Version 0.6.1¶
v0.6.1 is a security fix / bug fix release.
As always, only load previously trained models using the same version of AutoGluon that they were originally trained on. Loading models trained in different versions of AutoGluon is not supported.
See the full commit change-log here: https://github.com/autogluon/autogluon/compare/v0.6.0…v0.6.1
Special thanks to @lvwerra who is first time contributors to AutoGluon this release!
This version supports Python versions 3.7 to 3.9. 0.6.x are the last releases that will support Python 3.7.
Changes¶
Documentation improvements¶
Fix object detection tutorial layout (#2450) - @bryanyzhu
Add multimodal cheatsheet (#2467) - @sxjscience
Refactoring detection inference quickstart and bug fix on fit->predict - @yongxinw, @zhiqiangdon, @Innixma, @BingzhaoZhu, @tonyhoo
Use Pothole Dataset in Tutorial for AutoMM Detection (#2468) - @FANGAreNotGnu
add time series cheat sheet, add time series to doc titles (#2478) - @canerturkmen
Update all repo references to autogluon/autogluon (#2463) - @gidler
fix typo in object detection tutorial CI (#2516) - @tonyhoo
Bug Fixes / Security¶
bump evaluate to 0.3.0 (#2433) - @lvwerra
Add finetune/eval tests for AutoMM detection (#2441) - @FANGAreNotGnu
Adding Joint IA3_LoRA as efficient finetuning strategy (#2451) - @Raldir
Fix AutoMM warnings about object detection (#2458) - @zhiqiangdon
[Tabular] Speed up feature transform in tabular NN model (#2442) - @liangfu
fix matcher cpu inference bug (#2461) - @sxjscience
[timeseries] Silence GluonTS JSON warning (#2454) - @shchur
[timeseries] Fix pandas groupby bug + GluonTS index bug (#2420) - @shchur
Simplified infer speed throughput calculation (#2465) - @Innixma
[Tabular] make tabular nn dataset iterable (#2395) - @liangfu
Remove old images and dataset download scripts (#2471) - @Innixma
Support image bytearray in AutoMM (#2490) - @suzhoum
[NER] add an NER visualizer (#2500) - @cheungdaven
[Cloud] Lazy load TextPredcitor and ImagePredictor which will be deprecated (#2517) - @tonyhoo
Use detectron2 visualizer and update quickstart (#2502) - @yongxinw, @zhiqiangdon, @Innixma, @BingzhaoZhu, @tonyhoo
fix df preprocessor properties (#2512) - @zhiqiangdon
[timeseries] Fix info and fit_summary for TimeSeriesPredictor (#2510) - @shchur
[timeseries] Pass known_covariates to component models of the WeightedEnsemble - @shchur
[timeseries] Gracefully handle inconsistencies in static_features provided by user - @shchur
[security] update Pillow to >=9.3.0 (#2519) - @gradientsky
[CI] upgrade codeql v1 to v2 as v1 will be deprecated (#2528) - @tonyhoo
Upgrade scikit-learn-intelex version (#2466) - @Innixma
Save AutoGluonTabular model to the correct folder (#2530) - @shchur
support predicting with model fitted on v0.5.1 (#2531) - @liangfu
[timeseries] Implement input validation for TimeSeriesPredictor and improve debug messages - @shchur
[timeseries] Ensure that timestamps are sorted when creating a TimeSeriesDataFrame - @shchur
Add tests for preprocessing mutation (#2540) - @Innixma
Fix timezone datetime edgecase (#2538) - @Innixma, @gradientsky
Mmdet Fix Image Identifier (#2492) - @FANGAreNotGnu
[timeseries] Warn if provided data has a frequency that is not supported - @shchur
Train and inference with different image data types (#2535) - @suzhoum
Remove pycocotools (#2548) - @bryanyzhu
avoid copying identical dataframes (#2532) - @liangfu
Fix AutoMM Tokenizer (#2550) - @FANGAreNotGnu
[Tabular] Resource Allocation Fix (#2536) - @yinweisu
imodels version cap (#2557) - @yinweisu
Fix int32/int64 difference between windows and other platforms; fix mutation issue - @gradientsky