swh:1:snp:6298e170750eb9cfb13fbd6f84b11ca6a6738b27
Tip revision: a365045c6f17c6a805285ea0aaf9bc09ce386a5d authored by Jesper Nielsen on 20 January 2022, 11:23:01 UTC
Merge pull request #1757 from GPflow/develop
Merge pull request #1757 from GPflow/develop
Tip revision: a365045
RELEASE.md
Release notes for all past releases are available in the ['Releases' section](https://github.com/GPflow/GPflow/releases) of the GPflow GitHub Repo. [HOWTO_RELEASE.md](HOWTO_RELEASE.md) explains just that.
# Release x.y.z (template for future releases)
<INSERT SMALL BLURB ABOUT RELEASE FOCUS AREA AND POTENTIAL TOOLCHAIN CHANGES>
## Breaking Changes
* <DOCUMENT BREAKING CHANGES HERE>
* <THIS SECTION SHOULD CONTAIN API AND BEHAVIORAL BREAKING CHANGES>
## Known Caveats
* <CAVEATS REGARDING THE RELEASE (BUT NOT BREAKING CHANGES).>
* <ADDING/BUMPING DEPENDENCIES SHOULD GO HERE>
* <KNOWN LACK OF SUPPORT ON SOME PLATFORM SHOULD GO HERE>
## Major Features and Improvements
* <INSERT MAJOR FEATURE HERE, USING MARKDOWN SYNTAX>
* <IF RELEASE CONTAINS MULTIPLE FEATURES FROM SAME AREA, GROUP THEM TOGETHER>
## Bug Fixes and Other Changes
* <SIMILAR TO ABOVE SECTION, BUT FOR OTHER IMPORTANT CHANGES / BUG FIXES>
* <IF A CHANGE CLOSES A GITHUB ISSUE, IT SHOULD BE DOCUMENTED HERE>
* <NOTES SHOULD BE GROUPED PER AREA>
## Thanks to our Contributors
This release contains contributions from:
<INSERT>, <NAME>, <HERE>, <USING>, <GITHUB>, <HANDLE>
# Release 2.3.2 (next upcoming release in progress)
<INSERT SMALL BLURB ABOUT RELEASE FOCUS AREA AND POTENTIAL TOOLCHAIN CHANGES>
## Breaking Changes
* <DOCUMENT BREAKING CHANGES HERE>
* <THIS SECTION SHOULD CONTAIN API AND BEHAVIORAL BREAKING CHANGES>
## Known Caveats
* <CAVEATS REGARDING THE RELEASE (BUT NOT BREAKING CHANGES).>
* <ADDING/BUMPING DEPENDENCIES SHOULD GO HERE>
* <KNOWN LACK OF SUPPORT ON SOME PLATFORM SHOULD GO HERE>
## Major Features and Improvements
* <INSERT MAJOR FEATURE HERE, USING MARKDOWN SYNTAX>
* <IF RELEASE CONTAINS MULTIPLE FEATURES FROM SAME AREA, GROUP THEM TOGETHER>
## Bug Fixes and Other Changes
* <SIMILAR TO ABOVE SECTION, BUT FOR OTHER IMPORTANT CHANGES / BUG FIXES>
* <IF A CHANGE CLOSES A GITHUB ISSUE, IT SHOULD BE DOCUMENTED HERE>
* <NOTES SHOULD BE GROUPED PER AREA>
## Thanks to our Contributors
This release contains contributions from:
<INSERT>, <NAME>, <HERE>, <USING>, <GITHUB>, <HANDLE>
# Release 2.3.1
This is a bug-fix release, primarily for the GPR posterior object.
## Bug Fixes and Other Changes
* GPR posterior
* Fix the calculation in the GPR posterior object (#1734).
* Fixes leading dimension issues with `GPRPosterior._conditional_with_precompute()` (#1747).
* Make `gpflow.optimizers.Scipy` able to handle unused / unconnected variables. (#1745).
* Build
* Fixed broken CircleCi build (#1738).
* Update CircleCi build to use next-gen Docker images (#1740).
* Fixed broken triggering of docs generation (#1744).
* Make all slow tests depend on fast tests (#1743).
* Make `make dev-install` also install the test requirements (#1737).
* Documentation
* Fixed broken link in `README.md` (#1736).
* Fix broken build of `cglb.ipynb` (#1742).
* Add explanation of how to run notebooks locally (#1729).
* Fix formatting in notebook on Heteroskedastic Likelihood (#1727).
* Fix broken link in introduction (#1718).
* Test suite
* Amends `test_gpr_posterior.py` so it will cover leading dimension uses.
## Thanks to our Contributors
This release contains contributions from:
st--, jesnie, johnamcleod, Andrew878
# Release 2.3.0
## Major Features and Improvements
* Refactor posterior base class to support other model types. (#1695)
* Add new posterior class to enable faster predictions from the GPR/SGPR models. (#1696, #1711)
* Construct Parameters from other Parameters and retain properties. (#1699)
* Add CGLB model (#1706)
## Bug Fixes and Other Changes
* Fix unit test failure when using TensorFlow 2.5.0 (#1684)
* Upgrade black formatter to version 20.8b1 (#1694)
* Remove erroneous DeprecationWarnings (#1693)
* Fix SGPR derivation (#1688)
* Fix tests which fail with TensorFlow 2.6.0 (#1714)
## Thanks to our Contributors
This release contains contributions from:
johnamcleod, st--, Andrew878, tadejkrivec, awav, avullo
# Release 2.2.1
Bugfix for creating the new posterior objects with `PrecomputeCacheType.VARIABLE`.
# Release 2.2.0
The main focus of this release is the new "Posterior" object introduced by
PR #1636, which allows for a significant speed-up of post-training predictions
with the `SVGP` model (partially resolving #1599).
* For end-users, by default nothing changes; see Breaking Changes below if you
have written your own _implementations_ of `gpflow.conditionals.conditional`.
* After training an `SVGP` model, you can call `model.posterior()` to obtain a
Posterior object that precomputes all quantities not depending on the test
inputs (e.g. Choleskty of Kuu), and provides a `posterior.predict_f()` method
that reuses these cached quantities. `model.predict_f()` computes exactly the
same quantities as before and does **not** give any speed-up.
* `gpflow.conditionals.conditional()` forwards to the same "fused" code-path as
before.
## Breaking Changes
* `gpflow.conditionals.conditional.register` is deprecated and should not be
called outside of the GPflow core code. If you have written your own
implementations of `gpflow.conditionals.conditional()`, you have two options
to use your code with GPflow 2.2:
1. Temporary work-around: Instead of `gpflow.models.SVGP`, use the
backwards-compatible `gpflow.models.svgp.SVGP_deprecated`.
2. Convert your conditional() implementation into a subclass of
`gpflow.posteriors.AbstractPosterior`, and register
`get_posterior_class()` instead (see the "Variational Fourier Features"
notebook for an example).
## Known Caveats
* The Posterior object is currently only available for the `SVGP` model. We
would like to extend this to the other models such as `GPR`, `SGPR`, or `VGP`, but
this effort is beyond what we can currently provide. If you would be willing
to contribute to those efforts, please get in touch!
* The Posterior object does not currently provide the `GPModel` convenience
functions such as `predict_f_samples`, `predict_y`, `predict_log_density`.
Again, if you're willing to contribute, get in touch!
## Thanks to our Contributors
This release contains contributions from:
stefanosele, johnamcleod, st--
# Release 2.1.5
## Known Caveats
* GPflow requires TensorFlow >= 2.2.
## Deprecations
* The `gpflow.utilities.utilities` submodule has been deprecated and will be removed in GPflow 2.3. User code should access functions directly through `gpflow.utilities` instead (#1650).
## Major Features and Improvements
* Improves compatibility between monitoring API and Scipy optimizer (#1642).
* Adds `_add_noise_cov` method to GPR model class to make it more easily extensible (#1645).
## Bug Fixes
* Fixes a bug in ModelToTensorBoard (#1619) when `max_size=-1` (#1619)
* Fixes a dynamic shape issue in the quadrature code (#1626).
* Fixes #1651, a bug in `fully_correlated_conditional_repeat` (#1652).
* Fixes #1653, a bug in the "fallback" code path for multioutput Kuf (#1654).
* Fixes a bug in the un-whitened code path for the fully correlated conditional function (#1662).
* Fixes a bug in `independent_interdomain_conditional` (#1663).
* Fixes an issue with the gpflow.config API documentation (#1664).
* Test suite
* Fixes the test suite for TensorFlow 2.4 / TFP 0.12 (#1625).
* Fixes mypy call (#1637).
* Fixes a bug in test_method_equivalence.py (#1649).
## Thanks to our Contributors
This release contains contributions from:
johnamcleod, st--, vatsalaggarwal, sam-willis, vdutor