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getindata / kedro-kubeflow

Kedro Plugin to support running workflows on Kubeflow Pipelines
https://kedro-kubeflow.readthedocs.io
Apache License 2.0
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build(deps): bump kedro-mlflow from 0.11.1 to 0.11.8 #221

Closed dependabot[bot] closed 1 year ago

dependabot[bot] commented 1 year ago

Bumps kedro-mlflow from 0.11.1 to 0.11.8.

Release notes

Sourced from kedro-mlflow's releases.

Release 0.11.8

[0.11.8] - 2023-02-13

Added

  • :sparkles: Added support for Mlflow 2.0 (#390)

  • :sparkles: The modelify command now accepts a --run-name to specifiy the run name where the model is logged (#408)

Fixed

  • :memo: Update incorrect documentation about model registry with local relative filepath (#400)

  • :bug: The modelify command now creates a conda environment based on your environment python and kedro versions instead of hardcoded python=3.7 and kedro=0.16.5 (#405)

  • :bug: The modelify command now uses correctly the --pip-requirements argument instead of raising an error (#405)

  • :bug: The modelify command now uses modelify as a default run name (#408)

�

Release 0.11.7

[0.11.7] - 2023-01-28

Added

  • :sparkles: Added a MlflowModelRegistryDataSet in kedro_mlflow.io.models to enable fetching a mlflow model from the mlflow model registry by its name(#260)

Fixed

  • :bug: Use __default__ as a run name if the pipeline is not specified in the kedro run commmand to avoid empty names (#392)

�

Release 0.11.6

[0.11.6] - 2023-01-09

Changed

  • :sparkles: kedro-mlflow now uses the default configuration (ignoring mlflow.yml) if an active run already exists in the process where the pipeline is started, and uses this active run for logging. This enables using kedro-mlflow with an orchestrator which starts mlflow itself before running kedro (e.g. airflow, the mlflow run command, AzureML...) (#358)

�

Release 0.11.5

[0.11.5] - 2022-12-12

Added

  • :sparkles: Added an extra server.mlflow_registry_uri key in mlflow.yml to set the mlflow registry uri. (#260)
  • :sparkles: Add support for authorization with expiring tokens by adding an extra server.request_header_provider entry in mlflow.yml (#357)

... (truncated)

Changelog

Sourced from kedro-mlflow's changelog.

[0.11.8] - 2023-02-13

Added

  • :sparkles: Added support for Mlflow 2.0 (#390)

  • :sparkles: The modelify command now accepts a --run-name to specifiy the run name where the model is logged (#408)

Fixed

  • :memo: Update incorrect documentation about model registry with local relative filepath (#400)

  • :bug: The modelify command now creates a conda environment based on your environment python and kedro versions instead of hardcoded python=3.7 and kedro=0.16.5 (#405)

  • :bug: The modelify command now uses correctly the --pip-requirements argument instead of raising an error (#405)

  • :bug: The modelify command now uses modelify as a default run name (#408)

[0.11.7] - 2023-01-28

Added

  • :sparkles: Added a MlflowModelRegistryDataSet in kedro_mlflow.io.models to enable fetching a mlflow model from the mlflow model registry by its name(#260)

Fixed

  • :bug: Use __default__ as a run name if the pipeline is not specified in the kedro run commmand to avoid empty names (#392)

[0.11.6] - 2023-01-09

Changed

  • :sparkles: kedro-mlflow now uses the default configuration (ignoring mlflow.yml) if an active run already exists in the process where the pipeline is started, and uses this active run for logging. This enables using kedro-mlflow with an orchestrator which starts mlflow itself before running kedro (e.g. airflow, the mlflow run command, AzureML...) (#358)

[0.11.5] - 2022-12-12

Added

  • :sparkles: Added an extra server.mlflow_registry_uri key in mlflow.yml to set the mlflow registry uri. (#260)
  • :sparkles: Add support for authorization with expiring tokens by adding an extra server.request_header_provider entry in mlflow.yml (#357)

Fixed

  • :bug: MlflowArtifactDataSet.load() now correctly loads the artifact when both artifact_path and run_id arguments are specified. Previous fix in 0.11.4 did not work because when the file already exist locally, mlflow did not download it again so tests were incorrectly passing (#362)

Removed

  • :fire: :boom: Remove reload_kedro_mlflow line magic for notebook because kedro will deprecate the entrypoint in 0.18.3. It is still possible to access the mlflow client associated to the configuration in a notebook with context.mlflow.server._mlflow_client (#349). This is not considered as a breaking change since apparently no one uses it according to a discussion with kedro's team.

[0.11.4] - 2022-10-04

... (truncated)

Commits
  • 9df9c23 :rocket: Bump version and CHANGELOG for release 0.11.8 (#411)
  • 930e29e :memo: Fix changelog typo
  • 0f2957d :sparkles: :bug: Add a run_name argument in mlflow modelify command and use '...
  • 5be41ef :bug: Enable using pip-requirements in modelify command and use environments ...
  • d5fe84b :arrow_up: Update sphinx-rtd-theme requirement
  • 4888b0e :memo: Update documentation about model registry with local relative filepath...
  • a29814c Add support for Mlflow 2.0 (#390)
  • 5f93f5d :rocket: Bump version and CHANGELOG for release 0.11.7 (#397)
  • a4276b3 :sparkles: Add an MlflowModelRegistryDataSet to load from the mlflow model re...
  • ea271e9 :bug: Use 'default' as the mlflow run name when the pipeline is not speci...
  • Additional commits viewable in compare view


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dependabot[bot] commented 1 year ago

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