code: def logger(info):
      fold, epoch = info["fold"] + 1, info["epoch"]
      val_loss, test_acc = info["val_loss"], info["test_acc"]
      print(
          f"{fold:02d}/{epoch:03d}: Val Loss: {val_loss:.4f}, "
          f"Test Accuracy: {test_acc:.3f}"
      )
  
file_path: pytorch_geometric/benchmark/kernel/main.py
imports: import argparse
  from itertools import product
  from asap import ASAP
  from datasets import get_dataset
  from diff_pool import DiffPool
  from edge_pool import EdgePool
  from gcn import GCN, GCNWithJK
  from gin import GIN, GIN0, GIN0WithJK, GINWithJK
  from global_attention import GlobalAttentionNet
  from graclus import Graclus
  from graph_sage import GraphSAGE, GraphSAGEWithJK
  from sag_pool import SAGPool
  from set2set import Set2SetNet
  from sort_pool import SortPool
  from top_k import TopK
  from train_eval import cross_validation_with_val_set
label_desc: Use image node_id 1 for calling a global function with example usage: logger(info) without return types