code: def train_linear(
      num_workers=1,
      num_hidden_layers=1,
      use_auto_transfer=True,
      epochs=3,
  ):
      config = {
          "lr": 1e-2,
          "hidden_size": num_hidden_layers,
          "batch_size": 4096,
          "epochs": epochs,
          "use_auto_transfer": use_auto_transfer,
      }
      trainer = TorchTrainer(
          train_func,
          train_loop_config=config,
          scaling_config=ScalingConfig(
              use_gpu=True, num_workers=num_workers
          ),
      )
      results = trainer.fit()
  
      print(results.metrics)
      return results
  
file_path: ray/python/ray/train/examples/pytorch/torch_data_prefetch_benchmark/auto_pipeline_for_host_to_device_data_transfer.py
imports: import argparse
  import warnings
  import numpy
  import torch
  import torch.nn
  import ray.train
  from ray.train import ScalingConfig
  from ray.train.torch import TorchTrainer
label_desc: Use image node_id 3 for calling a global function with example usage: train_linear(num_workers, num_hidden_layers, use_auto_transfer, epochs) and returns: results