Releases: WenjieDu/PyPOTS
v1.3 🍕 Add TKAN
This new release integrates TKAN (an implementation of Temporal Kolmogorov-Arnold Networks) into PyPOTS, along with some bug fixes. Refer to the below changelog for details.
👍 Kudos to our new contributor @awanawana!
What's Changed
- Add TKAN (Temporal Kolmogorov-Arnold Networks) imputation model by @Copilot in #809
- Update docs by @WenjieDu in #810
- Fix linting issues and update docs by @WenjieDu in #811
- build(deps): bump docker/setup-buildx-action from 3 to 4 by @dependabot[bot] in #817
- build(deps): bump docker/build-push-action from 6 to 7 by @dependabot[bot] in #816
- build(deps): bump docker/login-action from 3 to 4 by @dependabot[bot] in #815
- build(deps): bump docker/setup-qemu-action from 3 to 4 by @dependabot[bot] in #814
- Update docs to add DeepWiki link by @WenjieDu in #818
- fix: add numpy support to calc_quantile_loss function by @awanawana in #822
- Update docs by @WenjieDu in #823
New Contributors
- @awanawana made their first contribution in #822
Full Changelog: v1.2...v1.3
v1.2 🍪 New algorithms and bug fixes
What's Changed
- Fix GPVAE training TypeError: convert length_scale float to tensor in matern_kernel by @Copilot in #799
- Fix MOMENT segfault on multiple GPUs by @Copilot in #800
- Add MixLinear as a forecasting model by @Copilot in #805
- Add TimeMixer++ forecasting task support by @Copilot in #806
- Add SeFT as a classification model by @Copilot in #801
- Update docs by @WenjieDu in #807
New Contributors
- @Copilot made their first contribution in #799
Full Changelog: v1.1...v1.2
v1.1🐞Bug fix
We fixed some known bugs (listed in the changelog) in this release.
👍 Kudos to our new contributors Emmanuel @emmanuel-ferdman and Arina @arinagoncharova2005!
What's Changed
- fix: update threading interface in testing by @emmanuel-ferdman in #761
- Update docs by @WenjieDu in #762
- Update docs and fix deprecated threading.Thread.setDaemon by @WenjieDu in #763
- Update the team page in docs by @WenjieDu in #764
- build(deps): bump actions/first-interaction from 1 to 2 by @dependabot[bot] in #765
- build(deps): bump actions/first-interaction from 1 to 2 by @dependabot[bot] in #767
- build(deps): bump actions/first-interaction from 2 to 3 by @dependabot[bot] in #771
- build(deps): bump actions/checkout from 4 to 5 by @dependabot[bot] in #770
- Update TEFN reference by @WenjieDu in #772
- build(deps): bump actions/setup-python from 5 to 6 by @dependabot[bot] in #776
- build(deps): bump actions/stale from 9 to 10 by @dependabot[bot] in #775
- build(deps): bump pypa/gh-action-pypi-publish from 1.12.4 to 1.13.0 by @dependabot[bot] in #774
- Update configs in greetings by @WenjieDu in #779
- Make CI run on Ubuntu only by @WenjieDu in #782
- Fix TimeMixer channel independence forecasting by @WenjieDu in #780
- Update configs in issue_manager workflow by @WenjieDu in #784
- build(deps): bump tiangolo/issue-manager from 0.5.1 to 0.6.0 by @dependabot[bot] in #786
- build(deps): bump actions/checkout from 5 to 6 by @dependabot[bot] in #791
- Fix the issue of CSAI by @LinglongQian in #788
- Fix n_layers typo in timemixer/timemixerpp.classification() by @WenjieDu in #793
- Update docs by @WenjieDu in #796
- Fix device mismatch in padding function by @arinagoncharova2005 in #794
- Fix multi_class type error in LogisticRegression and device mismatch in torch_pad_nan by @WenjieDu in #798
New Contributors
- @emmanuel-ferdman made their first contribution in #761
- @arinagoncharova2005 made their first contribution in #794
Full Changelog: v1.0...v1.1
v1.0🍻The 1st major version comes
We enabled PatchTST and Autoformer to work on the classification task. In addition, some reported bugs from the community have been fixed. 👍Kudos to our new contributor @zltututu!
Considering the major functionalities in the current stage have all been implemented and we have researched a stable version, this version is released as the 1st major version of PyPOTS as v1.0. This is our new milestone, and let's move forward towards v2.0!
What's Changed
- Fix runtime error in ModernTCN when using multiple layers by @zltututu in #751
- Fix the unintended overwriting issue in TimesNet by @WenjieDu in #756
- Add classification PatchTST by @WenjieDu in #757
- Add classification Autoformer by @WenjieDu in #758
- Update docs by @WenjieDu in #759
- Release v1.0 by @WenjieDu in #760
New Contributors
Full Changelog: v0.19...v1.0
v0.19📈Implement 3 models for forecasting
MICN, DLinear, and FiLM are implementation for time series forecasting.
What's Changed
- Update docs by @WenjieDu in #743
- Update docs by @WenjieDu in #746
- Add forecasting MICN by @WenjieDu in #747
- Add forecasting DLinear by @WenjieDu in #748
- Add forecasting FiLM by @WenjieDu in #749
- Add forecasting FiLM, DLinear, MICN, and release v0.19 by @WenjieDu in #750
Full Changelog: v0.18...v0.19
v0.18🔍Implement 10 models on anomaly detection
iTransforme, Crossforme, Pyraformer, FEDformer, Informer, Transformer, ETSformer, TimeMixer, Nonstationary Tr., and FiLM are implemented on the anomaly detection task.
What's Changed
- Add 10 new anomaly detection algorithms by @yyysjz1997 in #738
- Add 10 new models by @WenjieDu in #739
- Update docs by @WenjieDu in #741
- Update docs and release v0.18 by @WenjieDu in #742
Full Changelog: v0.17...v0.18
v0.17 Five algos added to anomaly detection
TimeMixer++, SCINet, DLinear, TimesNet, and Reformer are implemented on the anomaly detection task.
👍Kudos to our new contributors Yiyuan @yyysjz1997 and Pavel @Durakavalyanie!
What's Changed
- Add anomaly detection TimesNet by @yyysjz1997 in #725
- Fix unused n_sampling_times argument in CSDI.predict by @Durakavalyanie in #730
- Implement Reformer for anomaly detection by @WenjieDu in #732
- Implement SCINet for anomaly detection by @WenjieDu in #733
- Implement DLinear for anomaly detection by @WenjieDu in #734
- Implement TimeMixerPP for anomaly detection by @WenjieDu in #735
- Update the staling workflow and the PR template by @WenjieDu in #731
- Update docs by @WenjieDu in #736
- Release v0.17 by @WenjieDu in #737
New Contributors
- @yyysjz1997 made their first contribution in #725
- @Durakavalyanie made their first contribution in #730
Full Changelog: v0.16...v0.17
v0.16 Three forecasting algos implemented
ModernTCN, TimesNet, and SegRNN are implemented on the forecasting task in this release.
What's Changed
- Add forecasting TimesNet by @WenjieDu in #705
- Update dependency versions for development environment by @WenjieDu in #709
- Update some CI configs by @WenjieDu in #713
- Fix AttributeError: 'NoneType' object has no attribute 'endswith' in TimeLLM by @WenjieDu in #712
- Add
sentencepieceto dependencies of dev env by @WenjieDu in #715 - Exempt issues and PRs with 'potential bug' label from staling by @WenjieDu in #716
- Add forecasting ModernTCN by @WenjieDu in #717
- Add forecasting SegRNN by @WenjieDu in #720
- Add issue manger to auto close completed issues by @WenjieDu in #721
- Update docs by @WenjieDu in #722
- Decrease anomaly rate in CI testing to avoid GPT4TS outputting NaNs by @WenjieDu in #723
- Release v0.16 by @WenjieDu in #724
- Fix failed issue manager by @WenjieDu in #728
- Fix failed greeting workflow by @WenjieDu in #727
Full Changelog: v0.15...v0.16
v0.15⚡️Three New Algos
In this release, TimeMixer++, TOTEM, and TSLANet are included and have been implemented on the imputation task.
What's Changed
- Add TimeMixer++ by @WenjieDu in #691
- Bump the least version of Python to 3.9 in GitHub CI workflow by @WenjieDu in #698
- Add TOTEM modules and IMPU TOTEM by @WenjieDu in #694
- Add TSLANet modules and IMPU TSLANet by @WenjieDu in #696
- Release v0.15 by @WenjieDu in #700
- Update docs by @WenjieDu in #702
- Publish to Docker Hub by @WenjieDu in #703
Full Changelog: v0.14...v0.15
v0.14🕵Six Anomaly Detection Models Implemented
This new release implements TEFN, ImputeFormer, SAITS, PatchTST, SegRNN, and Autoformer for anomaly detection. Moreover, models now output their latents #674, which are returned as a part of dict results in pypots.{task_name}.{model_name}.core._{mode_name}.forward(). A model-saving bug (#668) has been fixed that may result in the best model state not being properly loaded/saved.
Refer to the below changelog for more details.
What's Changed
- Fix the bug that model state not a deep copy by @WenjieDu in #668
- build(deps): bump actions/setup-python from 3 to 5 by @dependabot in #636
- Fix failed CLAS TEFN with
ROC AUC<0.5 by @WenjieDu in #671 - Add ANOD Autoformer by @WenjieDu in #672
- Update docs to add ANOD package by @WenjieDu in #673
- Output model latents and refactor the framework by @WenjieDu in #674
- Fix OOM TimeLLM when testing by @WenjieDu in #676
- Use agreed names to distinguish data at different stages by @WenjieDu in #678
- Fix the bug that calc_criterion() not callable on multiGPUs by @WenjieDu in #681
- Implement SAITS for anomaly detection by @WenjieDu in #684
- Fix failed docs building by @WenjieDu in #685
- Implement TEFN for anomaly detection by @WenjieDu in #686
- Implement ImputeFormer for anomaly detection by @WenjieDu in #687
- Implement PatchTST for anomaly detection by @WenjieDu in #688
- Implement SegRNN for anomaly detection by @WenjieDu in #689
- Release v0.14 by @WenjieDu in #690
Full Changelog: v0.13...v0.14