From d193e8771821d92c6affb49f296e4f4c0d9940b0 Mon Sep 17 00:00:00 2001 From: Aaron Davidson Date: Wed, 18 Jul 2018 11:36:03 -0700 Subject: [PATCH] Bump version and update changelog for 0.3.0 release (#167) --- CHANGELOG.rst | 26 ++++++++++++++++++++++++- docs/source/python_api/mlflow.spark.rst | 8 ++++++++ mlflow/models/__init__.py | 2 +- mlflow/version.py | 2 +- 4 files changed, 35 insertions(+), 3 deletions(-) create mode 100644 docs/source/python_api/mlflow.spark.rst diff --git a/CHANGELOG.rst b/CHANGELOG.rst index 997106fcbbe37..f2fcdf50b220e 100644 --- a/CHANGELOG.rst +++ b/CHANGELOG.rst @@ -1,6 +1,30 @@ Changelog ========= +0.3.0 (2018-07-18) +------------------ + +Breaking changes: + +- [MLflow Server] Renamed ``--artifact-root`` parameter to ``--default-artifact-root`` in ``mlflow server`` to better reflect its purpose (#165, @aarondav) + +Features: + +- Spark MLlib integration: we now support logging SparkML Models directly in the log_model API, model format, and serving APIs (#72, @tomasatdatabricks) +- Google Cloud Storage is now supported as an artifact storage root (#152, @bnekolny) +- Support asychronous/parallel execution of MLflow runs (#82, @smurching) +- [SageMaker] Support for deleting, updating applications deployed via SageMaker (#145, @dbczumar) +- [SageMaker] Pushing the MLflow SageMaker container now includes the MLflow version that it was published with (#124, @sueann) +- [SageMaker] Simplify parameters to SageMaker deploy by providing sane defaults (#126, @sueann) +- [UI] One-element metrics are now displayed as a bar char (#118, @cryptexis) + +Bug fixes: + +- Require gitpython>=2.1.0 (#98, @aarondav) +- Fixed TensorFlow model loading so that columns match the output names of the exported model (#94, @smurching) +- Fix SparkUDF when number of columns >= 10 (#97, @aarondav) +- Miscellaneous bug and documentation fixes from @emres, @dmatrix, @stbof, @gsganden, @dennyglee, @anabranch, @mikehuston, @andrewmchen, @juntai-zheng + 0.2.1 (2018-06-28) ------------------ @@ -19,7 +43,7 @@ This is a patch release fixing some smaller issues after the 0.2.0 release. - ``--artifact-root`` to allow storing artifacts at a remote location, S3 only right now (#78, @mateiz) - Server now runs behind gunicorn to allow concurrent requests to be made (#61, @mateiz) -- Tensorflow integration, we now support logging Tensorflow Models directly in the log_artifacts API, Model format, and serving APIs (#28, @juntai-zheng) +- Tensorflow integration: we now support logging Tensorflow Models directly in the log_model API, model format, and serving APIs (#28, @juntai-zheng) - Added ``experiments.list_experiments`` as part of experiments API (#37, @mparkhe) - Improved support for unicode strings (#79, @smurching) - Diabetes progression example dataset and training code (#56, @dennyglee) diff --git a/docs/source/python_api/mlflow.spark.rst b/docs/source/python_api/mlflow.spark.rst new file mode 100644 index 0000000000000..f765ce631b1f5 --- /dev/null +++ b/docs/source/python_api/mlflow.spark.rst @@ -0,0 +1,8 @@ +mlflow.spark +=============== + +.. automodule:: mlflow.spark + :members: + :undoc-members: + :show-inheritance: + diff --git a/mlflow/models/__init__.py b/mlflow/models/__init__.py index b4c99e45eb3c7..c958cca324da9 100644 --- a/mlflow/models/__init__.py +++ b/mlflow/models/__init__.py @@ -45,7 +45,7 @@ def log(cls, artifact_path, flavor, **kwargs): :param artifact_path: Run-relative path identifying this model. :param flavor: Flavor module / object to save the model with. The module / object must have - save_model function which will persist the model as a valid MLflow model. + save_model function which will persist the model as a valid MLflow model. :param kwargs: Extra args passed to the model flavor. """ with TempDir() as tmp: diff --git a/mlflow/version.py b/mlflow/version.py index 231a9f627b901..0e093c0835d52 100644 --- a/mlflow/version.py +++ b/mlflow/version.py @@ -1,4 +1,4 @@ # Copyright 2018 Databricks, Inc. -VERSION = '0.2.1' +VERSION = '0.3.0'