Bump mlflow from 1.9.1 to 1.30.1

[dependabot]

Bumps mlflow from 1.9.1 to 1.30.1.

Release notes

Sourced from mlflow's releases.

MLflow 1.30.0

We are happy to announce the availability of MLflow 1.30.0!

MLflow 1.30.0 includes several major features and improvements

Features:

• [Pipelines] Introduce hyperparameter tuning support to MLflow Pipelines (#6859, @​prithvikannan)
• [Pipelines] Introduce support for prediction outlier comparison to training data set (#6991, @​jinzhang21)
• [Pipelines] Introduce support for recording all training parameters for reproducibility (#7026, #7094, @​prithvikannan)
• [Pipelines] Add support for Delta tables as a datasource in the ingest step (#7010, @​sunishsheth2009)
• [Pipelines] Add expanded support for data profiling up to 10,000 columns (#7035, @​prithvikanna)
• [Pipelines] Add support for AutoML in MLflow Pipelines using FLAML (#6959, @​mshtelma)
• [Pipelines] Add support for simplified transform step execution by allowing for unspecified configuration (#6909, @​apurva-koti)
• [Pipelines] Introduce a data preview tab to the transform step card (#7033, @​prithvikannan)
• [Tracking] Introduce run_name attribute for create_run, get_run and update_run APIs (#6782, #6798 @​apurva-koti)
• [Tracking] Add support for searching by creation_time and last_update_time for the search_experiments API (#6979, @​harupy)
• [Tracking] Add support for search terms run_id IN and run ID NOT IN for the search_runs API (#6945, @​harupy)
• [Tracking] Add support for searching by user_id and end_time for the search_runs API (#6881, #6880 @​subramaniam02)
• [Tracking] Add support for searching by run_name and run_id for the search_runs API (#6899, @​harupy; #6952, @​alexacole)
• [Tracking] Add support for synchronizing run name attribute and mlflow.runName tag (#6971, @​BenWilson2)
• [Tracking] Add support for signed tracking server requests using AWSSigv4 and AWS IAM (#7044, @​pdifranc)
• [Tracking] Introduce the update_run() API for modifying the status and name attributes of existing runs (#7013, @​gabrielfu)
• [Tracking] Add support for experiment deletion in the mlflow gc cli API (#6977, @​shaikmoeed)
• [Models] Add support for environment restoration in the evaluate() API (#6728, @​jerrylian-db)
• [Models] Remove restrictions on binary classification labels in the evaluate() API (#7077, @​dbczumar)
• [Scoring] Add support for BooleanType to mlflow.pyfunc.spark_udf() (#6913, @​BenWilson2)
• [SQLAlchemy] Add support for configurable Pool class options for SqlAlchemyStore (#6883, @​mingyu89)

Bug fixes:

• [Pipelines] Enable Pipeline subprocess commands to create a new SparkSession if one does not exist (#6846, @​prithvikannan)
• [Pipelines] Fix a rendering issue with bool column types in Step Card data profiles (#6907, @​sunishsheth2009)
• [Pipelines] Add validation and an exception if required step files are missing (#7067, @​mingyu89)
• [Pipelines] Change step configuration validation to only be performed during runtime execution of a step (#6967, @​prithvikannan)
• [Tracking] Fix infinite recursion bug when inferring the model schema in mlflow.pyspark.ml.autolog() (#6831, @​harupy)
• [UI] Remove the browser error notification when failing to fetch artifacts (#7001, @​kevingreer)
• [Models] Allow mlflow-skinny package to serve as base requirement in MLmodel requirements (#6974, @​BenWilson2)
• [Models] Fix an issue with code path resolution for loading SparkML models (#6968, @​dbczumar)
• [Models] Fix an issue with dependency inference in logging SparkML models (#6912, @​BenWilson2)
• [Models] Fix an issue involving potential duplicate downloads for SparkML models (#6903, @​serena-ruan)
• [Models] Add missing pos_label to sklearn.metrics.precision_recall_curve in mlflow.evaluate() (#6854, @​dbczumar)
• [SQLAlchemy] Fix a bug in SqlAlchemyStore where set_tag() updates the incorrect tags (#7027, @​gabrielfu)

Documentation updates:

• [Models] Update details regarding the default Keras serialization format (#7022, @​balvisio)

Small bug fixes and documentation updates:

... (truncated)

Changelog

Sourced from mlflow's changelog.

CHANGELOG

2.5.0 (2023-07-17)

MLflow 2.5.0 includes several major features and improvements:

• [MLflow AI Gateway] We are excited to announce the release of MLflow AI Gateway, a powerful tool designed to streamline the usage and management of various large language model (LLM) providers, such as OpenAI and Anthropic, within an organization. It offers a standardized interface that simplifies the interaction with these services and delivers centralized, secure management of credentials. To get started with MLflow AI Gateway, check out the docs at https://mlflow.org/docs/latest/gateway/index.html. (#8694, @​harupy, @​BenWilson2, @​dbczumar)
• [Auth]: We are excited to announce the release of authentication and authorization support for MLflow Tracking and the MLflow Model Registry, providing integrated access control capabilities to both services. To get started, check out the docs at https://mlflow.org/docs/latest/auth/index.html. (#9000, #8975, #8626, #8837, #8841, @​gabrielfu, @​harupy)

Features:

• [Models] Add Support to the LangChain flavor for chains that contain unserializable components (#8736, @​liangz1)
• [Scoring] Infer spark udf return type from model output schema (#8934, @​WeichenXu123)
• [Models] Add support for automated signature inference (#8860, #8782 #8795, #8725, @​jerrylian-db)

Bug fixes:

• [Security] Improve robustness to LFI attacks on Windows by enhancing path validation (#8999, @​serena-ruan)
  • If you are using mlflow server or mlflow ui on Windows, we recommend upgrading to MLflow 2.5.0 as soon as possible.
• [Scoring] Support nullable array type values as spark_udf return values (#9014, @​WeichenXu123)
• [Models] Revert cache deletion of system modules when adding custom model code to the system path (#8722, @​trungn1)
• [Models] add micro version to mlflow version pinning (#8687, @​C-K-Loan)
• [Artifacts] Prevent manually deleted artifacts from causing artifact garbage collection to fail (#8498, @​PenHsuanWang)

Documentation updates:

• [Docs] Update .push_model_to_sagemaker docs (#8851, @​pdifranc)
• [Docs] Fix invalid link for Azure ML documentation (#8800, @​dunnkers)
• [Artifacts / Docs / Models / Projects] Adds information on the OCI MLflow plugins for seamless integration with Oralce Cloud Infrastructure services. (#8707, @​mrDzurb)

Deprecation:

• [Models] Deprecate the gluon model flavor. The mlflow.gluon module will be removed in a future release. (#8968, @​harupy)

Small bug fixes and documentation updates:

#9069, #9056, #9055, #9054, #9048, #9043, #9035, #9034, #9037, #9038, #8993, #8966, #8985, @​BenWilson2; #9039, #9036, #8902, #8924, #8866, #8861, #8810, #8761, #8544, @​jerrylian-db; #8903, @​smurching; #9080, #9079, #9078, #9076, #9075, #9074, #9071, #9063, #9062, #9032, #9031, #9027, #9023, #9022, #9020, #9005, #8994, #8979, #8983, #8984, #8982, #8970, #8962, #8969, #8968, #8959, #8960, #8958, #8956, #8955, #8954, #8949, #8950, #8952, #8948, #8946, #8947, #8943, #8944, #8916, #8917, #8933, #8929, #8932, #8927, #8930, #8925, #8921, #8873, #8915, #8909, #8908, #8911, #8910, #8907, #8906, #8898, #8893, #8889, #8892, #8891, #8887, #8875, #8876, #8882, #8874, #8868, #8872, #8869, #8828, #8852, #8857, #8853, #8854, #8848, #8850, #8840, #8835, #8832, #8831, #8830, #8829, #8839, #8833, #8838, #8819, #8814, #8825, #8818, #8787, #8775, #8749, #8766, #8756, #8753, #8751, #8748, #8744, #8731, #8717, #8730, #8691, #8720, #8723, #8719, #8688, #8721, #8715, #8716, #8718, #8696, #8698, #8692, #8693, #8690, @​harupy; #9030, @​AlimurtuzaCodes; #9029, #9025, #9021, #9013, @​viktoriussuwandi; #9010, @​Bncer; #9011, @​Pecunia201; #9007, #9003, @​EdAbati; #9002, @​prithvikannan; #8991, #8867, @​AveshCSingh; #8951, #8896, #8888, #8849, @​gabrielfu; #8913, #8885, #8871, #8870, #8788, #8772, #8771, @​serena-ruan; #8879, @​maciejskorski; #7752, @​arunkumarkota; #9083, #9081, #8765, #8742, #8685, #8682, #8683, @​dbczumar; #8791, @​mhattingpete; #8739, @​yunpark93

2.4.2 (2023-07-10)

MLflow 2.4.2 is a patch release containing the following bug fixes and changes:

Bug fixes:

• [Models] Add compatibility for legacy transformers serialization (#8964, @​BenWilson2)
• [Models] Fix downloading MLmodel files from alias-based models:/ URIs (#8764, @​smurching)
• [Models] Fix reading model flavor config from URI for models in UC (#8728, @​smurching)
• [Models] Support feature_deps in ModelVersion creation for UC (#8867, #8815, @​AveshCSingh)
• [Models] Add support for listing artifacts in UC model registry artifact repo (#8803, @​smurching)
• [Core] Include resources for recipes in mlflow-skinny (#8895, @​harupy)

... (truncated)

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