Bean Machine
Overview
Bean Machine is a probabilistic programming language for inference over statistical models written in the Python language using a declarative syntax. Bean Machine is built on top of PyTorch and Bean Machine Graph, a custom C++ backend. Check out our tutorials and Quick Start to get started!
Installation
Bean Machine supports Python 3.7-3.10 and PyTorch 1.12.
Install the Latest Release with Pip
python -m pip install beanmachine
Install from Source
To download the latest Bean Machine source code from GitHub:
git clone https://github.com/facebookresearch/beanmachine.git
cd beanmachine
Then, you can choose from any of the following installation options.
Anaconda
We recommend using conda to manage the virtual environment and install the necessary build dependencies.
conda create -n {env name} python=3.8; conda activate {env name}
conda install -c conda-forge boost-cpp eigen=3.4.0
python -m pip install .
Docker
docker build -t beanmachine .
docker run -it beanmachine:latest bash
Validate Installation
If you would like to run the builtin unit tests:
python -m pip install "beanmachine[test]"
pytest src
License
Bean Machine is MIT licensed, as found in the LICENSE file.
3 maintainers
Metadata
3 maintainers
Release files for beanmachine 0.2.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| beanmachine-0.2.0.tar.gz | 450.3 kB | Details |
Built distributions (wheels)
Total release size: 20.8 MB
Release files / beanmachine-0.2.0.tar.gz
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Release files / beanmachine-0.2.0-cp310-cp310-win_amd64.whl
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Release files / beanmachine-0.2.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
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Release files / beanmachine-0.2.0-cp310-cp310-macosx_11_0_arm64.whl
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Release files / beanmachine-0.2.0-cp310-cp310-macosx_10_13_x86_64.whl
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Release files / beanmachine-0.2.0-cp38-cp38-macosx_11_0_arm64.whl
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