code: def main():
      args = parser.parse_args()
      print(args)
  
      invalidInputError(
          args.warmup_iterations >= 0,
          "warmup iterations should be a non-negative int",
      )
      if args.jit and args.int8:
          invalidInputError(
              False,
              "jit path is not available for int8 path using ipex",
          )
      if not args.ipex:
          # for official pytorch, int8 and jit path is not enabled.
          invalidInputError(
              not args.int8,
              "int8 path is not enabled for official pytorch",
          )
          invalidInputError(
              not args.jit,
              "jit path is not enabled for official pytorch",
          )
  
      env = {
          "MALLOC_CONF": "oversize_threshold:1,background_thread:true,metadata_thp:"
          "auto,dirty_decay_ms:9000000000,muzzy_decay_ms:9000000000",
          "DNNL_PRIMITIVE_CACHE_CAPACITY": "1024",
          "OMP_NUM_THREADS": str(args.cores),
          "KMP_BLOCKTIME": "1",
          "KMP_AFFINITY": "granularity=fine,compact,1,0",
      }
      if "LD_PRELOAD" in os.environ:
          env["LD_PRELOAD"] = os.environ["LD_PRELOAD"]
  
      if args.cluster_mode == "local":
          init_orca_context("local", cores=args.cores, memory="10g")
      elif args.cluster_mode == "standalone":
          init_orca_context(
              "standalone",
              master=args.master,
              cores=args.cores,
              num_nodes=args.num_nodes,
              memory="10g",
              driver_cores=1,
              driver_memory="2g",
              env=env,
          )
      elif args.cluster_mode == "yarn":
          init_orca_context(
              "yarn-client",
              cores=args.cores,
              num_nodes=args.num_nodes,
              memory="10g",
              driver_cores=4,
              driver_memory="2g",
              env=env,
          )
      else:
          invalidInputError(
              False,
              "cluster_mode should be one of 'local', 'yarn' and 'standalone', "
              "but got " + args.cluster_mode,
          )
      validate(args)
      stop_orca_context()
  
file_path: BigDL/python/orca/example/learn/pytorch/resnet50/inference.py
imports: import os
  import argparse
  import torch
  import torch.nn
  import torch.utils.data
  import torchvision.transforms
  import torchvision.datasets
  import torchvision.models
  from bigdl.dllib.utils.log4Error import *
  from bigdl.orca import init_orca_context, stop_orca_context
  from bigdl.orca.learn.pytorch.callbacks import MainCallback
label_desc: Use image node_id 1 for calling a global function with example usage: main() without return types