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#!/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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