code: def process_execution_check():
      accelerator = Accelerator()
      num_processes = accelerator.num_processes
      # Test main_process_first context manager
      path = Path("check_main_process_first.txt")
      with accelerator.main_process_first():
          if accelerator.is_main_process:
              time.sleep(0.1)  # ensure main process takes longest
              with open(path, "a+") as f:
                  f.write("Currently in the main process\n")
          else:
              with open(path, "a+") as f:
                  f.write("Now on another process\n")
      accelerator.wait_for_everyone()
  
      if accelerator.is_main_process:
          with open(path, "r") as f:
              text = "".join(f.readlines())
          try:
              assert text.startswith(
                  "Currently in the main process\n"
              ), "Main process was not first"
              if num_processes > 1:
                  assert text.endswith(
                      "Now on another process\n"
                  ), "Main process was not first"
              assert (
                  text.count("Now on another process\n")
                  == accelerator.num_processes - 1
              ), f"Only wrote to file {text.count('Now on another process') + 1} times, not {accelerator.num_processes}"
          except AssertionError:
              path.unlink()
              raise
  
      if accelerator.is_main_process and path.exists():
          path.unlink()
      accelerator.wait_for_everyone()
      # Test the decorators
      f = io.StringIO()
      with contextlib.redirect_stdout(f):
          accelerator.on_main_process(print_main)(accelerator.state)
      result = f.getvalue().rstrip()
      if accelerator.is_main_process:
          assert (
              result == "Printing from the main process 0"
          ), f"{result} != Printing from the main process 0"
      else:
          assert f.getvalue().rstrip() == "", f'{result} != ""'
      f.truncate(0)
      f.seek(0)
  
      with contextlib.redirect_stdout(f):
          accelerator.on_local_main_process(print_local_main)(
              accelerator.state
          )
      if accelerator.is_local_main_process:
          assert (
              f.getvalue().rstrip()
              == "Printing from the local main process 0"
          )
      else:
          assert f.getvalue().rstrip() == ""
      f.truncate(0)
      f.seek(0)
  
      with contextlib.redirect_stdout(f):
          accelerator.on_last_process(print_last)(accelerator.state)
      if accelerator.is_last_process:
          assert (
              f.getvalue().rstrip()
              == f"Printing from the last process {accelerator.state.num_processes - 1}"
          )
      else:
          assert f.getvalue().rstrip() == ""
      f.truncate(0)
      f.seek(0)
  
      for process_idx in range(num_processes):
          with contextlib.redirect_stdout(f):
              accelerator.on_process(
                  print_on, process_index=process_idx
              )(accelerator.state, process_idx)
          if accelerator.process_index == process_idx:
              assert (
                  f.getvalue().rstrip()
                  == f"Printing from process {process_idx}: {accelerator.process_index}"
              )
          else:
              assert f.getvalue().rstrip() == ""
          f.truncate(0)
          f.seek(0)
  
imports: import contextlib
  import io
  import math
  import time
  from copy import deepcopy
  from pathlib import Path
  import numpy
  import torch
  from torch.utils.data import DataLoader, Dataset
  from accelerate import Accelerator
  from accelerate.data_loader import SeedableRandomSampler, prepare_data_loader
  from accelerate.state import AcceleratorState
  from accelerate.test_utils import RegressionDataset, are_the_same_tensors
  from accelerate.utils import DistributedType, gather, is_bf16_available, is_ipex_available, is_npu_available, is_xpu_available, set_seed, synchronize_rng_states
label_desc: Use image node_id 5 for calling a global function with example usage: process_execution_check() without return types