mbirtorch
A PyTorch port of mbirjax: high-performance tomographic reconstruction with multi-GPU support.
This repo is the home for the port evaluated in
mbirjax_plans/plans/torch_port/port_plan.md (checked out parallel to this
repo). The plan defines the motivation, the parity gates against mbirjax,
the incremental phase plan, and a progress record; its findings pages and the
supporting scripts live alongside it under mbirjax_plans/plans/.
Setup
Create the conda environment and install the package in editable mode:
conda env create -f environment.yml
conda activate mbirtorch
pip install -e ".[test]"
Tests
dev_scripts/run_tests.sh
Caches
mbirtorch keeps one on-disk cache: compiled torch.compile artifacts, under
~/.mbirtorch/torch_cache. It exists to make cold starts fast -- with it, a
fresh process reuses prior compilations instead of recompiling (roughly 14 s
down to 2 s for a first small reconstruction). It grows with the number of
distinct compiled shapes and typically stays in the tens of megabytes; it is
never cleaned automatically. To remove it:
import mbirtorch
mbirtorch.clear_cache() # deletes ~/.mbirtorch entirely (recreated empty)
The location can be redirected by setting the TORCHINDUCTOR_CACHE_DIR
environment variable before the first compile (e.g. to node-local or scratch
storage on a cluster, where home quotas are tight); clear_cache() does not
touch a redirected location.
Everything else the package caches is in-memory only and is freed with the
objects that hold it (e.g. the per-model pixel-index cache); nothing besides
~/.mbirtorch is written to disk.
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