 2 papers added by Syntology. 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
UNIEGO: Proxies as Mediators for Unified Egocentric Video Representation Learning added by Syntology 2026-06 (from id) Wenhao-Chi/UNIEGO/timesformer/models/conv2d_same.py 54e11386110ff042 ran · honoured contract fingerprinted no licence file found · pointer only
Hyperspherical Autoencoder for High-Fidelity Image Reconstruction and Generation added by Syntology 2026-01 (from id) wkdgnsgo/HAE/src/model.py a1763386d63ec847 unverified MIT (permissive)
Motion meets Attention: Video Motion Prompts 3 Jul 2024 q1xiangchen/vmps/timesformer/models/conv2d_same.py 54e11386110ff042 ran · honoured contract fingerprinted MIT (permissive)
Deep Blind Super-Resolution for Satellite Video 13 Jan 2024 xy-boy/blind-satellite-vsr/model/blocks.py 4ec1f46edd412686 ran fingerprinted no licence file found · pointer only
Spatio-Temporal Deformable Attention Network for Video Deblurring 22 Jul 2022 huicongzhang/stdan/models/model/blocks.py 4ec1f46edd412686 ran fingerprinted MIT (permissive)
DepthShrinker: A New Compression Paradigm Towards Boosting Real-Hardware Efficiency of Compact Neural Networks 2 Jun 2022 facebookresearch/depthshrinker/models/efficientnet_blocks.py 54e11386110ff042 ran · honoured contract fingerprinted licence not identified · pointer only
DirecFormer: A Directed Attention in Transformer Approach to Robust Action Recognition 19 Mar 2022 uark-cviu/direcformer/slowfast/models/conv2d_same.py 54e11386110ff042 ran · honoured contract fingerprinted Apache-2.0 recorded; this copy not marked cleared · pointer only
4D-Net for Learned Multi-Modal Alignment 2 Sep 2021 chanlilong/4D_NET_pytorch/models/detector_models.py 466f16b4752e5041 unverified MIT (permissive)
AlphaNet: Improved Training of Supernets with Alpha-Divergence 16 Feb 2021 facebookresearch/AttentiveNAS/models/attentive_nas_dynamic_model.py 71cbea6f98bde1f9 ran · honoured contract fingerprinted licence not identified · pointer only
Cascaded Deep Video Deblurring Using Temporal Sharpness Prior 6 Apr 2020 csbhr/CDVD-TSP/code/model/blocks.py 4ec1f46edd412686 ran fingerprinted MIT (permissive)
Designing Network Design Spaces 30 Mar 2020 ZHANGHeng19931123/MutualGuide/models/backbone/gpunet_backbone.py 54e11386110ff042 ran · honoured contract fingerprinted MIT (permissive)
Deep Blind Video Super-resolution 10 Mar 2020 csbhr/Deep-Blind-VSR/code/model/blocks.py 4ec1f46edd412686 ran fingerprinted MIT (permissive)
EfficientDet: Scalable and Efficient Object Detection 20 Nov 2019 Jintao-Huang/EfficientDet_PyTorch/models/efficientnet.py ce78adffe6b7cfbf ran · honoured contract Apache-2.0 (permissive)
QuartzNet: Deep Automatic Speech Recognition with 1D Time-Channel Separable Convolutions 2019-10 (from id) marka17/digit-recognition/src/modules/jasper.py ba297314ad959cc0 unverified MIT (permissive)
QuartzNet: Deep Automatic Speech Recognition with 1D Time-Channel Separable Convolutions 2019-10 (from id) oleges1/quartznet-pytorch/model/utils.py 6a909b63465cabc2 unverified MIT (permissive)
Once-for-All: Train One Network and Specialize it for Efficient Deployment 26 Aug 2019 seulkiyeom/once-for-all/utils.py 71cbea6f98bde1f9 ran · honoured contract fingerprinted Apache-2.0 (permissive)
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks 28 May 2019 Jintao-Huang/EfficientNet_PyTorch/models/efficientnet.py ce78adffe6b7cfbf ran · honoured contract Apache-2.0 (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