[tune](deps): Bump mlflow from 1.19.0 to 1.22.0 in /python/requirements/tune #12

dependabot · 2021-12-04T08:11:36Z

Bumps mlflow from 1.19.0 to 1.22.0.

Release notes

MLflow 1.22.0

1.22.0 (2021-11-29)

MLflow 1.22.0 includes several major features and improvements:

Features:

[UI] Add a share button to the Experiment page (#4936, @marijncv)

[UI] Improve readability of column sorting dropdown on Experiment page (#5022, @WeichenXu123; #5018, @NieuweNils, @coder-freestyle)

[Tracking] Mark all autologging integrations as stable by removing @experimental decorators (#5028, @liangz1)

[Tracking] Add optional experiment_id parameter to mlflow.set_experiment() (#5012, @dbczumar)

[Tracking] Add support for XGBoost scikit-learn models to mlflow.xgboost.autolog() (#5078, @jwyyy)

[Tracking] Improve statsmodels autologging performance by removing unnecessary metrics (#4942, @WeichenXu123)

[Tracking] Update R client to tag nested runs with parent run ID (#4197, @yitao-li)

[Models] Support saving and loading all XGBoost model types (#4954, @jwyyy)

[Scoring] Support specifying AWS account and role when deploying models to SageMaker (#4923, @andresionek91)

[Scoring] Support serving MLflow models with MLServer (#4963, @adriangonz)

Bug fixes and documentation updates:

[UI] Fix bug causing Metric Plot page to crash when metric values are too large (#4947, @ianshan0915)

[UI] Fix bug causing parallel coordinate curves to vanish (#5087, @harupy)

[UI] Remove Creator field from Model Version page if user information is absent (#5089, @jinzhang21)

[UI] Fix model loading instructions for non-pyfunc models in Artifact Viewer (#5006, @harupy)

[Models] Fix a bug that added mlflow to conda.yaml even if a hashed version was already present (#5058, @maitre-matt)

[Docs] Add Python documentation for metric, parameter, and tag key / value length limits (#4991, @westford14)

[Examples] Update Python version used in Prophet example to fix installation errors (#5101, @BenWilson2)

[Examples] Fix Kubernetes resources specification in MLflow Projects + Kubernetes example (#4948, @jianyuan)

Small bug fixes and doc updates (#5119, #5107, #5105, #5103, #5085, #5088, #5051, #5081, #5039, #5073, #5072, #5066, #5064, #5063, #5060, #4718, #5053, #5052, #5041, #5043, #5047, #5036, #5037, #5029, #5031, #5032, #5030, #5007, #5019, #5014, #5008, #4998, #4985, #4984, #4970, #4966, #4980, #4967, #4978, #4979, #4968, #4976, #4975, #4934, #4956, #4938, #4950, #4946, #4939, #4913, #4940, #4935, @harupy; #5095, #5070, #5002, #4958, #4945, @BenWilson2; #5099, @chaosddp; #5005, @you-n-g; #5042, #4952, @shrinath-suresh; #4962, #4995, @WeichenXu123; #5010, @lichenran1234; #5000, @wentinghu; #5111, @alexott; #5102, #5024, #5011, #4959, @dbczumar; #5075, #5044, #5026, #4997, #4964, #4989, @liangz1; #4999, @stevenchen-db)

MLflow 1.21.0 includes several major features and improvements:

Features:

[UI] Add a diff-only toggle to the runs table for filtering out columns with constant values (#4862, @marijncv)

[UI] Add a duration column to the runs table (#4840, @marijncv)

[UI] Display the default column sorting order in the runs table (#4847, @marijncv)

[UI] Add start_time and duration information to exported runs CSV (#4851, @marijncv)

[UI] Add lifecycle stage information to the run page (#4848, @marijncv)

[UI] Collapse run page sections by default for space efficiency, limit artifact previews to 50MB (#4917, @dbczumar)

[Tracking] Introduce autologging capabilities for PaddlePaddle model training (#4751, @jinminhao)

[Tracking] Add an optional tags field to the CreateExperiment API (#4788, @dbczumar; #4795, @apurva-koti)

[Tracking] Add support for deleting artifacts from SFTP stores via the mlflow gc CLI (#4670, @afaul)

[Tracking] Support AzureDefaultCredential for authenticating with Azure artifact storage backends (#4002, @marijncv)

[Models] Upgrade the fastai model flavor to support fastai V2 (>=2.4.1) (#4715, @jinzhang21)

[Models] Introduce an mlflow.prophet model flavor for Prophet time series models (#4773, @BenWilson2)

[Models] Introduce a CLI for publishing MLflow Models to the SageMaker Model Registry (#4669, @jinnig)

[Models] Print a warning when inferred model dependencies are not available on PyPI (#4891, @dbczumar)

[Models, Projects] Add MLFLOW_CONDA_CREATE_ENV_CMD for customizing Conda environment creation (#4746, @giacomov)

... (truncated)

Changelog

Sourced from mlflow's changelog.

1.22.0 (2021-11-29)

MLflow 1.22.0 includes several major features and improvements:

Features:

[UI] Add a share button to the Experiment page (#4936, @marijncv)

[UI] Improve readability of column sorting dropdown on Experiment page (#5022, @WeichenXu123; #5018, @NieuweNils, @coder-freestyle)

[Tracking] Mark all autologging integrations as stable by removing @experimental decorators (#5028, @liangz1)

[Tracking] Add optional experiment_id parameter to mlflow.set_experiment() (#5012, @dbczumar)

[Tracking] Add support for XGBoost scikit-learn models to mlflow.xgboost.autolog() (#5078, @jwyyy)

[Tracking] Improve statsmodels autologging performance by removing unnecessary metrics (#4942, @WeichenXu123)

[Tracking] Update R client to tag nested runs with parent run ID (#4197, @yitao-li)

[Models] Support saving and loading all XGBoost model types (#4954, @jwyyy)

[Scoring] Support specifying AWS account and role when deploying models to SageMaker (#4923, @andresionek91)

[Scoring] Support serving MLflow models with MLServer (#4963, @adriangonz)

Bug fixes and documentation updates:

[UI] Fix bug causing Metric Plot page to crash when metric values are too large (#4947, @ianshan0915)

[UI] Fix bug causing parallel coordinate curves to vanish (#5087, @harupy)

[UI] Remove Creator field from Model Version page if user information is absent (#5089, @jinzhang21)

[UI] Fix model loading instructions for non-pyfunc models in Artifact Viewer (#5006, @harupy)

[Models] Fix a bug that added mlflow to conda.yaml even if a hashed version was already present (#5058, @maitre-matt)

[Docs] Add Python documentation for metric, parameter, and tag key / value length limits (#4991, @westford14)

[Examples] Update Python version used in Prophet example to fix installation errors (#5101, @BenWilson2)

[Examples] Fix Kubernetes resources specification in MLflow Projects + Kubernetes example (#4948, @jianyuan)

Small bug fixes and doc updates (#5119, #5107, #5105, #5103, #5085, #5088, #5051, #5081, #5039, #5073, #5072, #5066, #5064, #5063, #5060, #4718, #5053, #5052, #5041, #5043, #5047, #5036, #5037, #5029, #5031, #5032, #5030, #5007, #5019, #5014, #5008, #4998, #4985, #4984, #4970, #4966, #4980, #4967, #4978, #4979, #4968, #4976, #4975, #4934, #4956, #4938, #4950, #4946, #4939, #4913, #4940, #4935, @harupy; #5095, #5070, #5002, #4958, #4945, @BenWilson2; #5099, @chaosddp; #5005, @you-n-g; #5042, #4952, @shrinath-suresh; #4962, #4995, @WeichenXu123; #5010, @lichenran1234; #5000, @wentinghu; #5111, @alexott; #5102, #5024, #5011, #4959, @dbczumar; #5075, #5044, #5026, #4997, #4964, #4989, @liangz1; #4999, @stevenchen-db)

1.21.0 (2021-10-23)

MLflow 1.21.0 includes several major features and improvements:

Features:

[UI] Add a diff-only toggle to the runs table for filtering out columns with constant values (#4862, @marijncv)

[UI] Add a duration column to the runs table (#4840, @marijncv)

[UI] Display the default column sorting order in the runs table (#4847, @marijncv)

[UI] Add start_time and duration information to exported runs CSV (#4851, @marijncv)

[UI] Add lifecycle stage information to the run page (#4848, @marijncv)

[UI] Collapse run page sections by default for space efficiency, limit artifact previews to 50MB (#4917, @dbczumar)

[Tracking] Introduce autologging capabilities for PaddlePaddle model training (#4751, @jinminhao)

[Tracking] Add an optional tags field to the CreateExperiment API (#4788, @dbczumar; #4795, @apurva-koti)

[Tracking] Add support for deleting artifacts from SFTP stores via the mlflow gc CLI (#4670, @afaul)

[Tracking] Support AzureDefaultCredential for authenticating with Azure artifact storage backends (#4002, @marijncv)

[Models] Upgrade the fastai model flavor to support fastai V2 (>=2.4.1) (#4715, @jinzhang21)

[Models] Introduce an mlflow.prophet model flavor for Prophet time series models (#4773, @BenWilson2)

[Models] Introduce a CLI for publishing MLflow Models to the SageMaker Model Registry (#4669, @jinnig)

[Models] Print a warning when inferred model dependencies are not available on PyPI (#4891, @dbczumar)

... (truncated)

Commits

eb087a7 Update MLflow version to 1.22.0 (#5123)
1ee77fc Update ML package versions (#5122)
77efe4b Replace searchPlaceholder with placeholder (#5119)
5381d68 Autologging functionality for scikit-learn integration with XGBoost (Part 2) ...
af8460f Fix list in documentation explaining priorities of Azure settings (#5111)
68e14f5 Move shell scripts in dev folder (#5107)
2d1c4b2 Define _get_class_from_string (#5105)
f5fec68 Add support for azure china (#5099)
258e028 Update PyPI package index for dependency resolution warnings (#5102)
5d3e3c8 Rename test-requirements.txt to dev-requirements.txt (#5103)
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Bumps [mlflow](https://github.com/mlflow/mlflow) from 1.19.0 to 1.22.0. - [Release notes](https://github.com/mlflow/mlflow/releases) - [Changelog](https://github.com/mlflow/mlflow/blob/master/CHANGELOG.rst) - [Commits](mlflow/mlflow@v1.19.0...v1.22.0) --- updated-dependencies: - dependency-name: mlflow dependency-type: direct:production update-type: version-update:semver-minor ... Signed-off-by: dependabot[bot] <[email protected]>

dependabot · 2021-12-16T16:40:28Z