Update mlflow requirement from <1.28.0,>=1.0.0 to >=1.0.0,<1.29.0 in /requirements #14311

dependabot · 2022-08-19T05:14:50Z

Updates the requirements on mlflow to permit the latest version.

Release notes

MLflow 1.28.0 includes several major features and improvements:

Features:

[Pipelines] Log the full Pipeline runtime configuration to MLflow Tracking during Pipeline execution (#6359, @jinzhang21)

[Pipelines] Add pipeline.yaml configurations to specify the Model Registry backend used for model registration (#6284, @sunishsheth2009)

[Pipelines] Support optionally skipping the transform step of the scikit-learn regression pipeline (#6362, @sunishsheth2009)

[Pipelines] Add UI links to Runs and Models in Pipeline Step Cards on Databricks (#6294, @dbczumar)

[Tracking] Introduce mlflow.search_experiments() API for searching experiments by name and by tags (#6333, @WeichenXu123; #6227, #6172, #6154, @harupy)

[Tracking] Increase the maximum parameter value length supported by File and SQL backends to 500 characters (#6358, @johnyNJ)

[Tracking] Introduce an --older-than flag to mlflow gc for removing runs based on deletion time (#6354, @Jason-CKY)

[Tracking] Add MLFLOW_SQLALCHEMYSTORE_POOL_RECYCLE environment variable for recycling SQLAlchemy connections (#6344, @postrational)

[UI] Display deeply nested runs in the Runs Table on the Experiment Page (#6065, @tospe)

[UI] Add box plot visualization for metrics to the Compare Runs page (#6308, @ahlag)

[UI] Display tags on the Compare Runs page (#6164, @CaioCavalcanti)

[UI] Use scientific notation for axes when viewing metric plots in log scale (#6176, @RajezMariner)

[UI] Add button to Metrics page for downloading metrics as CSV (#6048, @rafaelvp-db)

[UI] Include NaN and +/- infinity values in plots on the Metrics page (#6422, @hubertzub-db)

[Tracking / Model Registry] Introduce environment variables to control retry behavior and timeouts for REST API requests (#5745, @peterdhansen)

[Tracking / Model Registry] Make MlflowClient importable as mlflow.MlflowClient (#6085, @subramaniam02)

[Model Registry] Add support for searching registered models and model versions by tags (#6413, #6411, #6320, @WeichenXu123)

[Model Registry] Add stage parameter to set_model_version_tag() (#6185, @subramaniam02)

[Model Registry] Add --registry-store-uri flag to mlflow server for specifying the Model Registry backend URI (#6142, @Secbone)

[Models] Improve performance of Spark Model logging on Databricks (#6282, @bbarnes52)

[Models] Include Pandas Series names in inferred model schemas (#6361, @RynoXLI)

[Scoring] Make model_uri optional in mlflow models build-docker to support building generic model serving images (#6302, @harupy)

[R] Support logging of NA and NaN parameter values (#6263, @nathaneastwood)

Bug fixes and documentation updates:

[Pipelines] Improve scikit-learn regression pipeline latency by limiting dataset profiling to the first 100 columns (#6297, @sunishsheth2009)

[Pipelines] Use xdg-open instead of open for viewing Pipeline results on Linux systems (#6326, @strangiato)

[Pipelines] Fix a bug that skipped Step Card rendering in Jupyter Notebooks (#6378, @apurva-koti)

[Tracking] Use the 401 HTTP response code in authorization failure REST API responses, instead of 500 (#6106, @balvisio)

[Tracking] Correctly classify artifacts as files and directories when using Azure Blob Storage (#6237, @nerdinand)

[Tracking] Fix a bug in the File backend that caused run metadata to be lost in the event of a failed write (#6388, @dbczumar)

[Tracking] Adjust mlflow.pyspark.ml.autolog() to only log model signatures for supported input / output data types (#6365, @harupy)

[Tracking] Adjust mlflow.tensorflow.autolog() to log TensorFlow early stopping callback info when log_models=False is specified (#6170, @WeichenXu123)

[Tracking] Fix signature and input example logging errors in mlflow.sklearn.autolog() for models containing transformers (#6230, @dbczumar)

[Tracking] Fix a failure in mlflow gc that occurred when removing a run whose artifacts had been previously deleted (#6165, @dbczumar)

[Tracking] Add missing sqlparse library to MLflow Skinny client, which is required for search support (#6174, @dbczumar)

[Tracking / Model Registry] Fix an mlflow server bug that rejected parameters and tags with empty string values (#6179, @dbczumar)

[Model Registry] Fix a failure preventing model version schemas from being downloaded with --serve-arifacts enabled (#6355, @abbas123456)

[Scoring] Patch the Java Model Server to support MLflow Models logged on recent versions of the Databricks Runtime (#6337, @dbczumar)

[Scoring] Verify that either the deployment name or endpoint is specified when invoking the mlflow deployments predict CLI (#6323, @dbczumar)

[Scoring] Properly encode datetime columns when performing batch inference with mlflow.pyfunc.spark_udf() (#6244, @harupy)

[Projects] Fix an issue where local directory paths were misclassified as Git URIs when running Projects (#6218, @ElefHead)

[R] Fix metric logging behavior for +/- infinity values (#6271, @nathaneastwood)

[Docs] Move Python API docs for MlflowClient from mlflow.tracking to mlflow.client (#6405, @dbczumar)

[Docs] Document that MLflow Pipelines requires Make (#6216, @dbczumar)

... (truncated)

Changelog

Sourced from mlflow's changelog.

1.28.0 (2022-08-09)

MLflow 1.28.0 includes several major features and improvements:

Features:

[Pipelines] Log the full Pipeline runtime configuration to MLflow Tracking during Pipeline execution (#6359, @jinzhang21)

[Pipelines] Add pipeline.yaml configurations to specify the Model Registry backend used for model registration (#6284, @sunishsheth2009)

[Pipelines] Support optionally skipping the transform step of the scikit-learn regression pipeline (#6362, @sunishsheth2009)

[Pipelines] Add UI links to Runs and Models in Pipeline Step Cards on Databricks (#6294, @dbczumar)

[Tracking] Introduce mlflow.search_experiments() API for searching experiments by name and by tags (#6333, @WeichenXu123; #6227, #6172, #6154, @harupy)

[Tracking] Increase the maximum parameter value length supported by File and SQL backends to 500 characters (#6358, @johnyNJ)

[Tracking] Introduce an --older-than flag to mlflow gc for removing runs based on deletion time (#6354, @Jason-CKY)

[Tracking] Add MLFLOW_SQLALCHEMYSTORE_POOL_RECYCLE environment variable for recycling SQLAlchemy connections (#6344, @postrational)

[UI] Display deeply nested runs in the Runs Table on the Experiment Page (#6065, @tospe)

[UI] Add box plot visualization for metrics to the Compare Runs page (#6308, @ahlag)

[UI] Display tags on the Compare Runs page (#6164, @CaioCavalcanti)

[UI] Use scientific notation for axes when viewing metric plots in log scale (#6176, @RajezMariner)

[UI] Add button to Metrics page for downloading metrics as CSV (#6048, @rafaelvp-db)

[UI] Include NaN and +/- infinity values in plots on the Metrics page (#6422, @hubertzub-db)

[Tracking / Model Registry] Introduce environment variables to control retry behavior and timeouts for REST API requests (#5745, @peterdhansen)

[Tracking / Model Registry] Make MlflowClient importable as mlflow.MlflowClient (#6085, @subramaniam02)

[Model Registry] Add support for searching registered models and model versions by tags (#6413, #6411, #6320, @WeichenXu123)

[Model Registry] Add stage parameter to set_model_version_tag() (#6185, @subramaniam02)

[Model Registry] Add --registry-store-uri flag to mlflow server for specifying the Model Registry backend URI (#6142, @Secbone)

[Models] Improve performance of Spark Model logging on Databricks (#6282, @bbarnes52)

[Models] Include Pandas Series names in inferred model schemas (#6361, @RynoXLI)

[Scoring] Make model_uri optional in mlflow models build-docker to support building generic model serving images (#6302, @harupy)

[R] Support logging of NA and NaN parameter values (#6263, @nathaneastwood)

Bug fixes and documentation updates:

[Pipelines] Improve scikit-learn regression pipeline latency by limiting dataset profiling to the first 100 columns (#6297, @sunishsheth2009)

[Pipelines] Use xdg-open instead of open for viewing Pipeline results on Linux systems (#6326, @strangiato)

[Pipelines] Fix a bug that skipped Step Card rendering in Jupyter Notebooks (#6378, @apurva-koti)

[Tracking] Use the 401 HTTP response code in authorization failure REST API responses, instead of 500 (#6106, @balvisio)

[Tracking] Correctly classify artifacts as files and directories when using Azure Blob Storage (#6237, @nerdinand)

[Tracking] Fix a bug in the File backend that caused run metadata to be lost in the event of a failed write (#6388, @dbczumar)

[Tracking] Adjust mlflow.pyspark.ml.autolog() to only log model signatures for supported input / output data types (#6365, @harupy)

[Tracking] Adjust mlflow.tensorflow.autolog() to log TensorFlow early stopping callback info when log_models=False is specified (#6170, @WeichenXu123)

[Tracking] Fix signature and input example logging errors in mlflow.sklearn.autolog() for models containing transformers (#6230, @dbczumar)

[Tracking] Fix a failure in mlflow gc that occurred when removing a run whose artifacts had been previously deleted (#6165, @dbczumar)

[Tracking] Add missing sqlparse library to MLflow Skinny client, which is required for search support (#6174, @dbczumar)

[Tracking / Model Registry] Fix an mlflow server bug that rejected parameters and tags with empty string values (#6179, @dbczumar)

[Model Registry] Fix a failure preventing model version schemas from being downloaded with --serve-arifacts enabled (#6355, @abbas123456)

[Scoring] Patch the Java Model Server to support MLflow Models logged on recent versions of the Databricks Runtime (#6337, @dbczumar)

[Scoring] Verify that either the deployment name or endpoint is specified when invoking the mlflow deployments predict CLI (#6323, @dbczumar)

[Scoring] Properly encode datetime columns when performing batch inference with mlflow.pyfunc.spark_udf() (#6244, @harupy)

[Projects] Fix an issue where local directory paths were misclassified as Git URIs when running Projects (#6218, @ElefHead)

[R] Fix metric logging behavior for +/- infinity values (#6271, @nathaneastwood)

... (truncated)

Commits

519b308 Update MLflow version to 1.28.0 (#6447)
8953ef8 [ALL TESTS] Update (#6443)
b258143 Patch (#6440)
c40aacd [ALL TESTS] Changelog for MLflow 1.28.0 (#6433)
7d73598 Raise clear error message when pipeline path contains a space (#6426)
509d334 remove near from deprecation msg (#6430)
63af13c Update MLflow UI (#6422)
e3a9f31 Remove unused method SearchUtils._get_comparison_for_model_registry (#6412)
d16d7cb Fix IN operator related issues in sql filter parser (#6411)
4fde6c3 Allow sql filter IN operator right-hand side values including whitespaces (#6...
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cc @Borda @carmocca @akihironitta

akihironitta · 2022-08-24T16:42:44Z

@dependabot rebase

akihironitta · 2022-08-25T11:35:29Z

@dependabot rebase

Updates the requirements on [mlflow](https://github.com/mlflow/mlflow) to permit the latest version. - [Release notes](https://github.com/mlflow/mlflow/releases) - [Changelog](https://github.com/mlflow/mlflow/blob/master/CHANGELOG.md) - [Commits](mlflow/mlflow@1.0.0...v1.28.0) --- updated-dependencies: - dependency-name: mlflow dependency-type: direct:production ... Signed-off-by: dependabot[bot] <support@github.com>

codecov · 2022-08-25T12:31:59Z

Codecov Report

Merging #14311 (5d3114e) into master (70fe0ed) will decrease coverage by 3%.
The diff coverage is n/a.

❗ Current head 5d3114e differs from pull request most recent head e59fe8c. Consider uploading reports for the commit e59fe8c to get more accurate results

@@            Coverage Diff             @@
##           master   #14311      +/-   ##
==========================================
- Coverage      79%      76%      -3%     
==========================================
  Files         111      332     +221     
  Lines        7258    26891   +19633     
==========================================
+ Hits         5740    20429   +14689     
- Misses       1518     6462    +4944

….0-and-lt-1.29.0

…/requirements (#14311) Update mlflow requirement in /requirements Updates the requirements on [mlflow](https://github.com/mlflow/mlflow) to permit the latest version. - [Release notes](https://github.com/mlflow/mlflow/releases) - [Changelog](https://github.com/mlflow/mlflow/blob/master/CHANGELOG.md) - [Commits](mlflow/mlflow@1.0.0...v1.28.0) --- updated-dependencies: - dependency-name: mlflow dependency-type: direct:production ... Signed-off-by: dependabot[bot] <support@github.com> Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>

dependabot bot requested review from Borda, awaelchli, kaushikb11, rohitgr7, tchaton and williamFalcon as code owners August 19, 2022 05:14

dependabot bot added the ci Continuous Integration label Aug 19, 2022

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Borda approved these changes Aug 19, 2022

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dependabot bot force-pushed the dependabot-pip-requirements-mlflow-gte-1.0.0-and-lt-1.29.0 branch from 7e10583 to 32c2f1a Compare August 24, 2022 16:43

dependabot bot force-pushed the dependabot-pip-requirements-mlflow-gte-1.0.0-and-lt-1.29.0 branch from 32c2f1a to 5d3114e Compare August 25, 2022 11:36

Merge branch 'master' into dependabot-pip-requirements-mlflow-gte-1.0…

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….0-and-lt-1.29.0

Borda merged commit 1ad452f into master Aug 26, 2022

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Update mlflow requirement from <1.28.0,>=1.0.0 to >=1.0.0,<1.29.0 in /requirements #14311

Update mlflow requirement from <1.28.0,>=1.0.0 to >=1.0.0,<1.29.0 in /requirements #14311

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Update mlflow requirement from <1.28.0,>=1.0.0 to >=1.0.0,<1.29.0 in /requirements #14311

Update mlflow requirement from <1.28.0,>=1.0.0 to >=1.0.0,<1.29.0 in /requirements #14311

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