search

DougTrajano / mlflow-server

MLflow Tracking Server with basic auth deployed in AWS App Runner.
https://gallery.ecr.aws/t9j8s4z8/mlflow
Apache License 2.0
34 stars 17 forks source link

Bump mlflow from 1.25.1 to 1.26.0 #150

Closed dependabot[bot] closed 2 years ago

dependabot[bot] commented 2 years ago

Bumps mlflow from 1.25.1 to 1.26.0.

Release notes

Sourced from mlflow's releases.

MLflow 1.26.0 includes several major features and improvements:

Features:

  • [CLI] Add endpoint naming and options configuration to the deployment CLI (#5731, @​trangevi)
  • [Build,Doc] Add development environment setup script for Linux and MacOS x86 Operating Systems (#5717, @​BenWilson2)
  • [Tracking] Update mlflow.set_tracking_uri to add support for paths defined as pathlib.Path in addition to existing str path declarations (#5824, @​cacharle)
  • [Scoring] Add custom timeout override option to the scoring server CLI to support high latency models (#5663, @​sniafas)
  • [UI] Add sticky header to experiment run list table to support column name visibility when scrolling beyond page fold (#5818, @​hubertzub-db)
  • [Artifacts] Add GCS support for MLflow garbage collection (#5811, @​aditya-iyengar-rtl-de)
  • [Evaluate] Add pos_label argument for eval_and_log_metrics API to support accurate binary classifier evaluation metrics (#5807, @​yxiong)
  • [UI] Add fields for latest, minimum and maximum metric values on metric display page (#5574, @​adamreeve)
  • [Models] Add support for input_example and signature logging for pyspark ml flavor when using autologging (#5719, @​bali0019)
  • [Models] Add virtualenv environment manager support for mlflow models docker-build CLI (#5728, @​harupy)
  • [Models] Add support for wildcard module matching in log_model_allowlist for PySpark models (#5723, @​serena-ruan)
  • [Projects] Add virtualenv environment manager support for MLflow projects (#5631, @​harupy)
  • [Models] Add virtualenv environment manager support for MLflow Models (#5380, @​harupy)
  • [Models] Add virtualenv environment manager support for mlflow.pyfunc.spark_udf (#5676, @​WeichenXu123)
  • [Models] Add support for input_example and signature logging for tensorflow flavor when using autologging (#5510, @​bali0019)
  • [Server-infra] Add JSON Schema Type Validation to enable raising 400 errors on malformed requests to REST API endpoints (#5458, @​mrkaye97)
  • [Scoring] Introduce abstract endpoint interface for mlflow deployments (#5378, @​trangevi)
  • [UI] Add End Time and Duration fields to run comparison page (#3378, @​RealArpanBhattacharya)
  • [Serving] Add schema validation support when parsing input csv data for model serving (#5531, @​vvijay-bolt)

Bug fixes and documentation updates:

  • [Models] Fix REPL ID propagation from datasource listener to publisher for Spark data sources (#5826, @​dbczumar)
  • [UI] Update ag-grid and implement getRowId to improve performance in the runs table visualization (#5725, @​adamreeve)
  • [Serving] Fix tf-serving parsing to support columnar-based formatting (#5825, @​arjundc-db)
  • [Artifacts] Update log_artifact to support models larger than 2GB in HDFS (#5812, @​hitchhicker)
  • [Models] Fix autologging to support lightgbm metric names with "@" symbols within their names (#5785, @​mengchendd)
  • [Models] Pyfunc: Fix code directory resolution of subdirectories (#5806, @​dbczumar)
  • [Server-Infra] Fix mlflow-R server starting failure on windows (#5767, @​serena-ruan)
  • [Docs] Add documentation for virtualenv environment manager support for MLflow projects (#5727, @​harupy)
  • [UI] Fix artifacts display sizing to support full width rendering in preview pane (#5606, @​szczeles)
  • [Models] Fix local hostname issues when loading spark model by binding driver address to localhost (#5753, @​WeichenXu123)
  • [Models] Fix autologging validation and batch_size calculations for tensorflow flavor (#5683, @​MarkYHZhang)
  • [Artifacts] Fix SqlAlchemyStore.log_batch implementation to make it log data in batches (#5460, @​erensahin)

Small bug fixes and doc updates (#5858, #5859, #5853, #5854, #5845, #5829, #5842, #5834, #5795, #5777, #5794, #5766, #5778, #5765, #5763, #5768, #5769, #5760, #5727, #5748, #5726, #5721, #5711, #5710, #5708, #5703, #5702, #5696, #5695, #5669, #5670, #5668, #5661, #5638, @​harupy; #5749, @​arpitjasa-db; #5675, @​Davidswinkels; #5803, #5797, @​ahlag; #5743, @​kzhang01; #5650, #5805, #5724, #5720, #5662, @​BenWilson2; #5627, @​cterrelljones; #5646, @​kutal10; #5758, @​davideli-db; #5810, @​rahulporuri; #5816, #5764, @​shrinath-suresh; #5869, #5715, #5737, #5752, #5677, #5636, @​WeichenXu123; #5735, @​subramaniam02; #5746, @​akaigraham; #5734, #5685, @​lucalves; #5761, @​marcelatoffernet; #5707, @​aashish-khub; #5808, @​ketangangal; #5730, #5700, @​shaikmoeed; #5775, @​dbczumar; #5747, @​zhixuanevelynwu)

Note: Version 1.26.0 of the MLflow R package has not yet been released. It will be available on CRAN within the next week.

Changelog

Sourced from mlflow's changelog.

1.26.0 (2022-05-16)

MLflow 1.26.0 includes several major features and improvements:

Features:

  • [CLI] Add endpoint naming and options configuration to the deployment CLI (#5731, @​trangevi)
  • [Build,Doc] Add development environment setup script for Linux and MacOS x86 Operating Systems (#5717, @​BenWilson2)
  • [Tracking] Update mlflow.set_tracking_uri to add support for paths defined as pathlib.Path in addition to existing str path declarations (#5824, @​cacharle)
  • [Scoring] Add custom timeout override option to the scoring server CLI to support high latency models (#5663, @​sniafas)
  • [UI] Add sticky header to experiment run list table to support column name visibility when scrolling beyond page fold (#5818, @​hubertzub-db)
  • [Artifacts] Add GCS support for MLflow garbage collection (#5811, @​aditya-iyengar-rtl-de)
  • [Evaluate] Add pos_label argument for eval_and_log_metrics API to support accurate binary classifier evaluation metrics (#5807, @​yxiong)
  • [UI] Add fields for latest, minimum and maximum metric values on metric display page (#5574, @​adamreeve)
  • [Models] Add support for input_example and signature logging for pyspark ml flavor when using autologging (#5719, @​bali0019)
  • [Models] Add virtualenv environment manager support for mlflow models docker-build CLI (#5728, @​harupy)
  • [Models] Add support for wildcard module matching in log_model_allowlist for PySpark models (#5723, @​serena-ruan)
  • [Projects] Add virtualenv environment manager support for MLflow projects (#5631, @​harupy)
  • [Models] Add virtualenv environment manager support for MLflow Models (#5380, @​harupy)
  • [Models] Add virtualenv environment manager support for mlflow.pyfunc.spark_udf (#5676, @​WeichenXu123)
  • [Models] Add support for input_example and signature logging for tensorflow flavor when using autologging (#5510, @​bali0019)
  • [Server-infra] Add JSON Schema Type Validation to enable raising 400 errors on malformed requests to REST API endpoints (#5458, @​mrkaye97)
  • [Scoring] Introduce abstract endpoint interface for mlflow deployments (#5378, @​trangevi)
  • [UI] Add End Time and Duration fields to run comparison page (#3378, @​RealArpanBhattacharya)
  • [Serving] Add schema validation support when parsing input csv data for model serving (#5531, @​vvijay-bolt)

Bug fixes and documentation updates:

  • [Models] Fix REPL ID propagation from datasource listener to publisher for Spark data sources (#5826, @​dbczumar)
  • [UI] Update ag-grid and implement getRowId to improve performance in the runs table visualization (#5725, @​adamreeve)
  • [Serving] Fix tf-serving parsing to support columnar-based formatting (#5825, @​arjundc-db)
  • [Artifacts] Update log_artifact to support models larger than 2GB in HDFS (#5812, @​hitchhicker)
  • [Models] Fix autologging to support lightgbm metric names with "@" symbols within their names (#5785, @​mengchendd)
  • [Models] Pyfunc: Fix code directory resolution of subdirectories (#5806, @​dbczumar)
  • [Server-Infra] Fix mlflow-R server starting failure on windows (#5767, @​serena-ruan)
  • [Docs] Add documentation for virtualenv environment manager support for MLflow projects (#5727, @​harupy)
  • [UI] Fix artifacts display sizing to support full width rendering in preview pane (#5606, @​szczeles)
  • [Models] Fix local hostname issues when loading spark model by binding driver address to localhost (#5753, @​WeichenXu123)
  • [Models] Fix autologging validation and batch_size calculations for tensorflow flavor (#5683, @​MarkYHZhang)
  • [Artifacts] Fix SqlAlchemyStore.log_batch implementation to make it log data in batches (#5460, @​erensahin)

Small bug fixes and doc updates (#5858, #5859, #5853, #5854, #5845, #5829, #5842, #5834, #5795, #5777, #5794, #5766, #5778, #5765, #5763, #5768, #5769, #5760, #5727, #5748, #5726, #5721, #5711, #5710, #5708, #5703, #5702, #5696, #5695, #5669, #5670, #5668, #5661, #5638, @​harupy; #5749, @​arpitjasa-db; #5675, @​Davidswinkels; #5803, #5797, @​ahlag; #5743, @​kzhang01; #5650, #5805, #5724, #5720, #5662, @​BenWilson2; #5627, @​cterrelljones; #5646, @​kutal10; #5758, @​davideli-db; #5810, @​rahulporuri; #5816, #5764, @​shrinath-suresh; #5869, #5715, #5737, #5752, #5677, #5636, @​WeichenXu123; #5735, @​subramaniam02; #5746, @​akaigraham; #5734, #5685, @​lucalves; #5761, @​marcelatoffernet; #5707, @​aashish-khub; #5808, @​ketangangal; #5730, #5700, @​shaikmoeed; #5775, @​dbczumar; #5747, @​zhixuanevelynwu)

Commits
  • 8561f8c Update MLflow version to 1.26.0 (#5868)
  • b0811ec init (#5869)
  • 120be84 [ALL TESTS] Update (#5863)
  • 3d57776 python dev/update_pypi_package_index.py (#5864)
  • 60124e4 Update MLflow UI (#5858)
  • 17137cb Fix bug where clicking mlflow logo returns "No Experiments Exist" (#5859)
  • 70ab2fe Fix validate_docker_installation to throw when docker daemon is not running...
  • 6b67584 Pin some ML dependencies to prevent pip from filling up diskspace while resol...
  • c1722fd Fix tests for SFTP artifact repository (#5845)
  • c3216a9 Refactor ExperimentListView using @databricks/design-system's Tree comp...
  • Additional commits viewable in compare view


Dependabot compatibility score

Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.

Dependabot commands and options
You can trigger Dependabot actions by commenting on this PR: - `@dependabot rebase` will rebase this PR - `@dependabot recreate` will recreate this PR, overwriting any edits that have been made to it - `@dependabot merge` will merge this PR after your CI passes on it - `@dependabot squash and merge` will squash and merge this PR after your CI passes on it - `@dependabot cancel merge` will cancel a previously requested merge and block automerging - `@dependabot reopen` will reopen this PR if it is closed - `@dependabot close` will close this PR and stop Dependabot recreating it. You can achieve the same result by closing it manually - `@dependabot ignore this major version` will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself) - `@dependabot ignore this minor version` will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself) - `@dependabot ignore this dependency` will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself)
dependabot[bot] commented 2 years ago

Superseded by #152.