From d12722525fc010a3910b5152c72654a2ade5eac4 Mon Sep 17 00:00:00 2001
From: YurenHao0426 <Blackhao0426@gmail.com>
Date: Wed, 17 Jun 2026 11:19:27 -0500
Subject: Initial import

---
 diag/run_rec.sh | 13 +++++++++++++
 1 file changed, 13 insertions(+)
 create mode 100644 diag/run_rec.sh

(limited to 'diag/run_rec.sh')

diff --git a/diag/run_rec.sh b/diag/run_rec.sh
new file mode 100644
index 0000000..632498d
--- /dev/null
+++ b/diag/run_rec.sh
@@ -0,0 +1,13 @@
+#!/usr/bin/env bash
+# Step-2: recursive GNN + full PTRM on ZINC ring-counting. Does per-step noise + best-Q@K
+# selection break the 1-WL counting ceiling that input-RNI couldn't? Averaging vs selection.
+set -uo pipefail
+cd /home/yurenh2/rrog
+export PYTHONPATH=/home/yurenh2/rrog
+echo "host=$(hostname) gpu=${CUDA_VISIBLE_DEVICES:-?} start=$(date -Is)"
+run() { echo "===== $* ====="; python3 diag/train_rec.py "$@" --epochs 200 --seed 0 || echo "!! FAILED $*"; }
+run --sigma 0   --K 1  --select bestq    # deterministic recursive baseline (~1-WL ceiling)
+run --sigma 0.1 --K 8  --select none     # averaging over rollouts (RNI-style null)
+run --sigma 0.1 --K 8  --select bestq    # PTRM-proper: per-step noise + best-Q@K selection
+run --sigma 0.2 --K 16 --select bestq    # scaled noise + rollouts
+echo "done=$(date -Is)"
-- 
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