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# RRoG-GNN Runner
This repo runs the current RRoG/TRM-on-GNN experiment grid.
Core rule:
```text
view/graph aggregation happens once; recursive compute is edge-free hidden-state refinement.
```
The main reported table is:
```text
Task x Backbone -> classic baseline
Task x Backbone x fixed-RRoG -> delta against the matching classic row
```
`classic` is the non-RRoG baseline for every backbone: `T=0`, `n_sup=1`.
## One-command Run On 2x A6000
On a clean machine with two visible GPUs:
```bash
git clone git@github.com:YurenHao0426/rrog-gnn-runner.git
cd rrog-gnn-runner
./scripts/setup_and_run_two_a6000.sh
```
Defaults:
- GPU0: `zinc-cycle56` over 17 backbones, `classic + fixed-rrog`
- GPU1: `ogbg-molhiv` over 17 backbones, `classic + fixed-rrog`
- Results: `runs/*.json`
- Logs: `logs/*.log`
- Summaries: `summaries/*.md`
If the environment already has compatible `torch`, `torch_geometric`, and `ogb`:
```bash
SKIP_SETUP=1 ./scripts/setup_and_run_two_a6000.sh
```
To override CUDA wheel index during setup:
```bash
TORCH_INDEX_URL=https://download.pytorch.org/whl/cu121 ./scripts/setup_env.sh
```
## Common Commands
Smoke test:
```bash
./scripts/setup_env.sh
DEVICE=cuda:0 ./scripts/run_smoke.sh
```
Run the paired ZINC matrix only:
```bash
DEVICE=cuda:0 EPOCHS=200 ./scripts/run_zinc_cycle56_full.sh
```
Run one OGB molecular task:
```bash
TASK=ogbg-molhiv DEVICE=cuda:1 EPOCHS=100 ./scripts/run_ogb_mol_task_full.sh
```
Run the same OGB task with the lighter fixed recursion used by the ZINC sweep:
```bash
TASK=ogbg-molhiv DEVICE=cuda:1 EPOCHS=100 FIXED_T=1 FIXED_NS=3 ./scripts/run_ogb_mol_task_full.sh
```
Run all selected OGB molecular tasks serially on one GPU:
```bash
DEVICE=cuda:1 ./scripts/run_ogb_mol_all_tasks.sh
```
Collect summaries:
```bash
./scripts/collect_results.sh
```
## Backbones
The implemented 2D view/backbone list is shared across ZINC and OGB:
```text
gin, gine, gcn, graphsage, gatv2, graphconv, transformer, pna,
gen, film, resgated, tag, sgc, cheb, arma, mf, appnp
```
For ZINC `gine`, there are no bond features, so GINE uses a learned constant edge token.
For OGB molecular tasks, GINE and edge-aware backbones use OGB bond encodings.
## Notes
- Runs are resumable at the cell level: scripts skip existing expected JSON files.
- ZINC cycle-count cache is generated under `data/cycle_cache`.
- OGB datasets are downloaded under `data/ogb`.
- Override data/runs locations with `RROG_DATA_DIR` and `RROG_RUNS_DIR`.
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