dl4bi 0.1.0

Deep Learning for Bayesian Inference (DL4BI)

Deep Learning for Bayesian Inference (dl4bi)

Install

Install with the appropriate command. If JAX isn't installed already, we recommend using one of the dl4bi[<jax-version>] installs.

pip install dl4bi # dl4bi
pip install dl4bi[cpu] # dl4bi + jax for CPU
pip install dl4bi[cuda12] # dl4bi + jax for CUDA-12
pip install dl4bi[cuda13] # dl4bi + jax for CUDA-13

View Documentation (Locally)

git clone [e-mail]:MLGlobalHealth/dl4bi.git
cd dl4bi
uv run --with pdoc pdoc --docformat google --math dl4bi

Example benchmarks can be found here.

Development Setup

• Install uv: curl -LsSf https://astral.sh/uv/install.sh | sh
• Clone the repository and cd into it: git clone [e-mail]:MLGlobalHealth/dl4bi.git && cd dl4bi
• Install the latest Python with uv: uv python install
• Sync the project environment:
  • CPU JAX: uv sync --extra cpu
  • CUDA 12 JAX: uv sync --extra cuda12
  • CUDA 13 JAX: uv sync --extra cuda13
• uv sync creates .venv, installs the project in editable mode, includes the default dev dependency group, and picks a Python interpreter compatible with the project's requires-python
• Before making changes, install the shared development hooks: uv run pre-commit install --install-hooks
• Verify the hook setup once per clone with: uv run pre-commit run --all-files
• Keep the hooks installed for local development; commits on main run pytest -q tests through the shared pre-commit setup
• Run project commands through uv, e.g. uv run pytest or uv run python gp.py
• If you want to activate the virtualenv directly, use source .venv/bin/activate

Build and Publish to PyPI

1. Bump the package version:

uv version --bump patch --frozen

2. Build the source distribution and wheel:

uv build --no-sources

3. Publish to TestPyPI first:

UV_PUBLISH_TOKEN=$TEST_PYPI_TOKEN uv publish \
  --publish-url https://test.pypi.org/legacy/ \
  --check-url https://test.pypi.org/simple/

4. After validating the release, publish the same artifacts to PyPI:

UV_PUBLISH_TOKEN=$PYPI_TOKEN uv publish

5. Smoke-test the published install targets in fresh environments:

uv run --isolated --with "dl4bi==<version>" --no-project -- python -c "import dl4bi"
uv run --isolated --with "dl4bi[cpu]==<version>" --no-project -- python -c "import dl4bi"
uv run --isolated --with "dl4bi[cuda12]==<version>" --no-project -- python -c "import dl4bi"
uv run --isolated --with "dl4bi[cuda13]==<version>" --no-project -- python -c "import dl4bi"