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combinator-ml / terraform-k8s-mlflow

MLflow terraform module
Apache License 2.0
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chore(deps): bump mlflow[extras] from 1.19.0 to 1.21.0 in /docker #18

Closed dependabot[bot] closed 3 years ago

dependabot[bot] commented 3 years ago

Bumps mlflow[extras] from 1.19.0 to 1.21.0.

Release notes

Sourced from mlflow[extras]'s releases.

MLflow 1.20.2 is a patch release containing the following features and bug fixes:

Features:

  • Enabled auto dependency inference in spark flavor in autologging (#4759, @​harupy)

Bug fixes and documentation updates:

  • Increased MLflow client HTTP request timeout from 10s to 120s (#4764, @​jinzhang21)
  • Fixed autologging compatibility bugs with TensorFlow and Keras version 2.6.0 (#4766, @​dbczumar)

Small bug fixes and doc updates (#4770, @​WeichenXu123)

MLflow 1.20.1

Note: The MLflow R package for 1.20.1 is not yet available but will be in a week because CRAN's submission system will be offline until September 1st.

MLflow 1.20.1 is a patch release for the MLflow Python and R packages containing the following bug fixes:

  • Avoid calling importlib_metadata.packages_distributions upon mlflow.utils.requirements_utils import (#4741, @​dbczumar)
  • Avoid depending on importlib_metadata==4.7.0 (#4740, @​dbczumar)

MLflow 1.20.0

Note: The MLflow R package for 1.20.0 is not yet available but will be in a week because CRAN's submission system will be offline until September 1st.

MLflow 1.20.0 includes several major features and improvements:

Features:

  • Autologging for scikit-learn now records post training metrics when scikit-learn evaluation APIs, such as sklearn.metrics.mean_squared_error, are called (#4491, #4628 #4638, @​WeichenXu123)
  • Autologging for PySpark ML now records post training metrics when model evaluation APIs, such as Evaluator.evaluate(), are called (#4686, @​WeichenXu123)
  • Add pip_requirements and extra_pip_requirements to mlflow.*.log_model and mlflow.*.save_model for directly specifying the pip requirements of the model to log / save (#4519, #4577, #4602, @​harupy)
  • Added stdMetrics entries to the training metrics recorded during PySpark CrossValidator autologging (#4672, @​WeichenXu123)
  • MLflow UI updates:
    1. Improved scalability of the parallel coordinates plot for run performance comparison,
    2. Added support for filtering runs based on their start time on the experiment page,
    3. Added a dropdown for runs table column sorting on the experiment page,
    4. Upgraded the AG Grid plugin, which is used for runs table loading on the experiment page, to version 25.0.0,
    5. Fixed a bug on the experiment page that caused the metrics section of the runs table to collapse when selecting columns from other table sections (#4712, @​dbczumar)
  • Added support for distributed execution to autologging for PyTorch Lightning (#4717, @​dbczumar)
  • Expanded R support for Model Registry functionality (#4527, @​bramrodenburg)
  • Added model scoring server support for defining custom prediction response wrappers (#4611, @​Ark-kun)
  • mlflow.*.log_model and mlflow.*.save_model now automatically infer the pip requirements of the model to log / save based on the current software environment (#4518, @​harupy)
  • Introduced support for running Sagemaker Batch Transform jobs with MLflow Models (#4410, #4589, @​YQ-Wang)

Bug fixes and documentation updates:

  • Deprecate requirements_file argument for mlflow.*.save_model and mlflow.*.log_model (#4620, @​harupy)
  • set nextPageToken to null (#4729, @​harupy)
  • Fix a bug in MLflow UI where the pagination token for run search is not refreshed when switching experiments (#4709, @​harupy)
  • Fix a bug in the model scoring server that rejected requests specifying a valid Content-Type header with the charset parameter (#4609, @​Ark-kun)

... (truncated)

Changelog

Sourced from mlflow[extras]'s changelog.

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

Bug fixes and documentation updates:

  • [UI] Fix an issue where column selections made in the runs table were persisted across experiments (#4926, @​sunishsheth2009)
  • [UI] Fix an issue where the text null was displayed in the runs table column ordering dropdown (#4924, @​harupy)
  • [UI] Fix a bug causing the metric plot view to display NaN values upon click (#4858, @​arpitjasa-db)
  • [Tracking] Fix a model load failure for paths containing spaces or special characters on UNIX systems (#4890, @​BenWilson2)
  • [Tracking] Correct a migration issue that impacted usage of MLflow Tracking with SQL Server (#4880, @​marijncv)
  • [Tracking] Spark datasource autologging tags now respect the maximum allowable size for MLflow Tracking (#4809, @​dbczumar)
  • [Model Registry] Add previously-missing certificate sources for Model Registry REST API requests (#4731, @​ericgosno91)
  • [Model Registry] Throw an exception when users supply invalid Model Registry URIs for Databricks (#4877, @​yunpark93)
  • [Scoring] Fix a schema enforcement error that incorrectly cast date-like strings to datetime objects (#4902, @​wentinghu)
  • [Docs] Expand the documentation for the MLflow Skinny Client (#4113, @​eedeleon)

Small bug fixes and doc updates (#4928, #4919, #4927, #4922, #4914, #4899, #4893, #4894, #4884, #4864, #4823, #4841, #4817, #4796, #4797, #4767, #4768, #4757, @​harupy; #4863, #4838, @​marijncv; #4834, @​ksaur; #4772, @​louisguitton; #4801, @​twsl; #4929, #4887, #4856, #4843, #4789, #4780, @​WeichenXu123; #4769, @​Ark-kun; #4898, #4756, @​apurva-koti; #4784, @​lakshikaparihar; #4855, @​ianshan0915; #4790, @​eedeleon; #4931, #4857, #4846, 4777, #4748, @​dbczumar)

1.20.2 (2021-09-03)

MLflow 1.20.2 is a patch release containing the following features and bug fixes:

Features:

  • Enabled auto dependency inference in spark flavor in autologging (#4759, @​harupy)

Bug fixes and documentation updates:

  • Increased MLflow client HTTP request timeout from 10s to 120s (#4764, @​jinzhang21)
  • Fixed autologging compatibility bugs with TensorFlow and Keras version 2.6.0 (#4766, @​dbczumar)

... (truncated)

Commits
  • e0a0300 Update MLflow version to 1.21.0 (#4932)
  • 290bf3d [ALL TESTS] Update (#4930)
  • f01ac91 Revert "Add support to serve MLflow models through MLServer (#4845)" (#4931)
  • 093ee6e Add support to serve MLflow models through MLServer (#4845)
  • 0b39aca Set globally_configured flag correctly for spark and pyspark.ml autologging i...
  • 233ab7f Specify datamodule in pytorch lightning tests (#4928)
  • 380e2ba Avoid using defaults conda channel and use conda-forge instead (#4919)
  • bec12da Persist preSwitchCategorizedUncheckedKeys and `postSwitchCategorizedUncheck...
  • 68067c2 Support filtering runs by start_time (#4922)
  • e119988 MLflow UI updates (#4917)
  • Additional commits viewable in compare view


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