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MLflow 1.7.1

· One min read
MLflow maintainers
MLflow maintainers
MLflow maintainers

MLflow 1.7.1 is a patch release containing bug fixes and small changes:

  • Remove usage of Nonnull annotations and findbugs dependency in Java package.
  • Add version upper bound (<=1.3.13) to sqlalchemy dependency in Python package
  • Documentation fixes

For a comprehensive list of changes, see the release change log, and check out the latest documentation on mlflow.org.

MLflow 1.7.0

· One min read
MLflow maintainers
MLflow maintainers
MLflow maintainers

We are happy to announce the availability of MLflow 1.7.0!

In addition to bug and documentation fixes, MLflow 1.7.0 includes the following major changes:

  • Support for Python 2 is deprecated and will be dropped in a future release. At that point, existing Python 2 workflows that use MLflow will continue to work without modification, but Python 2 users will no longer get access to the latest MLflow features and bugfixes.

  • Breaking changes to Model Registry REST APIs

    • Model Registry REST APIs have been updated to be more consistent with the other MLflow APIs and are intended to be stable until the next major version.
    • Python and Java client APIs for Model Registry are backward compatible and have been updated to use the new REST APIs.

In addition several UI and and backend features were added in version 1.7.0. For a comprehensive list of changes, see the release change log, and check out the latest documentation on mlflow.org.

MLflow 1.6.0

· One min read
MLflow maintainers
MLflow maintainers
MLflow maintainers

We are happy to announce the availability of MLflow 1.6.0!

MLflow 1.6.0 includes a better runs table interface, a utility for easier parameter tuning, and automatic logging from XGBoost, LightGBM, and Spark. It also includes bug and documentation fixes, including a long-awaited fix allowing "@" symbols in database URLs.

For a comprehensive list of changes, see the release change log, and check out the latest documentation on mlflow.org.

MLflow 1.5.0

· One min read
MLflow maintainers
MLflow maintainers
MLflow maintainers

We are happy to announce the availability of MLflow 1.5.0!

In addition to bug and documentation fixes, MLflow 1.5.0 includes the following major features and improvements:

  • New support for a LightGBM flavor.
  • New support for a XGBoost flavor.
  • New support for a Gluon flavor and autologging.
  • Runs automatically created by mlflow.tensorflow.autolog() and mlflow.keras.autolog() are now automatically ended after training and/or exporting your model. See the docs for more details.

For a comprehensive list of changes, see the release change log, and check out the latest documentation on mlflow.org.

MLflow 1.4.0

· One min read
MLflow maintainers
MLflow maintainers
MLflow maintainers

We are happy to announce the availability of MLflow 1.4.0!

In addition to bug and documentation fixes, MLflow 1.4.0 includes the following major features and improvements:

  • Model Registry (Beta). MLflow 1.4.0 adds an experimental model registry feature, where you can manage, version, and keep lineage of your production models.
  • TensorFlow updates
    • MLflow Keras model saving, loading, and logging has been updated to be compatible with TensorFlow 2.0.
    • Autologging for tf.estimator and tf.keras models has been updated to be compatible with TensorFlow 2.0. The same functionalities of autologging in TensorFlow 1.x are available in TensorFlow 2.0, namely when fitting tf.keras models and when exporting saved tf.estimator models.
    • Examples and READMEs for both TensorFlow 1.X and TensorFlow 2.0 have been added to mlflow/examples/tensorflow.

For a comprehensive list of changes, see the release change log, and check out the latest documentation on mlflow.org.

MLflow 1.3.0

· One min read
MLflow maintainers
MLflow maintainers
MLflow maintainers

We are happy to announce the availability of MLflow 1.3.0!

In addition to several bug and documentation fixes, MLflow 1.3.0 includes the following major features and improvements:

  • The Python client now supports logging & loading models using TensorFlow 2.0
  • Significant performance improvements when fetching runs and experiments in MLflow servers that use SQL database-backed storage
  • New GetExperimentByName REST API endpoint, used in the Python client to speed up set_experiment and get_experiment_by_name
  • New mlflow.delete_run, mlflow.delete_experiment fluent APIs in the Python client
  • New CLI command (mlflow experiments csv) to export runs of an experiment into a CSV
  • Directories can now be logged as artifacts via mlflow.log_artifact in the Python fluent API
  • HTML and geojson artifacts are now rendered in the run UI
  • Keras autologging support for fit_generator Keras API
  • MLflow models packaged as docker containers can be executed via Google Cloud Run
  • Artifact storage configurations are propagated to containers when executing docker-based MLflow projects locally
  • The Python, Java, R clients and UI now retry HTTP requests on 429 (Too Many Requests) errors

For a comprehensive list of changes, see the release change log, and check out the latest documentation on mlflow.org.

MLflow 1.2.0

· One min read
MLflow maintainers
MLflow maintainers
MLflow maintainers

We are happy to announce the availability of MLflow 1.2.0!

In addition to several bug and documentation fixes, MLflow 1.2.0 includes the following major features and improvements:

  • Experiments now have editable tags and descriptions
  • Search latency has been significantly reduced in the SQLAlchemyStore

For a comprehensive list of changes, see the release change log, and check out the latest documentation on mlflow.org.

MLflow 1.1.0

· One min read
MLflow maintainers
MLflow maintainers
MLflow maintainers

We are happy to announce the availability of MLflow 1.1.0!

MLflow 1.1.0 introduces several major features:

  • Automatic logging from TensorFlow and Keras
  • Parallel coordinate plots in the tracking UI
  • Pandas DataFrame based search API
  • Java Fluent API
  • Kubernetes execution backend for MLflow projects
  • Search Pagination

For a comprehensive list of features, see the release change log, and check out the latest documentation on mlflow.org.

MLflow 0.9.1

· One min read
MLflow maintainers
MLflow maintainers
MLflow maintainers

We are happy to announce the availability of MLflow 0.9.1!

MLflow 0.9.1 is a patch release on top of 0.9.0 containing mostly bug fixes and internal improvements. We have also included a one breaking API change in preparation for additions in MLflow 1.0 and later. This release also includes significant improvements to the Search API. Please visit the release change log to read more about the fixes and updates in this release.