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batcher

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

batcher appears in the code Syntology harvested for 15 papers, as 12 distinct code bodies found in 19 places (a place is one code body under one paper). At least one of them ran in 5 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 batcher 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 3 of the 12 distinct code bodies named batcher; 9 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
0ran
9unverified
0fingerprinted

Licence is a property of each copy, so it is counted per place: 7 of the 19 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

15 papers shown of 15, newest first; 19 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
Taylorformer: Probabilistic Modelling for Random Processes including Time Series 30 May 2023 oremnirv/Taylorformer/data_wrangler/batcher.py dc7e83587205280e unverified MIT (permissive)
Robust Multivariate Time-Series Forecasting: Adversarial Attacks and Defense Mechanisms 19 Jul 2022 awslabs/gluonts/src/gluonts/itertools.py 9441ca1a63b924c3 unverified Apache-2.0 (permissive)
Monte Carlo EM for Deep Time Series Anomaly Detection 29 Dec 2021 Francois-Aubet/gluon-ts/src/gluonts/itertools.py 668d3b50df5c6b08 unverified Apache-2.0 (permissive)
PSA-GAN: Progressive Self Attention GANs for Synthetic Time Series 2 Aug 2021 awslabs/gluon-ts/src/gluonts/itertools.py 9441ca1a63b924c3 unverified Apache-2.0 (permissive)
Whitening Sentence Representations for Better Semantics and Faster Retrieval 29 Mar 2021 autoliuweijie/bert-whitening-pytorch/eval_with_whitening(nli).py 85db364c67187a22 unverified MIT (permissive)
High-Dimensional Multivariate Forecasting with Low-Rank Gaussian Copula Processes 7 Oct 2019 mbohlkeschneider/gluon-ts/src/gluonts/itertools.py 668d3b50df5c6b08 unverified Apache-2.0 (permissive)
Evaluation Benchmarks and Learning Criteria for Discourse-Aware Sentence Representations 31 Aug 2019 ZeweiChu/DiscoEval/train/discoeval_example.py c852fb3cac0794ad ran · honoured contract licence not identified · pointer only
GluonTS: Probabilistic Time Series Models in Python 12 Jun 2019 mbohlkeschneider/psa-gan/src/gluonts/itertools.py 668d3b50df5c6b08 unverified Apache-2.0 (permissive)
GluonTS: Probabilistic Time Series Models in Python 12 Jun 2019 canerturkmen/gluon-ts/src/gluonts/itertools.py f11db9afe0156686 unverified Apache-2.0 (permissive)
GluonTS: Probabilistic Time Series Models in Python 12 Jun 2019 elenaehrlich/gluon-ts/src/gluonts/itertools.py 32cf67ab3871ffdc unverified Apache-2.0 (permissive)
Correlation Coefficients and Semantic Textual Similarity 19 May 2019 Babylonpartners/corrsim/evaluation/corrsim_eval.py e51eada32278286d unverified Apache-2.0 (permissive)
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding 11 Oct 2018 BinWang28/BERT_Sentence_Embedding/SBERT_WK.py 41ef4758bed26d28 unverified Apache-2.0 (permissive)
What you can cram into a single vector: Probing sentence embeddings for linguistic properties 3 May 2018 identical code first harvested elsewhere ff910817bb9f0411 ran · honoured contract licence of this copy not recorded
Learning General Purpose Distributed Sentence Representations via Large Scale Multi-task Learning 30 Mar 2018 identical code first harvested elsewhere ff910817bb9f0411 ran · honoured contract licence of this copy not recorded
SentEval: An Evaluation Toolkit for Universal Sentence Representations 14 Mar 2018 identical code first harvested elsewhere e1c6e7d12d71cb6b ran · honoured contract licence of this copy not recorded
SentEval: An Evaluation Toolkit for Universal Sentence Representations 14 Mar 2018 identical code first harvested elsewhere ff910817bb9f0411 ran · honoured contract licence of this copy not recorded
StackGAN++: Realistic Image Synthesis with Stacked Generative Adversarial Networks 19 Oct 2017 akanimax/T2F/implementation/networks/InferSent/mutils.py b7fe5da253d02512 unverified MIT (permissive)
Supervised Learning of Universal Sentence Representations from Natural Language Inference Data 5 May 2017 sidak/SentEval/examples/infersent.py e1c6e7d12d71cb6b ran · honoured contract licence not identified · pointer only
Supervised Learning of Universal Sentence Representations from Natural Language Inference Data 5 May 2017 facebookresearch/SentEval/examples/bow.py ff910817bb9f0411 ran · honoured contract licence not identified · pointer only

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