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48
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28 days
Latest Release
40 days ago

Changelog History
Page 1

  • v1.21.0 Changes

    October 23, 2021

    MLflow 1.21.0 includes several major features and improvements:

    ๐Ÿ”‹ Features:

    • ๐Ÿ’ป [UI] Add a diff-only toggle to the runs table for filtering out columns with constant values (#4862, @marijncv)
    • ๐Ÿ’ป [UI] Add a duration column to the runs table (#4840, @marijncv)
    • 0๏ธโƒฃ [UI] Display the default column sorting order in the runs table (#4847, @marijncv)
    • ๐Ÿ’ป [UI] Add start_time and duration information to exported runs CSV (#4851, @marijncv)
    • ๐Ÿ’ป [UI] Add lifecycle stage information to the run page (#4848, @marijncv)
    • 0๏ธโƒฃ [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)
    • ๐Ÿ‘ [Tracking] Add support for deleting artifacts from SFTP stores via the mlflow gc CLI (#4670, @afaul)
    • 0๏ธโƒฃ [Tracking] Support AzureDefaultCredential for authenticating with Azure artifact storage backends (#4002, @marijncv)
    • โฌ†๏ธ [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)
    • โš  [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)

    ๐Ÿ› Bug fixes and documentation updates:

    • ๐Ÿ’ป [UI] Fix an issue where column selections made in the runs table were persisted across experiments (#4926, @sunishsheth2009)
    • ๐Ÿ’ป [UI] Fix an issue where the text null was displayed in the runs table column ordering dropdown (#4924, @harupy)
    • ๐Ÿ’ป [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)
    • ๐Ÿ‘ป [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)
    • ๐Ÿ“š [Docs] Expand the documentation for the MLflow Skinny Client (#4113, @eedeleon)

    โšก๏ธ 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)

  • v1.20.2 Changes

    September 03, 2021

    ๐Ÿš€ MLflow 1.20.2 is a patch release containing the following features and bug fixes:

    ๐Ÿ”‹ Features:

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

    ๐Ÿ› Bug fixes and documentation updates:

    • โฑ Increased MLflow client HTTP request timeout from 10s to 120s (#4764, @jinzhang21)
    • ๐Ÿ›  Fixed autologging compatibility bugs with TensorFlow and Keras version 2.6.0 (#4766, @dbczumar)

    โšก๏ธ Small bug fixes and doc updates (#4770, @WeichenXu123)

  • v1.20.1 Changes

    August 26, 2021

    ๐Ÿš€ MLflow 1.20.1 is a patch release containing the following bug fixes:

    • ๐Ÿ“‡ Avoid calling importlib_metadata.packages_distributions upon mlflow.utils.requirements_utils import (#4741, @dbczumar)
    • ๐Ÿ“‡ Avoid depending on importlib_metadata==4.7.0 (#4740, @dbczumar)
  • v1.20.0 Changes

    August 25, 2021

    MLflow 1.20.0 includes several major features and improvements:

    ๐Ÿ”‹ 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)
    • โž• Added stdMetrics entries to the training metrics recorded during PySpark CrossValidator autologging (#4672, @WeichenXu123)
    • โšก๏ธ 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)
    • โž• Added support for distributed execution to autologging for PyTorch Lightning (#4717, @dbczumar)
    • ๐Ÿ‘ Expanded R support for Model Registry functionality (#4527, @bramrodenburg)
    • โž• Added model scoring server support for defining custom prediction response wrappers (#4611, @Ark-kun)
    • ๐ŸŒฒ 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)
    • ๐Ÿ‘ท Introduced support for running Sagemaker Batch Transform jobs with MLflow Models (#4410, #4589, @YQ-Wang)

    ๐Ÿ› 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)
    • ๐Ÿ›  Fix a bug in MLflow UI where the pagination token for run search is not refreshed when switching experiments (#4709, @harupy)
    • ๐Ÿ›  Fix a bug in the model scoring server that rejected requests specifying a valid Content-Type header with the charset parameter (#4609, @Ark-kun)
    • ๐Ÿ›  Fixed a bug that caused SQLAlchemy backends to exhaust DB connections. (#4663, @arpitjasa-db)
    • ๐Ÿ‘Œ Improve docker build procedures to raise exceptions if docker builds fail (#4610, @Ark-kun)
    • Disable autologging for scikit-learn cross_val_* APIs, which are incompatible with autologging (#4590, @WeichenXu123)
    • ๐Ÿ—„ Deprecate MLflow Models support for fast.ai V1 (#4728, @dbczumar)
    • ๐Ÿ— Deprecate the old Azure ML deployment APIs mlflow.azureml.cli.build_image and mlflow.azureml.build_image (#4646, @trangevi)
    • ๐Ÿ—„ Deprecate MLflow Models support for TensorFlow < 2.0 and Keras < 2.3 (#4716, @harupy)

    โšก๏ธ Small bug fixes and doc updates (#4730, #4722, #4725, #4723, #4703, #4710, #4679, #4694, #4707, #4708, #4706, #4705, #4625, #4701, #4700, #4662, #4699, #4682, #4691, #4684, #4683, #4675, #4666, #4648, #4653, #4651, #4641, #4649, #4627, #4637, #4632, #4634, #4621, #4619, #4622, #4460, #4608, #4605, #4599, #4600, #4581, #4583, #4565, #4575, #4564, #4580, #4572, #4570, #4574, #4576, #4568, #4559, #4537, #4542, @harupy; #4698, #4573, @Ark-kun; #4674, @kvmakes; #4555, @vagoston; #4644, @zhengjxu; #4690, #4588, @apurva-koti; #4545, #4631, #4734, @WeichenXu123; #4633, #4292, @shrinath-suresh; #4711, @jinzhang21; #4688, @murilommen; #4635, @ryan-duve; #4724, #4719, #4640, #4639, #4629, #4612, #4613, #4586, @dbczumar)

  • v1.19.0 Changes

    July 14, 2021

    MLflow 1.19.0 includes several major features and improvements:

    ๐Ÿ”‹ Features:

    • โž• Add support for plotting per-class feature importance computed on linear boosters in XGBoost autologging (#4523, @dbczumar)
    • Add mlflow_create_registered_model and mlflow_delete_registered_model for R to create/delete registered models.
    • โž• Add support for setting tags while resuming a run (#4497, @dbczumar)
    • โšก๏ธ MLflow UI updates (#4490, @sunishsheth2009)

      • Add framework for internationalization support.
      • Move metric columns before parameter and tag columns in the runs table.
      • Change the display format of run start time to elapsed time (e.g. 3 minutes ago) from timestamp (e.g. 2021-07-14 14:02:10) in the runs table.

    ๐Ÿ› Bug fixes and documentation updates:

    • ๐Ÿ›  Fix a bug causing MLflow UI to crash when sorting a column containing both NaN and empty values (#3409, @harupy)

    โšก๏ธ Small bug fixes and doc updates (#4541, #4534, #4533, #4517, #4508, #4513, #4512, #4509, #4503, #4486, #4493, #4469, @harupy; #4458, @KasirajanA; #4501, @jimmyxu-db; #4521, #4515, @jerrylian-db; #4359, @shrinath-suresh; #4544, @WeichenXu123; #4549, @smurching; #4554, @derkomai; #4506, @tomasatdatabricks; #4551, #4516, #4494, @dbczumar; #4511, @keypointt)

  • v1.18.0 Changes

    June 18, 2021

    MLflow 1.18.0 includes several major features and improvements:

    ๐Ÿ”‹ Features:

    • ๐ŸŽ Autologging performance improvements for XGBoost, LightGBM, and scikit-learn (#4416, #4473, @dbczumar)
    • โž• Add new PaddlePaddle flavor to MLflow Models (#4406, #4439, @jinminhao)
    • Introduce paginated ListExperiments API (#3881, @wamartin-aml)
    • Include Runtime version for MLflow Models logged on Databricks (#4421, @stevenchen-db)
    • ๐ŸŒฒ MLflow Models now log dependencies in pip requirements.txt format, in addition to existing conda format (#4409, #4422, @stevenchen-db)
    • โž• Add support for limiting the number child runs created by autologging for scikit-learn hyperparameter search models (#4382, @mohamad-arabi)
    • ๐Ÿ‘Œ Improve artifact upload / download performance on Databricks (#4260, @dbczumar)
    • Migrate all model dependencies from conda to "pip" section (#4393, @WeichenXu123)

    ๐Ÿ› Bug fixes and documentation updates:

    • ๐Ÿ›  Fix an MLflow UI bug that caused git source URIs to be rendered improperly (#4403, @takabayashi)
    • ๐Ÿ›  Fix a bug that prevented reloading of MLflow Models based on the TensorFlow SavedModel format (#4223) (#4319, @saschaschramm)
    • ๐Ÿ›  Fix a bug in the behavior of KubernetesSubmittedRun.get_status() for Kubernetes MLflow Project runs (#3962) (#4159, @jcasse)
    • ๐Ÿ›  Fix a bug in TLS verification for MLflow artifact operations on S3 (#4047, @PeterSulcs)
    • ๐Ÿ›  Fix a bug causing the MLflow server to crash after deletion of the default experiment (#4352, @asaf400)
    • ๐Ÿ›  Fix a bug causing mlflow models serve to crash on Windows 10 (#4377, @simonvanbernem)
    • ๐Ÿ›  Fix a crash in runs search when ordering by metric values against the MSSQL backend store (#2551) (#4238, @naor2013)
    • ๐Ÿ›  Fix an autologging incompatibility issue with TensorFlow 2.5 (#4371, @dbczumar)
    • Fix a bug in the disable_for_unsupported_versions autologging argument that caused library versions to be incorrectly compared (#4303, @WeichenXu123)

    โšก๏ธ Small bug fixes and doc updates (#4405, @mohamad-arabi; #4455, #4461, #4459, #4464, #4453, #4444, #4449, #4301, #4424, #4418, #4417, #3759, #4398, #4389, #4386, #4385, #4384, #4380, #4373, #4378, #4372, #4369, #4348, #4364, #4363, #4349, #4350, #4174, #4285, #4341, @harupy; #4446, @kHarshit; #4471, @AveshCSingh; #4435, #4440, #4368, #4360, @WeichenXu123; #4431, @apurva-koti; #4428, @stevenchen-db; #4467, #4402, #4261, @dbczumar)

  • v1.17.0 Changes

    May 07, 2021

    MLflow 1.17.0 includes several major features and improvements:

    ๐Ÿ”‹ Features:

    • โž• Add support for hyperparameter-tuning models to mlflow.pyspark.ml.autolog() (#4270, @WeichenXu123)

    ๐Ÿ› Bug fixes and documentation updates:

    • ๐Ÿ›  Fix PyTorch Lightning callback definition for compatibility with PyTorch Lightning 1.3.0 (#4333, @dbczumar)
    • ๐Ÿ›  Fix a bug in scikit-learn autologging that omitted artifacts for unsupervised models (#4325, @dbczumar)
    • ๐Ÿ‘Œ Support logging datetime.date objects as part of model input examples (#4313, @vperiyasamy)
    • Implement HTTP request retries in the MLflow Java client for 500-level responses (#4311, @dbczumar)
    • Include a community code of conduct (#4310, @dennyglee)

    โšก๏ธ Small bug fixes and doc updates (#4276, #4263, @WeichenXu123; #4289, #4302, #3599, #4287, #4284, #4265, #4266, #4275, #4268, @harupy; #4335, #4297, @dbczumar; #4324, #4320, @tleyden)

  • v1.16.0 Changes

    April 22, 2021

    MLflow 1.16.0 includes several major features and improvements:

    ๐Ÿ”‹ Features:

    • โž• Add mlflow.pyspark.ml.autolog() API for autologging of pyspark.ml estimators (#4228, @WeichenXu123)
    • Add mlflow.catboost.log_model, mlflow.catboost.save_model, mlflow.catboost.load_model APIs for CatBoost model persistence (#2417, @harupy)
    • 0๏ธโƒฃ Enable mlflow.pyfunc.spark_udf to use column names from model signature by default (#4236, @Loquats)
    • โž• Add datetime data type for model signatures (#4241, @vperiyasamy)
    • Add mlflow.sklearn.eval_and_log_metrics API that computes and logs metrics for the given scikit-learn model and labeled dataset. (#4218, @alkispoly-db)

    ๐Ÿ› Bug fixes and documentation updates:

    • ๐Ÿ›  Fix a database migration error for PostgreSQL (#4211, @dolfinus)
    • ๐Ÿ›  Fix autologging silent mode bugs (#4231, @dbczumar)

    โšก๏ธ Small bug fixes and doc updates (#4255, #4252, #4254, #4253, #4242, #4247, #4243, #4237, #4233, @harupy; #4225, @dmatrix; #4206, @mlflow-automation; #4207, @shrinath-suresh; #4264, @WeichenXu123; #3884, #3866, #3885, @ankan94; #4274, #4216, @dbczumar)

  • v1.15.0 Changes

    March 26, 2021

    ๐Ÿ›  MLflow 1.15.0 includes several features, bug fixes and improvements. Notably, it includes a number of improvements to MLflow autologging:

    ๐Ÿ”‹ Features:

    • โž• Add silent=False option to all autologging APIs, to allow suppressing MLflow warnings and logging statements during autologging setup and training (#4173, @dbczumar)
    • Add disable_for_unsupported_versions=False option to all autologging APIs, to disable autologging for versions of ML frameworks that have not been explicitly tested against the current version of the MLflow client (#4119, @WeichenXu123)

    ๐Ÿ› Bug fixes:

    • Autologged runs are now terminated when execution is interrupted via SIGINT (#4200, @dbczumar)
    • The R mlflow_get_experiment API now returns the same tag structure as mlflow_list_experiments and mlflow_get_run (#4017, @lorenzwalthert)
    • ๐Ÿ›  Fix bug where mlflow.tensorflow.autolog would previously mutate the user-specified callbacks list when fitting tf.keras models (#4195, @dbczumar)
    • ๐Ÿ›  Fix bug where SQL-backed MLflow tracking server initialization failed when using the MLflow skinny client (#4161, @eedeleon)
    • Model version creation (e.g. via mlflow.register_model) now fails if the model version status is not READY (#4114, @ankit-db)

    โšก๏ธ Small bug fixes and doc updates (#4191, #4149, #4162, #4157, #4155, #4144, #4141, #4138, #4136, #4133, #3964, #4130, #4118, @harupy; #4152, @mlflow-automation; #4139, @WeichenXu123; #4193, @smurching; #4029, @architkulkarni; #4134, @xhochy; #4116, @wenleix; #4160, @wentinghu; #4203, #4184, #4167, @dbczumar)

  • v1.14.1 Changes

    March 01, 2021

    ๐Ÿš€ MLflow 1.14.1 is a patch release containing the following bug fix:

    • ๐Ÿ›  Fix issues in handling flexible numpy datatypes in TensorSpec (#4147, @arjundc-db)