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Changelog

v0.11.1 (2024-06-13)

  • 8f6c8ef feat: vanilla ae with independent channels (#392)
  • 1239acd Multichannel config (#390)
  • 56a6ac1 feat: Support Python 3.12; upgrade pynumaflow to 0.7.1 (#383)
  • c61f59d fix: release new patch version (#385)
  • 4122625 fix: make pivot as optional (#384)
  • 309f16a Added multichannel autoencoder with test cases (#382)

Contributors

  • Avik Basu
  • Kushal Batra
  • Miroslav Boussarov

v0.11.0a0 (2024-05-31)

  • 1b6511b feat: Support Python 3.12; upgrade pynumaflow to 0.7.1

Contributors

  • Avik Basu

v0.11.0 (2024-06-10)

  • 56a6ac1 feat: Support Python 3.12; upgrade pynumaflow to 0.7.1 (#383)

Contributors

  • Avik Basu

v0.10.2 (2024-05-31)

  • c61f59d fix: release new patch version (#385)
  • fb662db fix: release new patch version

Contributors

  • Kushal Batra

v0.10.1 (2024-05-31)

  • 4122625 fix: make pivot as optional (#384)
  • 309f16a Added multichannel autoencoder with test cases (#382)
  • 934d8cf Feat/vanilla ae refactor (#379)

Contributors

  • Avik Basu
  • Kushal Batra
  • Miroslav Boussarov

v0.10.0a0 (2024-05-08)

  • 6f46250 fix: filters
  • 87c16da fix: filters
  • bbcfd47 fix: threshold and filters
  • 984650b feat: agg from conf for multi pivot (#378)
  • 402aabf Fix: Changing pivot to pivot_table to support aggregation (#376)
  • 141e9a0 Postproc support for None (#375)
  • e1ae3ee feat: multi column pivot for druid connector (#374)
  • 98c5766 Static filter (#373)
  • f9ebfaf fix: add threshold in metadata
  • cbf4dbd try: replicate og vanilla ae
  • 8b2e939 feat: enable feature transforms
  • eed9ad4 fix: adjust factor
  • 9ad6d8d feat: fallback to stddev if threshold is too low
  • 5593be3 fix: C contiguous error for exp mov avg tx
  • 8321914 correct struct log for ack_insuf_data
  • b36356c fix: percentile scaler, exp mov avg, sigmoid norm (#369)
  • f7bd30b feat: add PercentileScaler

Contributors

  • Avik Basu
  • Gulshan Bhatia
  • Kushal Batra
  • Nandita Koppisetty
  • s0nicboOm

v0.10.0 (2024-05-14)

  • 934d8cf Feat/vanilla ae refactor (#379)
  • f29f771 Adding RDS Trainer UDF changes (#371)

Contributors

  • Avik Basu
  • Saisharath Reddy Kondakindi

v0.9.2 (2024-05-06)

Contributors

  • Gulshan Bhatia

v0.9.1a11 (2024-05-07)

  • 984650b feat: agg from conf for multi pivot (#378)

Contributors

  • Nandita Koppisetty

v0.9.1a10 (2024-05-03)

  • 402aabf Fix: Changing pivot to pivot_table to support aggregation (#376)

Contributors

  • Nandita Koppisetty

v0.9.1a9 (2024-05-03)

  • 141e9a0 Postproc support for None (#375)
  • e1ae3ee feat: multi column pivot for druid connector (#374)

Contributors

  • Kushal Batra
  • Nandita Koppisetty

v0.9.1a8 (2024-05-01)

Contributors

  • Kushal Batra

v0.9.1a7 (2024-04-29)

  • f9ebfaf fix: add threshold in metadata

Contributors

  • s0nicboOm

v0.9.1a6 (2024-04-24)

  • cbf4dbd try: replicate og vanilla ae
  • 8b2e939 feat: enable feature transforms

Contributors

  • Avik Basu

v0.9.1a5 (2024-04-23)

Contributors

  • Avik Basu

v0.9.1a4 (2024-04-23)

  • 9ad6d8d feat: fallback to stddev if threshold is too low

Contributors

  • Avik Basu

v0.9.1a3 (2024-04-22)

  • 5593be3 fix: C contiguous error for exp mov avg tx

Contributors

  • Avik Basu

v0.9.1a2 (2024-04-22)

  • 8321914 correct struct log for ack_insuf_data

Contributors

  • Gulshan Bhatia

v0.9.1a1 (2024-04-22)

  • b36356c fix: percentile scaler, exp mov avg, sigmoid norm (#369)

Contributors

  • Avik Basu

v0.9.1a0 (2024-04-18)

Contributors

  • Avik Basu
  • Gulshan Bhatia

v0.9.1 (2024-04-17)

  • c3991bb Refactor logging in UDFs (#356)
  • be29f02 Aws connectors (#358)

Contributors

  • Gulshan Bhatia
  • Saisharath Reddy Kondakindi

v0.9.0 (2024-04-17)

  • ad20add fix: remove print (#363)
  • 61f6598 feat: initial support for flattened vector in backtest (#361)
  • 0cbaa52 feat: introduce stride in dataset (#360)
  • db2cc4f feat: support for train transformers (#354)
  • 377ada2 feat: generate static scores for backtesting (#355)

Contributors

  • Avik Basu
  • Kushal Batra

v0.8.0 (2024-03-05)

  • 8dee66b feat!: support static threshold score adjustment (#350)

Contributors

  • Avik Basu

v0.8.dev0 (2024-02-28)

  • 4e93088 bump dev version
  • 81971dc fix: static threshold
  • db943a6 fix: conditional fwd tags
  • c0225a9 refactor
  • 8f8a532 feat: score adjustment with joined trainer vtx
  • ac0eda1 more tests
  • 6623e2b feat: trainer join vertex for preprocess & inference
  • fb97b3a feat: allow chunked druid fetch (#349)
  • d8bda0e feat: Multivariate Anomaly Detection (#343)
  • d0dcb47 feat: score adjuster using static threshold

Contributors

  • Avik Basu

v0.7.0 (2024-02-08)

  • b41a7f7 fix: comments
  • 780f2e2 fix merge issues
  • 9de1e83 fix: backtest
  • c418b5a tmpfix: numalogic opex tags for query filter
  • bc6d08c feat: Score config in postprocess
  • a913545 fix: get item for final score
  • cc681a3 tmp: testing per feature score
  • 634b2cf fix: factory class
  • 36db5df tests: median thresh tests
  • 777b5e2 fix: import
  • a075761 feat: add percentile thresholding
  • fbf171f fix: pipeline id keyerr in tools.py
  • add642c fix: pipeline id key error
  • dc35c80 try: better docker workflow
  • faf1e32 fix: default ml pipe id in preproc
  • 03faf8f fix: vae nsamples
  • 16c02f1 feat: add beta parameter for disentanglement
  • 5ec5883 feat: difference transform
  • 46363d3 feat: output threshold + final scores
  • 7f9317c feat: support loading nl conf
  • 3035407 feat: multivariate backtesting
  • c0596d7 add more logs
  • 3ca8c15 tmp: try exp mov average
  • 43c1ec8 feat: add transforms and robust thresholding
  • 19ddc8e Demo branch (#335)

Contributors

  • Avik Basu
  • Kushal Batra

v0.6.3 (2024-02-08)

  • 4dbde41 Fix: Get metrics from _conf.metrics on Trainer to avoid issue with Flattening the matrix (#346)

Contributors

  • shashank10456

v0.6.2 (2024-01-31)

  • 824a55d fix: add FlattenVector transformer (#344)
  • 146ec00 fix: add unified conf (#342)
  • 870f263 fix: take mean before calculating the thresholds (#340)
  • dbb510f fix: add max value map for cliping the value (#339)
  • 80ef431 "Source" tag for metrics (#338)
  • b292553 Add pl conf (#336)
  • 28fa28f Metrics (#322)

Contributors

  • Kushal Batra

v0.6.1.dev5 (2023-11-30)

  • dfc383a feat: support both base conf and app conf (#328)
  • 8b7f45f feat!: support full multivariate prometheus fetching (#325)

Contributors

  • Avik Basu

v0.6.1.dev4 (2023-11-21)

Contributors

  • Avik Basu

v0.6.1.dev3 (2023-11-21)

  • 5aa4c13 fix: use ckeys aligning with config in pre, post and inference vtx

Contributors

  • Avik Basu

v0.6.1.dev2 (2023-11-20)

Contributors

  • Avik Basu

v0.6.1.dev1 (2023-11-20)

  • 9d1b999 fix: send conf keys instead of request keys to trainer

Contributors

  • Avik Basu

v0.6.1.dev0 (2023-11-20)

  • 14e1a66 fix: mock method
  • 8369510 feat!: separate Prom trainer and Druid trainer
  • 7be6ddc add more tests
  • c783ba8 feat!: support mv query in fetch() method

Contributors

  • Avik Basu

v0.6.1.a9 (2024-01-20)

  • 870f263 fix: take mean before calculating the thresholds (#340)
  • dbb510f fix: add max value map for cliping the value (#339)
  • 80ef431 "Source" tag for metrics (#338)

Contributors

  • Kushal Batra

v0.6.1.a7 (2023-12-22)

Contributors

v0.6.1 (2024-01-29)

  • 146ec00 fix: add unified conf (#342)
  • 870f263 fix: take mean before calculating the thresholds (#340)
  • dbb510f fix: add max value map for cliping the value (#339)
  • 80ef431 "Source" tag for metrics (#338)
  • b292553 Add pl conf (#336)
  • 28fa28f Metrics (#322)
  • dfc383a feat: support both base conf and app conf (#328)
  • 8b7f45f feat!: support full multivariate prometheus fetching (#325)
  • c967f20 feat: support multivar prom (#317)
  • 46cdfcd add retrain logic for insufficient data (#321)
  • 0bbb53d doc: Update to fix examples ipynb files (#318)
  • 61f4575 chore!: unify and refactor trainer (#315)

Contributors

  • Avik Basu
  • Haripriya
  • Kushal Batra

v0.6.0rc0 (2023-10-12)

  • 9787b2d update version
  • a12948f chore!: unify and refactor trainer
  • 509e38a feat: support multivariate threshold output (#314)

Contributors

  • Avik Basu

v0.6.0a11 (2023-10-04)

  • 64c2e95 add: druidfetcher support for different configId (#307)

Contributors

  • Kushal Batra

v0.6.0a10 (2023-10-02)

Contributors

  • Kushal Batra

v0.6.0a9 (2023-10-02)

  • d7f9605 feat: update druid query context (#304)

Contributors

  • shrivardhan

v0.6.0a8 (2023-09-27)

  • a0e0ad0 fix: docker extra args error (#302)

Contributors

  • Avik Basu

v0.6.0a7 (2023-09-27)

  • dfab26e refactor druid connector (#301)
  • 2973dd2 feat: add dedup logic (#299)

Contributors

  • Kushal Batra
  • shrivardhan

v0.6.0a6 (2023-09-26)

Contributors

  • Kushal Batra

v0.6.0a5 (2023-09-22)

  • d249942 fix druid connector with tests (#296)

Contributors

  • shrivardhan

v0.6.0a4 (2023-09-20)

  • 98e376a fix: udf server start error (#294)

Contributors

  • Avik Basu

v0.6.0a3 (2023-09-19)

  • f55312b fix: pydruid version update (#293)

Contributors

  • Kushal Batra

v0.6.0a2 (2023-09-19)

Contributors

  • Kushal Batra

v0.6.0a1 (2023-09-19)

Contributors

v0.6.0 (2023-11-14)

  • 46cdfcd add retrain logic for insufficient data (#321)
  • 0bbb53d doc: Update to fix examples ipynb files (#318)
  • 61f4575 chore!: unify and refactor trainer (#315)
  • 509e38a feat: support multivariate threshold output (#314)
  • 64c2e95 add: druidfetcher support for different configId (#307)
  • f25f49a feat: add jitter (#305)
  • d7f9605 feat: update druid query context (#304)
  • a0e0ad0 fix: docker extra args error (#302)
  • dfab26e refactor druid connector (#301)
  • 2973dd2 feat: add dedup logic (#299)
  • fdec237 fix: trainer bug (#297)
  • d249942 fix druid connector with tests (#296)
  • 98e376a fix: udf server start error (#294)
  • f55312b fix: pydruid version update (#293)
  • 21f85f9 try : wfl (#290)
  • 3e89ccd fix: allow full df scores in backtest (#288)
  • bc1c627 feat: add multiple save for redis registry (#281)
  • a364721 feat: initial version of backtest tool (#282)
  • 0cdc257 feat: use well-defined dimensions instead of strings (#284)
  • de8930a feat!: numalogic udfs (#271)
  • c62c902 doc: update quick-start.md (#246)
  • 52a65c0 fix: improve metadata serialization (#244)
  • 8482c01 perf: improve serialization performance (#243)
  • 76cac48 fix: tensor dimension swap instead of view change (#240)
  • 2dfd84c feat: convolutional vae for multivariate time series (#237)
  • dc18442 feat: Multivariate threshold using Mahalanobis distance (#234)
  • 466681b feat: add thread safety to local cache (#224)

Contributors

  • Avik Basu
  • Haripriya
  • Jason Zesheng Chen
  • Kushal Batra
  • shrivardhan

v0.5.0.post1 (2023-07-10)

  • adebf98 feat: add thread safety to local cache (#224)

Contributors

  • Avik Basu

v0.5.0 (2023-07-06)

  • b21e246 fix (RedisRegistry): avoid overwriting cache with the same key during load (#223)
  • 0b0daed feat!: add dynamodb registry (#220)
  • dacae49 fix: dataset slicing (#222)
  • 7778ae8 fix: update production key to latest key (#221)
  • 4831180 examples: pipeline using block (#216)
  • 203c100 Upgraded python support for 3.11 (#211)
  • 9ebc32f feat!: introduce numalogic blocks (#206)
  • 4058811 fix: redis logging (#209)
  • b93bce5 fix: removing logger level setting (#205)
  • 6727296 fix: add caching logs (#203)
  • 4411aa7 examples: update with new numalogic and pynumaflow (#202)
  • 2298be4 chore!: refactor preproc and postproc into transforms module (#201)
  • 9e838ef fix: Sparse AE for vanilla and conv (#199)
  • 3193159 fix: registry test_case (#197)
  • efa1df7 chore!: Auto detect instance type while mlflow model save (#190)
  • 4a1effd feat: add redis caching (#179)
  • 0f7e6e0 fix: allow import from Registryconfig with optional dependencies (#180)
  • 6c21e95 fix: stale check; conf lazy imports (#178)
  • f1909a8 feat: redis registry (#170)
  • 794ddc6 feat: local memory artifact cache (#165)
  • 03514d6 chore!: drop support for python 3.8 (#164)
  • 73bbad2 feat: first benchmarking using KPI anomaly data (#163)
  • ed40681 feat: support weight decay in optimizers (#161)
  • cae88b3 chore!: use torch and lightning 2.0 (#159)

Contributors

  • Avik Basu
  • Kushal Batra
  • Miroslav Boussarov
  • Tarun Chawla

v0.4.1 (2023-06-20)

Contributors

  • Avik Basu

v0.4.0.post1 (2023-06-06)

  • b134fa2 fix: redis logging (#209)

Contributors

  • Kushal Batra

v0.4.0 (2023-06-06)

  • bd050c9 fix: removing logger level setting (#205)

Contributors

  • Kushal Batra

v0.4a1 (2023-06-02)

  • 1f5f458 fix: add caching logs (#203)
  • ce93191 examples: update with new numalogic and pynumaflow (#202)
  • fd169cf chore!: refactor preproc and postproc into transforms module (#201)
  • a2b00c1 fix: Sparse AE for vanilla and conv (#199)
  • 5e69f5f fix: registry test_case (#197)

Contributors

  • Avik Basu
  • Kushal Batra

v0.4a0 (2023-05-11)

  • 75aea49 chore!: Auto detect instance type while mlflow model save (#190)
  • e884b90 feat: add redis caching (#179)
  • 7834730 fix: allow import from Registryconfig with optional dependencies (#180)
  • 25a16f2 fix: stale check; conf lazy imports (#178)

Contributors

  • Avik Basu
  • Kushal Batra

v0.4.dev5 (2023-05-09)

  • 54cffe3 fix: optional dependency imports

Contributors

  • Avik Basu

v0.4.dev4 (2023-05-09)

  • 8086db1 fix: stale check; conf lazy imports (#178)
  • b664e49 Prerelease 0.4 (#173)
  • 85fb527 chore!: use torch and lightning 2.0

Contributors

  • Avik Basu

v0.3.8 (2023-04-18)

  • 3160c2b feat: exponential moving average postprocessing (#156)
  • 9de8e4c fix: validation loss not being logged (#155)

Contributors

  • Avik Basu

v0.3.7 (2023-03-27)

  • b61ac1f fix: Tanhscaler nan output for constant feature (#153)
  • 69006eb Update CODEOWNERS (#151)
  • 6b38465 feat: more generic convolutional ae (#149)

Contributors

  • Avik Basu
  • Vigith Maurice

v0.3.6 (2023-03-22)

  • cb5509a add: anomaly sign and return labels for anomalies generated (#146)
  • b6f63ef fix: latest model calling (#145)
  • 6ee3446 fix: transition (#144)

Contributors

  • Kushal Batra

v0.3.5 (2023-03-09)

  • ea01b44 feat: Sigmoid threshold (#141)

Contributors

  • Avik Basu

v0.3.4 (2023-03-03)

  • ec8401d feat: tanh preprocessing (#139)

Contributors

  • Avik Basu

v0.3.3 (2023-02-08)

  • 4eae629 fix!: consistency with threshold methods (#138)
  • 2ac1c2f feat: static threshold estimator (#136)
  • d3488c9 feat: initial config schema (#135)

Contributors

  • Avik Basu

v0.3.2 (2023-01-20)

Contributors

v0.3.1 (2023-01-12)

  • 2923718 fix: unbatch error on certain cases (#131)
  • 232302e fix: pin protobuf to v3.20 for pytorch-lightning (#130)
  • dca9a7a feat!: merge to release v0.3 (#119)
  • df20591 fix: sklearn base import for scikit learn v1.2 (#112)
  • d2c6293 fix: change example pipeline mlflow port (#96)
  • f9c74c9 fix: allow only patch updates in torch version due to cuda build errors on mac (#90)
  • 0a5fcdf fix_readme: mention namespace name when applying the pipeline (#88)

Contributors

  • Avik Basu
  • Kushal Batra

v0.3.0a1 (2022-12-22)

  • 88d26ec feat!: convert AE variants to lightning modules (#110)
  • ed94615 fix: fix and clean mlflow test cases (#109)

Contributors

  • Avik Basu
  • Kushal Batra

v0.3.0a0 (2022-12-08)

  • 78cf5b4 fix: fix pipeline for 0.3 release (#106)
  • 709553f fix: fix mlflow test cases (#98)
  • 701812e feat!: disentangle threshold selection from the main model (#89)

Contributors

  • Avik Basu
  • Kushal Batra

v0.3.0 (2023-01-05)

  • dca9a7a feat!: merge to release v0.3 (#119)

Contributors

  • Avik Basu

v0.2.10 (2023-01-06)

  • c00bb14 fix: Upgrade torch to 1.13.1 (#128)

Contributors

  • Avik Basu

v0.2.9 (2022-12-21)

  • df20591 fix: sklearn base import for scikit learn v1.2 (#112)

Contributors

  • Avik Basu

v0.2.8 (2022-11-29)

  • 7d5075d remove mlflow full
  • 05d6071 fix: have mlflow-server as an optional extra
  • 3c5bc83 fix: lock file
  • d2c6293 fix: change example pipeline mlflow port (#96)

Contributors

  • Avik Basu
  • Kushal Batra

v0.2.7 (2022-11-14)

  • f9c74c9 fix: allow only patch updates in torch version due to cuda build errors on mac (#90)
  • 0a5fcdf fix_readme: mention namespace name when applying the pipeline (#88)
  • 537fae5 fix: AutoencoderPipeline logged loss mean (#55)
  • 22f8e5d chore!: make mlflow as an optional dependency (#47)

Contributors

  • Avik Basu
  • Kushal Batra
  • diego-ponce

v0.2.6 (2022-10-17)

  • 5703d1b fix: update readme with optional mlflow dependency
  • 702f3b4 fix: install extras in workflows
  • 8969e80 chore!: make mlflow as an optional dependency
  • 9cc97cb feat: resume training parameter (#40)

Contributors

  • Avik Basu
  • Kushal Batra

v0.2.5 (2022-09-28)

Contributors

v0.2.4 (2022-09-21)

  • f0b0d3c fix: loading secondary artifacts (#16)
  • 0c506bd chore (#19)
  • c845d09 Update README.md
  • e8be7c5 fix: pypi auto publish workflow (#18)
  • fa22031 [Chore] Update README (#17)

Contributors

  • Avik Basu
  • Kushal Batra
  • Saradhi Sreegiriraju
  • Vigith Maurice
  • amitkalamkar

v0.2.3 (2022-08-16)

  • 6847211 workflows: add pypi publish and auto release generation (#14)
  • 040584f feat: adding feature for retaining fixed number of stale model (#13)

Contributors

  • Avik Basu
  • Kushal Batra

v0.2.2 (2022-08-03)

  • a5ef072 feat: Add support for storing preproc artifacts (scondary artifact) i… (#11)

Contributors

  • Kushal Batra

v0.2.1 (2022-07-21)

Contributors

v0.2.0 (2022-07-21)

  • 5314070 feat: add transformers model (#8)

Contributors

  • Kushal Batra