diff options
Diffstat (limited to 'experiments/run_cs_full.py')
| -rw-r--r-- | experiments/run_cs_full.py | 14 |
1 files changed, 7 insertions, 7 deletions
diff --git a/experiments/run_cs_full.py b/experiments/run_cs_full.py index d66fc59..d170e13 100644 --- a/experiments/run_cs_full.py +++ b/experiments/run_cs_full.py @@ -1,6 +1,6 @@ #!/usr/bin/env python3 """H19 CitationFull-CiteSeer (4.2K, deg 2.5, 6-class) — same regime as Planetoid CiteSeer. -Quick BP + GRAFT depth sweep to confirm/extend the 'GRAFT wins on real sparse citation' story.""" +Quick BP + KAFT depth sweep to confirm/extend the 'KAFT wins on real sparse citation' story.""" import torch, sys, numpy as np, time import torch.nn as nn, torch.nn.functional as F @@ -9,7 +9,7 @@ from torch_geometric.nn import GCNConv from torch_geometric.utils import add_self_loops, degree sys.path.insert(0, '/home/yurenh2/graph-grape') -from src.trainers import GraphGrAPETrainer +from src.trainers import KAFTTrainer DATA_ROOT = '/home/yurenh2/graph-grape/data/CFull' device = torch.device('cuda:0') @@ -90,7 +90,7 @@ def bp_one(L, seed, d, train_mask, val_mask, test_mask, epochs=200, lr=5e-3, hid return bt -def graft_one(L, seed, d, A_hat, A_row, A_row_T, train_mask, val_mask, test_mask, +def kaft_one(L, seed, d, A_hat, A_row, A_row_T, train_mask, val_mask, test_mask, epochs=200, lr=5e-3, hidden=128): torch.manual_seed(seed); np.random.seed(seed); torch.cuda.manual_seed_all(seed) data = { @@ -99,7 +99,7 @@ def graft_one(L, seed, d, A_hat, A_row, A_row_T, train_mask, val_mask, test_mask 'num_features': d.x.shape[1], 'num_classes': int(d.y.max())+1, 'num_nodes': d.num_nodes, 'traces': {}, } - trainer = GraphGrAPETrainer( + trainer = KAFTTrainer( data=data, hidden_dim=hidden, lr=lr, weight_decay=0.0, lr_feedback=0.5, num_probes=64, topo_mode='fixed_A', max_topo_power=3, diffusion_alpha=0.5, diffusion_iters=10, @@ -133,14 +133,14 @@ def main(): t0 = time.time() bp = bp_one(L, s, d, tm, vm, tem) t1 = time.time() - gf = graft_one(L, s, d, A_hat, A_row, A_row_T, tm, vm, tem) + gf = kaft_one(L, s, d, A_hat, A_row, A_row_T, tm, vm, tem) t2 = time.time() bp_accs.append(bp); gf_accs.append(gf) - print(f' L={L} s={s}: BP={bp:.4f}({t1-t0:.0f}s) GRAFT={gf:.4f}({t2-t1:.0f}s)', flush=True) + print(f' L={L} s={s}: BP={bp:.4f}({t1-t0:.0f}s) KAFT={gf:.4f}({t2-t1:.0f}s)', flush=True) bp_m, bp_sd = np.mean(bp_accs), np.std(bp_accs) gf_m, gf_sd = np.mean(gf_accs), np.std(gf_accs) bp_res[L] = (bp_m, bp_sd); gf_res[L] = (gf_m, gf_sd) - print(f'>>> L={L}: BP {bp_m:.4f}±{bp_sd:.4f} GRAFT {gf_m:.4f}±{gf_sd:.4f} Δ={gf_m-bp_m:+.3f}', flush=True) + print(f'>>> L={L}: BP {bp_m:.4f}±{bp_sd:.4f} KAFT {gf_m:.4f}±{gf_sd:.4f} Δ={gf_m-bp_m:+.3f}', flush=True) if __name__ == '__main__': |