duan_jandClaude Fable 5
b55d6c1d91
careless installs plain careless (CPU). careless-gpu also installs plain careless but declares cuda/12.8.1 as build_requires/runtime_deps (jfjoch_viewer pattern) instead of pip-bundling CUDA via the [cuda] extra. Both builds honor UV_CACHE_DIR to share one download cache. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
careless-gpu
GPU build of careless (see ../careless/ for the CPU module and the full
background). Scaling and merging of X-ray diffraction data with approximate
Bayesian inference (variational merging), built on TensorFlow.
- Upstream: https://github.com/rs-station/careless
- License: MIT
How it differs from the careless module
- CUDA is not pip-installed (no
[cuda]extra, saves several GB): the clustercuda/12.8.1module provides it instead, declared asbuild_requires/runtime_deps(same pattern asjfjoch_viewer).runtime_depsmatters because TensorFlow dlopens the CUDA libraries when careless runs, so cuda must auto-load with this module. - If careless reports missing cuDNN at runtime, the cuda module does not
ship it; the fallback is installing
careless[cuda]inbuildinstead.
The venv layout, uv usage, and cache handling are identical to careless.
To share one download cache between both builds, run each with
UV_CACHE_DIR=<shared path> modbuild build <version> — a cache outside
PREFIX is kept, an in-PREFIX cache is removed after a successful install.
Adding a new version
Add the version under versions: in files/config.yaml, then on a Ra
login node: modbuild build <version> (modbuild/2.1.2).