code: def get_pet_launch_config(nproc: int) -> pet.LaunchConfig:
      """
      Initialize pet.LaunchConfig for single-node, multi-rank functions.
  
      Args:
          nproc: The number of processes to launch.
  
      Returns:
          An instance of pet.LaunchConfig for single-node, multi-rank functions.
  
      Example:
          >>> from torch.distributed import launcher
          >>> launch_config = get_pet_launch_config(nproc=8)
          >>> launcher.elastic_launch(config=launch_config, entrypoint=train)()
      """
      return pet.LaunchConfig(
          min_nodes=1,
          max_nodes=1,
          nproc_per_node=nproc,
          run_id=str(uuid.uuid4()),
          rdzv_backend="c10d",
          rdzv_endpoint="localhost:0",
          max_restarts=0,
          monitor_interval=1,
      )
  
imports: import ctypes
  import os
  import sys
  import unittest
  import uuid
  from contextlib import contextmanager
  from dataclasses import dataclass
  from datetime import timedelta
  from functools import wraps
  from io import StringIO
  from typing import Any, Callable, Dict, Generator, List, Optional, TextIO, Tuple, TypeVar
  import torch
  import torch.distributed.launcher
  from pyre_extensions import ParameterSpecification
  from torch import distributed, multiprocessing
  from torch.distributed.elastic.utils.distributed import get_free_port
  from torchtnt.utils.distributed import destroy_process_group
label_desc: Use image node_id 1 for calling a global function with example usage: get_pet_launch_config(nproc) and returns: pet