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reduce_tensor

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

reduce_tensor appears in the code Syntology harvested for 32 papers, as 22 distinct code bodies found in 32 places (a place is one code body under one paper). At least one of them ran in 11 of the papers; 1 of the code bodies carries 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 reduce_tensor 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 8 of the 22 distinct code bodies named reduce_tensor; 14 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

0ran · honoured contract
0ran · violated contract
1ran · our draft was wrong
4ran · fixture could not drive it
3ran
14unverified
1fingerprinted

Licence is a property of each copy, so it is counted per place: 6 of the 32 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

32 papers shown of 32, newest first; 32 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 1 papers added by Syntology; 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
Neural Collapse by Design: Learning Class Prototypes on the Hypersphere added by Syntology 2026-05 (from id) pakoromilas/nc_by_design/main_ce.py 4c0a8859c4aa301e unverified BSD-2-Clause (permissive)
PointLoRA: Low-Rank Adaptation with Token Selection for Point Cloud Learning 22 Apr 2025 songw-zju/PointLoRA/utils/dist_utils.py 5f9ab5e0087e7f19 unverified Apache-2.0 (permissive)
Parametric Point Cloud Completion for Polygonal Surface Reconstruction 11 Mar 2025 parametric-completion/paco/utils/dist_utils.py 5f9ab5e0087e7f19 unverified MIT (permissive)
A deeper look at depth pruning of LLMs 23 Jul 2024 shoaibahmed/llm_depth_pruning/dist_utils.py 8ca3bc5af5d77698 ran fingerprinted no licence file found · pointer only
Counterfactual Reasoning for Multi-Label Image Classification via Patching-Based Training 9 Apr 2024 xiemk/mlc-pat/src_files/helper_functions/distributed.py 14265d790751cfed unverified no licence file found · pointer only
Once for Both: Single Stage of Importance and Sparsity Search for Vision Transformer Compression 23 Mar 2024 hankye/once-for-both/models/layers.py 66146bb864eaf92b unverified MIT (permissive)
Instant3D: Instant Text-to-3D Generation 14 Nov 2023 ming1993li/instant3dcodes/training/loss.py 3efe35e36ec50fd3 unverified MIT (permissive)
RoboDepth: Robust Out-of-Distribution Depth Estimation under Corruptions 23 Oct 2023 hyBlue/FSRE-Depth/train_ddp.py 4c7488e70da6a280 ran MIT (permissive)
Masked Spatio-Temporal Structure Prediction for Self-supervised Learning on Point Cloud Videos 18 Aug 2023 johnsonsign/mast-pre/utils.py 5f0f7c378e04ba6a unverified MIT (permissive)
LATR: 3D Lane Detection from Monocular Images with Transformer 8 Aug 2023 JMoonr/LATR/experiments/ddp.py be5abd3083ea4db8 ran MIT (permissive)
Improving Knowledge Distillation via Regularizing Feature Norm and Direction 26 May 2023 wangyz1608/knowledge-distillation-via-nd/ImageNet/train_dkd.py b57663499e3c25d8 ran · fixture could not drive it no licence file found · pointer only
Fine-tuned CLIP Models are Efficient Video Learners 6 Dec 2022 muzairkhattak/vifi-clip/utils/tools.py 2e6dd851990fe932 unverified MIT (permissive)
Learning Dense and Continuous Optical Flow from an Event Camera 16 Nov 2022 danqu130/DCEIFlow/evaluate.py 06724a1cdbc6af8c ran · fixture could not drive it MIT (permissive)
Towards Transferable Unrestricted Adversarial Examples with Minimum Changes 4 Jan 2022 Equationliu/GA-Attack/main_bench_mark.py 65e1c0ed365fa761 ran · fixture could not drive it MIT (permissive)
On Training Implicit Models 9 Nov 2021 gsunshine/phantom_grad/MDEQ/MDEQ_ImageNet/train_mdeq_imagenet.py f55cbb1d14054e26 unverified MIT (permissive)
Unrestricted Adversarial Attacks on ImageNet Competition 17 Oct 2021 identical code first harvested elsewhere 65e1c0ed365fa761 ran · fixture could not drive it licence of this copy not recorded
D2C: Diffusion-Denoising Models for Few-shot Conditional Generation 12 Jun 2021 jiamings/d2c/d2c/autoencoder/utils.py be5abd3083ea4db8 ran MIT (permissive)
AgeFlow: Conditional Age Progression and Regression with Normalizing Flows 15 May 2021 Hzzone/AgeFlow/flow/models.py a25acbda57ff74c2 ran · fixture could not drive it no licence file found · pointer only
ImageNet-21K Pretraining for the Masses 22 Apr 2021 Alibaba-MIIL/ImageNet21K/src_files/helper_functions/distributed.py 14265d790751cfed unverified MIT (permissive)
Learning Neural Generative Dynamics for Molecular Conformation Generation 20 Feb 2021 deepgraphlearning/cgcf-confgen/models/cnf_edge/cnf.py 11965d5ebfe77481 ran · our draft was wrong no licence file found · pointer only
HiFiSinger: Towards High-Fidelity Neural Singing Voice Synthesis 3 Sep 2020 CODEJIN/HiFiSinger/distributed.py a9bfcbb1d3623ba1 unverified MIT (permissive)
Learning Gradient Fields for Shape Generation 14 Aug 2020 RuojinCai/ShapeGF/train_multi_gpus.py 11965d5ebfe77481 ran · our draft was wrong MIT (permissive)
TF-NAS: Rethinking Three Search Freedoms of Latency-Constrained Differentiable Neural Architecture Search 12 Aug 2020 AberHu/TF-NAS/train_eval_amp.py 91cd803b76cc8823 unverified MIT (permissive)
SeCo: Exploring Sequence Supervision for Unsupervised Representation Learning 3 Aug 2020 YihengZhang-CV/SeCo-Sequence-Contrastive-Learning/seco/util.py 5f0f7c378e04ba6a unverified MIT (permissive)
Flowtron: an Autoregressive Flow-based Generative Network for Text-to-Speech Synthesis 12 May 2020 NVIDIA/flowtron/distributed.py a9bfcbb1d3623ba1 unverified Apache-2.0 (permissive)
How to train your neural ODE: the world of Jacobian and kinetic regularization 7 Feb 2020 D-hash-code/ffjord-rnode-finalweek-mnist/dist_utils.py be51985b302891b6 unverified MIT (permissive)
Identifying and Compensating for Feature Deviation in Imbalanced Deep Learning 6 Jan 2020 zhangyongshun/BagofTricks-LT/lib/core/function.py 75000f8601e0929d unverified MIT (permissive)
Scaleable input gradient regularization for adversarial robustness 27 May 2019 cfinlay/tulip/imagenet/dist_utils.py c3f576afeebe9300 unverified MIT (permissive)
WaveGlow: A Flow-based Generative Network for Speech Synthesis 31 Oct 2018 NVIDIA/waveglow/distributed.py 720ec6edbf432e1e unverified BSD-3-Clause (permissive)
Deep Voice: Real-time Neural Text-to-Speech 25 Feb 2017 NVIDIA/nv-wavenet/pytorch/distributed.py 720ec6edbf432e1e unverified BSD-3-Clause (permissive)
arXiv:aaai_29654 zcy866/CSR/utils.py 3efe35e36ec50fd3 unverified MIT (permissive)
arXiv:Li_FCC_Feature_Clusters_Compression_for_Long-Tailed_Visual_Recognition_CVPR_2023_paper lijian16/FCC/lib/core/function.py 75000f8601e0929d 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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