repro-env

name	repro-env
description	Reproduce a working project environment from one lab server on another — code at the same commit, a CUDA-compatible python env, and a smoke test. Use for "make this run on host B too" or setting up a new server.

Reproduce an environment

Input: a project (directory on the source host) and a target host.

1. Fingerprint the source via run_command on host A:

   • code: git -C <dir> remote -v; git -C <dir> rev-parse HEAD; git -C <dir> status --porcelain | head
   • env: which python; python -V; pip freeze | head -60 (or conda env export --no-builds | head -60 for conda projects)
   • torch: python -c 'import torch; print(torch.__version__, torch.version.cuda)'

2. Check the target's ceiling. Driver and CUDA on B come from list_hosts. If B's driver can't run A's CUDA build, pick the closest torch build that works on B — and say so explicitly.

3. Code onto B: clone from the git remote and check out the same commit. No usable remote? → copy_path the directory (excluding wandb/, runs/, old checkpoints) after the user approves the size.

4. Env on B — the slow part goes in a detached tmux via start_session (background) so nothing times out: create the venv/conda env with matching python; install torch matching B's CUDA; pip install -r requirements.txt if present, else the frozen list from step 1.

5. Smoke test:

   python -c 'import torch; print(torch.cuda.is_available())'
   

   then import the project's main package or run its smallest entrypoint with --help.

Report

What matches (commit, python, torch), what differs and why (driver limits, unavailable pins), and the exact activation command to use on B. Never modify anything on the SOURCE host.