28 lines
1.0 KiB
Markdown
28 lines
1.0 KiB
Markdown
# careless
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Scaling and merging of X-ray diffraction data with approximate Bayesian
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inference (variational merging), built on TensorFlow.
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- Upstream: https://github.com/rs-station/careless
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- License: MIT
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## How it is built
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Upstream recommends a fresh conda env, but repo.anaconda.com is not
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reachable from Ra, so the build uses uv instead: it fetches a standalone
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Python 3.12 into `$PREFIX/python` (upstream supports >=3.9,<3.13), creates
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`$PREFIX/venv`, and runs `uv pip install careless[cuda]==<version>` into
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it. The `[cuda]` extra pulls the NVIDIA libraries as pip wheels, so the
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same install works on GPU and CPU-only Ra nodes.
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`uv` must be on PATH on the build host (e.g. `pip install --user uv`).
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Loading the module puts the venv's `bin/` on `PATH` (the `careless`
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command is directly available, no activation needed) and sets
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`CARELESS_ENV` to the venv path.
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## Adding a new version
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Add the version under `versions:` in `files/config.yaml`, then on a Ra
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login node: `modbuild build <version>` (modbuild/2.1.2).
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