Bump mlflow from 1.2.0 to 1.23.1 in /mlflow/wip/ratings/build-base

[dependabot[bot]]

Bumps mlflow from 1.2.0 to 1.23.1.

Release notes

Sourced from mlflow's releases.

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.