Adjustments to setup.py and README for torch Sobol

.travis.yml

@@ -9,9 +9,10 @@ matrix:
     - name: "GPyTorch + PyTorch stable (Python 3.6)"
       python: "3.6"
       install:
-        - pip install -q cython numpy
-        # TODO: Remove when locked to upcoming GPyTorch release 0.3.2
-        - pip install -q git+https://github.com/cornellius-gp/gpytorch.git@8f0d338d42222689f0106f5f29e62ef4777a392f
+        # TODO: Remove once GPyTorch 0.3.2 is released and marked a dep. of botorch
+        - pip install -q git+https://github.com/cornellius-gp/gpytorch.git@32911e3b51901917c0f14101972581c1295b5edb
+        # TODO: Remove once PyTorch 1.1 is released and marked a dep. of botorch
+        - pip install -q torch_nightly -f https://download.pytorch.org/whl/nightly/cpu/torch_nightly.html
         - pip install -q -e .[test]
       script:
         - pytest -ra --cov=. --cov-report term-missing
@@ -22,19 +23,21 @@ matrix:
       python: "3.7"
       dist: xenial
       install:
-        - pip install -q cython numpy
-        # TODO: Remove when locked to upcoming GPyTorch release 0.3.2
-        - pip install -q git+https://github.com/cornellius-gp/gpytorch.git@8f0d338d42222689f0106f5f29e62ef4777a392f
+        # TODO: Remove once GPyTorch 0.3.2 is released and marked a dep. of botorch
+        - pip install -q git+https://github.com/cornellius-gp/gpytorch.git@32911e3b51901917c0f14101972581c1295b5edb
+        # TODO: Remove once PyTorch 1.1 is released and marked a dep. of botorch
+        - pip install -q torch_nightly -f https://download.pytorch.org/whl/nightly/cpu/torch_nightly.html
         - pip install -q -e .[test]
       script:
         - pytest -ra --cov=. --cov-report term-missing
     # Latest versions
     - name: "GPyTorch + PyTorch latest"
       python: "3.6"
       install:
-        - pip install -q cython numpy
-        - pip install -q torch_nightly -f https://download.pytorch.org/whl/nightly/cpu/torch_nightly.html;
+        # TODO: Fix gpytorch installation to work with torch nightly in pip,
+        # so we don't have to reinstall torch nightly after installing stable
         - pip install -q git+https://github.com/cornellius-gp/gpytorch.git
+        - pip install -q torch_nightly -f https://download.pytorch.org/whl/nightly/cpu/torch_nightly.html
         - pip install -q -e .[test]
       script:
         - pytest -ra --cov=. --cov-report term-missing
@@ -57,9 +60,10 @@ matrix:
     - name: "Docs: Sphinx (Python 3.6)"
       python: "3.6"
       install:
-        - pip install -q cython numpy
-        # TODO: Remove when locked to upcoming GPyTorch release 0.3.2
-        - pip install -q git+https://github.com/cornellius-gp/gpytorch.git@8f0d338d42222689f0106f5f29e62ef4777a392f
+        # TODO: Remove once GPyTorch 0.3.2 is released and marked a dep. of botorch
+        - pip install -q git+https://github.com/cornellius-gp/gpytorch.git@32911e3b51901917c0f14101972581c1295b5edb
+        # TODO: Remove once PyTorch 1.1 is released and marked a dep. of botorch
+        - pip install -q torch_nightly -f https://download.pytorch.org/whl/nightly/cpu/torch_nightly.html
         - pip install -q -e .[dev]
       script:
         # warnings treated as errors

CONTRIBUTING.md

@@ -1,11 +1,23 @@
-# Contributing to botorch
-We want to make contributing to botorch is as easy and transparent as possible.
+# Contributing to BoTorch
+We want to make contributing to BoTorch is as easy and transparent as possible.
+
+
+## Development installation
+
+To get the development installation with all the necessary dependencies for
+linting, testing, and building the documentation, run the following:
+```bash
+git clone https://github.com/facebookexternal/botorch.git
+cd botorch
+pip install -e .[dev]
+```
+
 
 ## Our Development Process
 
 #### Code Style
 
-botorch uses the [black](https://github.com/ambv/black) code formatter to
+BoTorch uses the [black](https://github.com/ambv/black) code formatter to
 enforce a common code style across the code base. black is installed easily via
 pip using `pip install black`, and run locally by calling
 ```bash
@@ -20,7 +32,7 @@ Travis will fail on your PR if it does not adhere to the black formatting style.
 
 
 #### Type Hints
-botorch is fully typed using python 3.6+
+BoTorch is fully typed using python 3.6+
 [type hints](https://www.python.org/dev/peps/pep-0484/).
 We expect any contributions to also use proper type annotations. While we
 currently do not enforce full consistency of these in Travis (type checkers can
@@ -40,7 +52,7 @@ python -m unittest
 
 #### Documentation
 
-botorch's website is also open source, and is part of this very repository (the
+BoTorch's website is also open source, and is part of this very repository (the
 code can be found in the [website](../website/) folder).
 It is built using [Docusaurus](https://docusaurus.io/), and consists of three
 main elements:
@@ -89,5 +101,5 @@ outlined on that page and do not file a public issue.
 
 
 ## License
-By contributing to botorch, you agree that your contributions will be licensed
+By contributing to BoTorch, you agree that your contributions will be licensed
 under the LICENSE file in the root directory of this source tree.

README.md

@@ -1,47 +1,91 @@
-<img width="300" src="./botorch_logo_lockup.svg" alt="BoTorch Logo" />
+<a href="https://botorch.org">
+  <img width="300" src="./botorch_logo_lockup.svg" alt="BoTorch Logo" />
+</a>
 
 [![Build Status](
   https://travis-ci.com/facebookexternal/botorch.svg?token=esFvpzSw7sLSsfe1PAr1&branch=master
 )](https://travis-ci.com/facebookexternal/botorch)
 
 
-BoTorch is a library for Bayesian Optimization in PyTorch.
+BoTorch is a library for Bayesian Optimization built on PyTorch.
 
-It is currently an alpha version under active development - be warned!
+*BoTorch is currently in alpha and under active development - be warned*!
 
 
-## Installation
+### Why BoTorch
+BoTorch
+* Provides a modular and easily extensible interface for composing Bayesian
+  optimization primitives, including probabilistic models, acquisition functions,
+  and optimizers.
+* Harnesses the power of PyTorch, including auto-differentiation, native support
+  for highly parallelized modern hardware (e.g. GPUs) using device-agnostic code,
+  and a dynamic computation graph.
+* Supports Monte Carlo-based acquisition functions via the
+  [reparameterization trick](https://arxiv.org/abs/1312.6114), which makes it
+  straightforward to implement new ideas without having to impose restrictive
+  assumptions about the underlying model.
+* Enables seamless integration with deep and/or convolutional architectures in PyTorch.
+* Has first-class support for state-of-the art probabilistic models in
+  [GPyTorch](http://www.gpytorch.ai/), including support for multi-task Gaussian
+  Processes (GPs) deep kernel learning, deep GPs, and approximate inference.
 
-##### Setup Requirements (TODO: Remove once we can use torch Sobol)
 
-The following are required to run the setup:
+### Target Audience
 
-- Python >= 3.6
-- numpy
-- cython
+The primary audience for hands-on use of BoTorch are researchers and
+sophisticated practitioners in Bayesian Optimization and AI.
+
+We recommend using BoTorch as a low-level API for implementing new algorithms
+for [Ax](https://github.com/facebook/Ax). Ax has been designed to be
+an easy-to-use platform for end-users, which at the same time is flexible enough
+for Bayesian Optimization researchers to plug into for handling of feature
+transformations, (meta-)data management, storage, etc.
 
+We recommend that end-users who are not actively doing research on Bayesian
+Optimization simply use Ax.
 
-##### Installation Requirements
 
-- PyTorch >= 1.0.1
-- gpytorch >= 0.3.0
+## Installation
+
+#### Installation Requirements
+
+- Python >= 3.6
+- PyTorch nightly (**TODO:** peg to PyTorch 1.1 once released)
+- gpytorch >= 0.3.1 (**TODO:** peg to GPyTorch 0.3.2 once released)
 - scipy
 
-**Important:**
-You will want to have you PyTorch build link against **MKL** (the non-optimized
-version of botorch can be up to an order of magnitude slower). Setting this up
-manually can be tricky - to make sure this works please use the Anaconda
-installation instructions on https://pytorch.org/.
+**Important note for MacOS users:**
+* You will want to make sure your PyTorch build is linked against MKL (the
+  non-optimized version of BoTorch can be up to an order of magnitude slower in
+  some settings). Setting this up manually on MacOS can be tricky - to ensure
+  this works properly please follow the
+  [PyTorch installation instructions](https://pytorch.org/get-started/locally/).
+* If you need CUDA on MacOS, you will need to build PyTorch from source. Please
+  consult the PyTorch installation instructions above.
 
 
-### Install botorch
+#### Installing BoTorch
 
-To run the botorch setup, you'll need cython (**TODO:** Remove)
+The latest release of BoTorch is easily installed using either pip or conda:
 ```bash
-pip install cython
+pip install botorch
 ```
 
-We recommend installing botorch using pip via ssh:
+**TODO: Conda install**
+
+
+If you'd like to try our bleeding edge features (and don't mind running into an
+occasional bug here or there), you can install the latest master from GitHub
+(this will also require installing the current GPyTorch master)::
+```bash
+pip install git+https://github.com/cornellius-gp/gpytorch.git
+pip install git+https://github.com/facebookexternal/botorch.git
+```
+
+
+#### Installing BoTorch from the private repo **TODO: REMOVE**
+
+BoTorch is easily installed using pip:
 ```bash
 pip install git+ssh://[email protected]/facebookexternal/botorch.git
 ```
@@ -63,14 +107,9 @@ To customize the installation, you can also run the following instead:
 
 
 
-## Installation using conda
-
-**TODO: conda install is unsupported until the repo is public**
-
-
 ## Contributing
 See the [CONTRIBUTING](CONTRIBUTING.md) file for how to help out.
 
 
 ## License
-botorch is MIT licensed, as found in the LICENSE file.
+BoTorch is MIT licensed, as found in the LICENSE file.

botorch/__init__.py

@@ -1,12 +1,20 @@
 #!/usr/bin/env python3
 
+import os
+import re
+
 from . import acquisition, exceptions, models, optim, posteriors, test_functions
 from .cross_validation import batch_cross_validation
 from .fit import fit_gpytorch_model
 from .gen import gen_candidates_scipy, gen_candidates_torch, get_best_candidates
 from .utils import manual_seed
 
 
+# get version string from setup.py
+with open(os.path.join(os.path.dirname(__file__), os.pardir, "setup.py"), "r") as f:
+    __version__ = re.search(r"version=['\"]([^'\"]*)['\"]", f.read(), re.M).group(1)
+
+
 __all__ = [
     "acquisition",
     "batch_cross_validation",

botorch/acquisition/sampler.py

@@ -11,10 +11,10 @@
 import torch
 from torch import Tensor
 from torch.nn import Module
+from torch.quasirandom import SobolEngine
 
 from ..exceptions import UnsupportedError
 from ..posteriors import Posterior
-from ..qmc.sobol import SobolEngine
 from ..utils.sampling import draw_sobol_normal_samples, manual_seed
 
 

botorch/qmc/__init__.py

@@ -1,7 +1,8 @@
 #! /usr/bin/env python3
 
+from torch.quasirandom import SobolEngine
+
 from .normal import MultivariateNormalQMCEngine, NormalQMCEngine
-from .sobol import SobolEngine
 
 
 __all__ = ["MultivariateNormalQMCEngine", "NormalQMCEngine", "SobolEngine"]