MLflow v1.7.0 Release Notes
Release Date: 2020-03-02 // about 4 years ago-
1.7.0 (2020-03-02)
MLflow 1.7.0 includes several major features and improvements and some notable breaking changes.
🛠 MLflow support for Python 2 is now 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. We recommend that you upgrade to Python 3 - see https://docs.python.org/3/howto/pyporting.html for a migration guide.
💥 Breaking changes to Model Registry REST APIs:
🚀 Model Registry REST APIs have been updated to be more consistent with the other MLflow APIs. With this release Model Registry APIs are intended to be stable until the next major version.
- 🚀 Python and Java client APIs for Model Registry have been updated to use the new REST APIs. When using an MLflow client with a server using updated REST endpoints, you won't need to change any code but will need to upgrade to a new client version. The client APIs contain deprecated arguments, which for this release are backward compatible, but will be dropped in future releases. (#2457, @tomasatdatabricks; #2502, @mparkhe).
- ⚡️ The Model Registry UI has been updated to use the new REST APIs (#2476 @aarondav; #2507, @mparkhe)
Other Features:
- Ability to click through to individual runs from metrics plot (#2295, @harupy)
- ➕ Added mlflow gc CLI for permanent deletion of runs (#2265, @t-henri)
- Metric plot state is now captured in page URLs for easier link sharing (#2393, #2408, #2498 @smurching; #2459, @harupy)
- ➕ Added experiment management to MLflow UI (create/rename/delete experiments) (#2348, @ggliem)
- 💻 Ability to search for experiments by name in the UI (#2324, @ggliem)
- 💻 MLflow UI page titles now reflect the content displayed on the page (#2420, @AveshCSingh)
- ➕ Added a new LogModel REST API endpoint for capturing model metadata, and call it from the Python and R clients (#2369, #2430, #2468 @tomasatdatabricks)
- Java Client API to download model artifacts from Model Registry (#2308, @andychow-db)
🐛 Bug fixes and documentation updates:
- 📚 Updated Model Registry documentation page with code snippets and examples (#2493, @dmatrix; #2517, @harupy)
- 👍 Better error message for Model Registry, when using incompatible backend server (#2456, @aarondav)
- matplotlib is no longer required to use XGBoost and LightGBM autologging (#2423, @harupy)
- 🛠 Fixed bug where matplotlib figures were not closed in XGBoost and LightGBM autologging (#2386, @harupy)
- 🛠 Fixed parameter reading logic to support param values with newlines in FileStore (#2376, @dbczumar)
- 👌 Improve readability of run table column selector nodes (#2388, @dbczumar)
- ⚡️ Validate experiment name supplied to UpdateExperiment REST API endpoint (#2357, @ggliem)
- 🛠 Fixed broken MLflow DB README link in CLI docs (#2377, @dbczumar)
- 🔄 Change copyright year across docs to 2020 (#2349, @ParseThis)
⚡️ Small bug fixes and doc updates (#2378, #2449, #2402, #2397, #2391, #2387, #2523, #2527 @harupy; #2314, @juntai-zheng; #2404, @andychow-db; #2343, @pogil; #2366, #2370, #2364, #2356, @AveshCSingh; #2373, #2365, #2363, @smurching; #2358, @jcuquemelle; #2490, @RensDimmendaal; #2506, @dbczumar; #2234 @Zangr; #2359 @lbernickm; #2525, @mparkhe)