Bump mlflow from 1.19.0 to 1.23.1

dependabot[bot] commented 2 years ago

Bumps mlflow from 1.19.0 to 1.23.1.

Release notes

MLflow 1.23.1 is a patch release containing the following bug fixes:

[Models] Fix a directory creation failure when loading PySpark ML models (#5299, @arjundc-db)

[Model Registry] Revert to using case-insensitive validation logic for stage names in models:/ URIs (#5312, @lichenran1234)

[Projects] Fix a race condition during Project tar file creation (#5303, @dbczumar)

Note: Version 1.23.1 of the MLflow R package has not yet been released. It will be available on CRAN within the next week.

MLflow 1.23.0 includes several major features and improvements:

Note: Version 1.23.0 of the MLflow R package has not yet been released. It will be available on CRAN within the next week.

Features:

[Models] Introduce an mlflow.evaluate() API for evaluating MLflow Models, providing performance and explainability insights. For an overview, see https://mlflow.org/docs/latest/models.html#model-evaluation (#5069, #5092, #5256, @WeichenXu123)

[Models] log_model() APIs now return information about the logged MLflow Model, including artifact location, flavors, and schema (#5230, @liangz1)

[Models] Introduce an mlflow.models.Model.load_input_example() Python API for loading MLflow Model input examples (#5212, @maitre-matt)

[Models] Add a UUID field to the MLflow Model specification. MLflow Models now have a unique identifier (#5149, #5167, @WeichenXu123)

[Models] Support passing SciPy CSC and CSR matrices as MLflow Model input examples (#5016, @WeichenXu123)

[Model Registry] Support specifying latest in model URI to get the latest version of a model regardless of the stage (#5027, @lichenran1234)

[Tracking] Add support for LightGBM scikit-learn models to mlflow.lightgbm.autolog() (#5130, #5200, #5271 @jwyyy)

[Tracking] Improve S3 artifact download speed by caching boto clients (#4695, @Samreay)

[UI] Automatically update metric plots for in-progress runs (#5017, @cedkoffeto, @harupy)

Bug fixes and documentation updates:

[Models] Fix a bug in MLflow Model schema enforcement where strings were incorrectly cast to Pandas objects (#5134, @stevenchen-db)

[Models] Fix a bug where keyword arguments passed to mlflow.pytorch.load_model() were not applied for scripted models (#5163, @schmidt-jake)

[Model Registry][r] Fix bug in R client mlflow_create_model_version() API that caused model source to be set incorrectly (#5185, @bramrodenburg)

[Projects] Fix parsing behavior for Project URIs containing quotes (#5117, @dinaldoap)

[Scoring] Use the correct 400-level error code for malformed MLflow Model Server requests (#5003, @abatomunkuev)

[Tracking] Fix a bug where mlflow.start_run() modified user-supplied tags dictionary (#5191, @matheusMoreno)

[UI] Fix a bug causing redundant scroll bars to be displayed on the Experiment Page (#5159, @sunishsheth2009)

Small bug fixes and doc updates (#5275, #5264, #5244, #5249, #5255, #5248, #5243, #5240, #5239, #5232, #5234, #5235, #5082, #5220, #5219, #5226, #5217, #5194, #5188, #5132, #5182, #5183, #5180, #5177, #5165, #5164, #5162, #5015, #5136, #5065, #5125, #5106, #5127, #5120, @harupy; #5045, @BenWilson2; #5156, @pbezglasny; #5202, @jwyyy; #3863, @JoshuaAnickat; #5205, @abhiramr; #4604, @OSobky; #4256, @einsmein; #5140, @AveshCSingh; #5273, #5186, #5176, @WeichenXu123; #5260, #5229, #5206, #5174, #5160, @liangz1)

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)

... (truncated)

Changelog

Sourced from mlflow's changelog.

1.23.1 (2022-01-27)

MLflow 1.23.1 is a patch release containing the following bug fixes:

[Models] Fix a directory creation failure when loading PySpark ML models (#5299, @arjundc-db)

[Model Registry] Revert to using case-insensitive validation logic for stage names in models:/ URIs (#5312, @lichenran1234)

[Projects] Fix a race condition during Project tar file creation (#5303, @dbczumar)

1.23.0 (2022-01-17)

MLflow 1.23.0 includes several major features and improvements:

Features:

[Models] Introduce an mlflow.evaluate() API for evaluating MLflow Models, providing performance and explainability insights. For an overview, see https://mlflow.org/docs/latest/models.html#model-evaluation (#5069, #5092, #5256, @WeichenXu123)

[Models] log_model() APIs now return information about the logged MLflow Model, including artifact location, flavors, and schema (#5230, @liangz1)

[Models] Introduce an mlflow.models.Model.load_input_example() Python API for loading MLflow Model input examples (#5212, @maitre-matt)

[Models] Add a UUID field to the MLflow Model specification. MLflow Models now have a unique identifier (#5149, #5167, @WeichenXu123)

[Models] Support passing SciPy CSC and CSR matrices as MLflow Model input examples (#5016, @WeichenXu123)

[Model Registry] Support specifying latest in model URI to get the latest version of a model regardless of the stage (#5027, @lichenran1234)

[Tracking] Add support for LightGBM scikit-learn models to mlflow.lightgbm.autolog() (#5130, #5200, #5271 @jwyyy)

[Tracking] Improve S3 artifact download speed by caching boto clients (#4695, @Samreay)

[UI] Automatically update metric plots for in-progress runs (#5017, @cedkoffeto, @harupy)

Bug fixes and documentation updates:

[Models] Fix a bug in MLflow Model schema enforcement where strings were incorrectly cast to Pandas objects (#5134, @stevenchen-db)

[Models] Fix a bug where keyword arguments passed to mlflow.pytorch.load_model() were not applied for scripted models (#5163, @schmidt-jake)

[Model Registry][R] Fix bug in R client mlflow_create_model_version() API that caused model source to be set incorrectly (#5185, @bramrodenburg)

[Projects] Fix parsing behavior for Project URIs containing quotes (#5117, @dinaldoap)

[Scoring] Use the correct 400-level error code for malformed MLflow Model Server requests (#5003, @abatomunkuev)

[Tracking] Fix a bug where mlflow.start_run() modified user-supplied tags dictionary (#5191, @matheusMoreno)

[UI] Fix a bug causing redundant scroll bars to be displayed on the Experiment Page (#5159, @sunishsheth2009)

Small bug fixes and doc updates (#5275, #5264, #5244, #5249, #5255, #5248, #5243, #5240, #5239, #5232, #5234, #5235, #5082, #5220, #5219, #5226, #5217, #5194, #5188, #5132, #5182, #5183, #5180, #5177, #5165, #5164, #5162, #5015, #5136, #5065, #5125, #5106, #5127, #5120, @harupy; #5045, @BenWilson2; #5156, @pbezglasny; #5202, @jwyyy; #3863, @JoshuaAnickat; #5205, @abhiramr; #4604, @OSobky; #4256, @einsmein; #5140, @AveshCSingh; #5273, #5186, #5176, @WeichenXu123; #5260, #5229, #5206, #5174, #5160, @liangz1)

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)

... (truncated)

Commits

1fd9b52 Update MLflow version to 1.23.1 (#5324)
eab972d python dev/update_ml_package_versions.py (#5323)
5387dd3 python dev/update_pypi_package_index.py (#5322)
fced3a4 Fix loading a spark model on databricks (#5299)
61984e6 Use mkstemp to replace deprecated mktemp call (#5303)
271750b Fix the bug of stages in models URI being case-sensitive (#5312)
86ad040 Update MLflow version to 1.23.0 (#5279)
f2dc157 python dev/update_pypi_package_index.py (#5280)
9ef881f python dev/update_ml_package_versions.py (#5278)
043108c Changelog for MLflow 1.23 (#5270)
Additional commits viewable in compare view

Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.

Dependabot commands and options

You can trigger Dependabot actions by commenting on this PR: - `@dependabot rebase` will rebase this PR - `@dependabot recreate` will recreate this PR, overwriting any edits that have been made to it - `@dependabot merge` will merge this PR after your CI passes on it - `@dependabot squash and merge` will squash and merge this PR after your CI passes on it - `@dependabot cancel merge` will cancel a previously requested merge and block automerging - `@dependabot reopen` will reopen this PR if it is closed - `@dependabot close` will close this PR and stop Dependabot recreating it. You can achieve the same result by closing it manually - `@dependabot ignore this major version` will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself) - `@dependabot ignore this minor version` will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself) - `@dependabot ignore this dependency` will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself) - `@dependabot use these labels` will set the current labels as the default for future PRs for this repo and language - `@dependabot use these reviewers` will set the current reviewers as the default for future PRs for this repo and language - `@dependabot use these assignees` will set the current assignees as the default for future PRs for this repo and language - `@dependabot use this milestone` will set the current milestone as the default for future PRs for this repo and language You can disable automated security fix PRs for this repo from the [Security Alerts page](https://github.com/AICoE/prometheus-anomaly-detector/network/alerts).