code: def run_1_epoch(
      dataloader, feat, y, fanout, batch_size, model_backend
  ):
      if feat is not None:
          model = create_model(
              feat.shape[1],
              172,
              len(fanout),
              model_backend=model_backend,
          )
          opt = torch.optim.Adam(model.parameters(), lr=0.01)
      else:
          model = None
          opt = None
  
      # Warmup RUN
      times = train_model(model, dataloader, opt, feat, y)
  
      epoch_st = time.time()
      times = train_model(model, dataloader, opt, feat, y)
      epoch_time = time.time() - epoch_st
      time_d = analyze_time(
          dataloader, times, epoch_time, fanout, batch_size
      )
      return time_d
  
file_path: cugraph/benchmarks/cugraph-dgl/scale-benchmarks/model.py
imports: import torch
  import torch.nn.functional
  import time
label_desc: Use image node_id 4 for calling a global function with example usage: run_1_epoch(dataloader, feat, y, fanout, batch_size, model_backend) and returns: time_d