diff options
Diffstat (limited to 'experiments/run_dblp_depth.py')
| -rw-r--r-- | experiments/run_dblp_depth.py | 8 |
1 files changed, 3 insertions, 5 deletions
diff --git a/experiments/run_dblp_depth.py b/experiments/run_dblp_depth.py index d63b94a..f91440a 100644 --- a/experiments/run_dblp_depth.py +++ b/experiments/run_dblp_depth.py @@ -11,8 +11,7 @@ import os import time from torch_geometric.datasets import CitationFull from src.data import build_normalized_adj, build_row_normalized_adj, spmm, precompute_traces -from src.trainers import BPTrainer, DFATrainer, GraphGrAPETrainer -from benchmark_efficient import GraphGrAPEEfficient +from src.trainers import BPTrainer, DFATrainer, KAFTTrainer device = 'cuda:0' SEEDS = [0, 1, 2, 3, 4] @@ -108,7 +107,7 @@ def main(): row = {} for mname, cls, extra in [('BP', BPTrainer, {}), ('DFA', DFATrainer, dict(diffusion_alpha=0.5, diffusion_iters=10)), - ('GrAPE', GraphGrAPETrainer, grape_extra)]: + ('GrAPE', KAFTTrainer, grape_extra)]: accs = [train_one(cls, common, extra, s) for s in SEEDS] row[mname] = {'mean': float(np.mean(accs)), 'std': float(np.std(accs))} results[key] = row @@ -123,7 +122,6 @@ def main(): common = dict(data=dblp, hidden_dim=64, lr=0.01, weight_decay=5e-4, num_layers=L, residual_alpha=0.0, backbone=bb) bp_ms = time_method(BPTrainer, common, {}) - eff_ms = time_method(GraphGrAPEEfficient, common, dict(lr_feedback=0.5, num_probes=64, max_topo_power=3, diff_alpha=0.5, align_every=10)) key = f"DBLP_eff|{bb}|L={L}" @@ -146,7 +144,7 @@ def main(): key = f"{ds_name}|{bb}|L={L}|lr=0.01" row = {} for mname, cls, extra in [('BP', BPTrainer, {}), - ('GrAPE', GraphGrAPETrainer, grape_extra)]: + ('GrAPE', KAFTTrainer, grape_extra)]: accs = [train_one(cls, common, extra, s) for s in SEEDS] row[mname] = {'mean': float(np.mean(accs)), 'std': float(np.std(accs))} results[key] = row |