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convert_model

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

convert_model appears in the code Syntology harvested for 14 papers, as 13 distinct code bodies found in 15 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 convert_model 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 13 distinct code bodies named convert_model; 11 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
0ran · fixture could not drive it
1ran
11unverified
0fingerprinted

Licence is a property of each copy, so it is counted per place: 1 of the 15 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

14 papers shown of 14, newest first; 15 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
MONAQ: Multi-Objective Neural Architecture Querying for Time-Series Analysis on Resource-Constrained Devices 15 May 2025 kaist-dmlab/monaq/converters.py 04d0d2ddb8e33161 unverified MIT (permissive)
Cal-SFDA: Source-Free Domain-adaptive Semantic Segmentation with Differentiable Expected Calibration Error 6 Aug 2023 jo-wang/cal-sfda/model/sync_batchnorm/batchnorm.py 660b29e7beb7f344 ran MIT (permissive)
PopulAtion Parameter Averaging (PAPA) 6 Apr 2023 samsungsailmontreal/papa/sync_batchnorm/batchnorm.py 9cd45e4b4fb9ad28 unverified MIT (permissive)
Synthetic Text Generation with Differential Privacy: A Simple and Practical Recipe 25 Oct 2022 microsoft/dp-transformers/research/synthetic-text-generation-with-DP/generate-text.py 67563e08a8fbe297 unverified MIT (permissive)
Domain Adaptation on Point Clouds via Geometry-Aware Implicits 17 Dec 2021 jhonve/implicitpcda/models/sync_batchnorm/batchnorm.py fd571474b78c67d9 unverified MIT (permissive)
Music Demixing Challenge 2021 31 Aug 2021 yoyololicon/music-demixing-challenge-ismir-2021-entry/sync_batchnorm/batchnorm.py 9cd45e4b4fb9ad28 unverified MIT (permissive)
ClassMix: Segmentation-Based Data Augmentation for Semi-Supervised Learning 15 Jul 2020 WilhelmT/ClassMix/utils/sync_batchnorm/batchnorm.py b0cd1f9681d630e2 unverified MIT (permissive)
SqueezeSegV3: Spatially-Adaptive Convolution for Efficient Point-Cloud Segmentation 3 Apr 2020 chenfengxu714/SqueezeSegV3/src/common/sync_batchnorm/batchnorm.py 6175d817c01a13bc unverified BSD-2-Clause (permissive)
SalsaNext: Fast, Uncertainty-aware Semantic Segmentation of LiDAR Point Clouds for Autonomous Driving 7 Mar 2020 TiagoCortinhal/SalsaNext/train/common/sync_batchnorm/batchnorm.py 2f71fbe65121af01 unverified MIT (permissive)
Filter Response Normalization Layer: Eliminating Batch Dependence in the Training of Deep Neural Networks 21 Nov 2019 tattaka/Filter-Response-Normalization-PyTorch/filter_response_normalization/filter_response_normalize.py c9a5f3feedf35dc9 ran · our draft was wrong MIT (permissive)
Making Convolutional Networks Shift-Invariant Again 25 Apr 2019 tattaka/Antialiased-CNNs-Converter-PyTorch/antialiased_cnns_converter/antialiased_cnns_converter.py 32c38f429da97bdd unverified MIT (permissive)
Feature Distillation: DNN-Oriented JPEG Compression Against Adversarial Examples 14 Mar 2018 zihaoliu123/Feature-Distillation-DNN-Oriented-JPEG-Compression-Against-Adversarial-Examples/attacks/carlini_wrapper.py dce02585e3349215 unverified MIT (permissive)
MegDet: A Large Mini-Batch Object Detector 20 Nov 2017 vacancy/Synchronized-BatchNorm-PyTorch/sync_batchnorm/batchnorm.py 9cd45e4b4fb9ad28 unverified MIT (permissive)
MegDet: A Large Mini-Batch Object Detector 20 Nov 2017 chrisway613/Synchronized-BatchNormalization/func.py b242a8523848aac6 unverified no licence file found · pointer only
Pyramid Scene Parsing Network 4 Dec 2016 YininKorea/Contour-aware-equipotential-learning/Networks/sync_batchnorm/batchnorm.py 21d32f46755ba0dc 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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