code: def inference(model, test_loader, device, bf16):
      model.eval()
      for data in test_loader:
          data = data.to(device)
          if bf16:
              data.pos = data.pos.to(torch.bfloat16)
              model = model.to(torch.bfloat16)
          model(data.pos, data.batch)
  
file_path: pytorch_geometric/benchmark/points/train_eval.py
imports: import time
  import torch
  import torch.nn.functional
  from torch.optim import Adam
  from torch_geometric.loader import DataLoader
  from torch_geometric.profile import timeit, torch_profile
label_desc: Use image node_id 6 for calling a global function with example usage: inference(model, test_loader, device, bf16) without return types