Version 0.3.0: Multi-Objective Bayesian Optimization (pytorch#472)

Summary:
Pull Request resolved: pytorch#472

see title

Reviewed By: Balandat

Differential Revision: D22393843

fbshipit-source-id: 22f071c3e6eaaca3a09dd5db4e23f8b54450000d

Author: sdaulton

CHANGELOG.md

@@ -3,6 +3,38 @@
 The release log for BoTorch.
 
 
+## [0.3.0] - July 6, 2020
+
+Multi-Objective Bayesian Optimization
+
+#### New Features
+* Multi-Objective Acquisition Functions (#466)
+  * q-Expected Hypervolume Improvement
+  * q-ParEGO
+  * Analytic Expected Hypervolume Improvement with auto-differentiation
+* Multi-Objective Utilities (#466)
+  * Pareto Computation
+  * Hypervolume Calculation
+  * Box Decomposition algorithm
+* Multi-Objective Test Functions (#466)
+  * Suite of synthetic test functions for multi-objective, constrained
+  optimzation
+* Multi-Objective Tutorial (#468)
+* Abstract ConstrainedBaseTestProblem (#454)
+* Add optimize_acqf_list method for sequentially, greedily optimizing 1 candidate
+from each provided acquisition function (d10aec911b241b208c59c192beb9e4d572a092cd)
+
+
+#### Bug fixes
+* Fixed re-arranging mean in MultiTask MO models (#450).
+
+#### Other changes
+* Move gpt_posterior_settings into models.utils (#449)
+* Allow specifications of batch dims to collapse in samplers (#457)
+* Remove outcome transform before model-fitting for sequential model fitting
+in MO models (#458)
+
+
 ## [0.2.5] - May 14, 2020
 
 Bugfix Release

botorch/__init__.py

@@ -23,7 +23,7 @@
 from botorch.utils import manual_seed
 
 
-__version__ = "0.2.5"
+__version__ = "0.3.0"
 
 
 __all__ = [

setup.py

@@ -66,7 +66,7 @@
     long_description=long_description,
     long_description_content_type="text/markdown",
     python_requires=">=3.7",
-    install_requires=["torch>=1.4", "gpytorch>=1.1.1", "scipy"],
+    install_requires=["torch>=1.5", "gpytorch>=1.1.1", "scipy"],
     packages=find_packages(),
     extras_require={
         "dev": DEV_REQUIRES,