code: def step(
      time_fn,
      model,
      example_inputs,
      autocast_enable: False,
      amp_precision: Optional[str] = "float16",
  ):
      start_time = time_fn()
      with autocast_fn(
          enabled=autocast_enable, amp_precision=amp_precision
      ):
          model(example_inputs)
      end_time = time_fn(cuda_sync=True)
      return end_time - start_time
  
file_path: ml-cvnets/main_benchmark.py
imports: import time
  from typing import Optional
  import torch
  from torch.cuda.amp import autocast
  from cvnets import get_model
  from engine.utils import autocast_fn
  from options.opts import get_benchmarking_arguments
  from utils import logger
  from utils.common_utils import device_setup
  from utils.pytorch_to_coreml import convert_pytorch_to_coreml
  from utils.tensor_utils import create_rand_tensor
label_desc: Use image node_id 3 for calling a global function with example usage: step(time_fn, model, example_inputs, autocast_enable, amp_precision) and returns: unknown