build(deps): bump mlflow from 1.28.0 to 1.30.0

Bumps mlflow from 1.28.0 to 1.30.0.

Release notes

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.

1.30.0 (2022-10-19)

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:

#7093, #7095, #7092, #7064, #7049, #6921, #6920, #6940, #6926, #6923, #6862, @jerrylian-db; #6946, #6954, #6938, @mingyu89; #7047, #7087, #7056, #6936, #6925, #6892, #6860, #6828, @sunishsheth2009; #7061, #7058, #7098, #7071, #7073, #7057, #7038, #7029, #6918, #6993, #6944, #6976, #6960, #6933, #6943, #6941, #6900, #6901, #6898, #6890, #6888, #6886, #6887, #6885, #6884, #6849, #6835, #6834, @harupy; #7094, #7065, #7053, #7026, #7034, #7021, #7020, #6999, #6998, #6996, #6990, #6989, #6934, #6924, #6896, #6895, #6876, #6875, #6861, @prithvikannan; #7081, #7030, #7031, #6965, #6750, @bbarnes52; #7080, #7069, #7051, #7039, #7012, #7004, @dbczumar; #7054, @jinzhang21; #7055, #7037, #7036, #6949, #6951, @apurva-koti; #6815, @michaguenther; #6897, @chaturvedakash; #7025, #6981, #6950, #6948, #6937, #6829, #6830, @BenWilson2; #6982, @vadim; #6985, #6927, @kriscon-db; #6917, #6919, #6872, #6855, @WeichenXu123; #6980, @utkarsh867; #6973, #6935, @wentinghu; #6930, @mingyangge-db; #6956, @RohanBha1; #6916, @av-maslov; #6824, @shrinath-suresh; #6732, @oojo12; #6807, @ikrizanic; #7066, @subramaniam20jan; #7043, @AvikantSrivastava; #6879, @jspablo

... (truncated)

Commits

d975b5a Update MLflow version to 1.30.0 (#7115)
8ed7f78 Improve model validation docs (#7093)
72c1890 Add type checks to validation_thresholds parameter (#7095)
b106f0d Update requirements.yaml files (#7111)
33bf47e Run python3 dev/update_ml_package_versions.py (#7110)
e012b66 Run python3 dev/update_pypi_package_index.py (#7109)
16cb9d6 mlflow.evaluate(): allow arbitrary positive labels (#7077)
398fe53 Throw exception if not all required step files are present (#7067)
5d8319c Adding validation for ingest and split step (#7047)
34b23d7 Replace deprecated sqlalchemy features that will be removed in sqlalchemy 2.0...
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getindata / kedro-kubeflow

build(deps): bump mlflow from 1.28.0 to 1.30.0 #194

MLflow 1.30.0

1.30.0 (2022-10-19)