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Update version to 0.1.2 (#205)
Summary: Main change is to require gpytorch>=0.3.4 in order to circumvent a PyTorch bug Pull Request resolved: #205 Reviewed By: eytan Differential Revision: D16177392 Pulled By: Balandat fbshipit-source-id: 79edd0d2f04599d59b26762e3ab50e9aaaae7ab8
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.conda/meta.yaml

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- python>=3.6
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run:
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- pytorch>=1.1
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- gpytorch>=0.3.3
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- gpytorch>=0.3.4
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- scipy
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test:

CHANGELOG.md

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The release log for BoTorch.
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## [0.1.2] - July 9, 2019
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Maintenance release
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#### Bug fixes
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* Avoid [PyTorch bug]((https://github.com/pytorch/pytorch/issues/22353)
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resulting in bad gradients on GPU by requiring GPyTorch >= 0.3.4
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* Fixes to resampling behavior in MCSamplers (#204)
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#### Experimental Features
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* Linear truncated kernel for multi-fidelity bayesian optimization (#192)
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* SingleTaskMultiFidelityGP for GP models that have fidelity parameters (#181)
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## [0.1.1] - June 27, 2019
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API updates, more robust model fitting

README.md

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**Installation Requirements**
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- Python >= 3.6
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- PyTorch >= 1.1
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- gpytorch >= 0.3.3
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- gpytorch >= 0.3.4
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- scipy
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botorch/__init__.py

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from .utils import manual_seed
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__version__ = "0.1.1"
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__version__ = "0.1.2"
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__all__ = [

docs/getting_started.md

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- Python >= 3.6
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- PyTorch >= 1.1
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- gpytorch >= 0.3.3
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- gpytorch >= 0.3.4
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- scipy
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BoTorch is easily installed via

environment.yml

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- gpytorch
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dependencies:
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- pytorch>=1.1
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- gpytorch>=0.3.3
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- gpytorch>=0.3.4
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- scipy

setup.py

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long_description=long_description,
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long_description_content_type="text/markdown",
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python_requires=">=3.6",
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install_requires=["torch>=1.1", "gpytorch>=0.3.3", "scipy"],
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install_requires=["torch>=1.1", "gpytorch>=0.3.4", "scipy"],
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packages=find_packages(),
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extras_require={
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"dev": DEV_REQUIRES,

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