code: def inference_run(model, loader, bf16):
      model.eval()
      for data in loader:
          data = data.to(device)
          if bf16:
              data.x = data.x.to(torch.bfloat16)
          model(data)
  
file_path: pytorch_geometric/benchmark/kernel/train_eval.py
imports: import time
  import torch
  import torch.nn.functional
  from sklearn.model_selection import StratifiedKFold
  from torch import tensor
  from torch.optim import Adam
  from torch_geometric.loader import DataLoader
  from torch_geometric.loader import DenseDataLoader
label_desc: Use image node_id 7 for calling a global function with example usage: inference_run(model, loader, bf16) without return types