Mapping Tmux to PID and Process Validation | Generated by AI

Home 2026.04

Review of my approach

What worked

Weaknesses

  1. Captured both tmux panes blindly. I ran capture-pane -t 0 and -t 1 in parallel before checking whether they were different views. They were identical (same training, two attached clients). Better: one capture first, or tmux list-panes -a -F '#{session_name} #{pane_tty} #{pane_pid}' to map sessions to the actual train.py PID.

  2. Used a stale snapshot. capture-pane returned the visible scrollback. The last iter shown was 6800, but the process has been running for ~18 hours (1089 CPU-min, started Apr 29) and the checkpoint timestamp (06:42) is from step 6500 — current iter is almost certainly past 7000 by now. I should have noted the snapshot’s freshness, or grabbed more scrollback (-S -500), or watched a few seconds of live output to confirm it’s still advancing.

  3. No liveness check. I never verified the GPU is actually doing work right now. A nvidia-smi would confirm training isn’t hung; ps only shows the process exists.

  4. ETA was rough. I averaged 9.34s/iter and added a small fudge for checkpoint saves, but ignored that every 500th iter does a val pass. The eval log line at step 5000 also shows ~29s for that iter — that overhead repeats every 500 iters, not every 1000. Real ETA is probably ~20–30 min longer than I quoted.

  5. Didn’t sanity-check disk. Checkpoint is 1.4 GB and rewrites in place, so it’s bounded — but I should have glanced at df since OOD writes would silently kill training.

What I’d do differently next time: map tmux→PID first, then one fresh capture of the correct pane plus nvidia-smi and df -h . — fewer redundant calls, stronger answer.

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