code: def launch_train(*args):
      num_processes = torch.cuda.device_count()
      print(f"Device count: {num_processes}")
      with patch_environment(
          world_size=num_processes,
          master_addr="127.0.0.1",
          master_port="29500",
          mixed_precision=args[1].mixed_precision,
      ):
          launcher = PrepareForLaunch(
              training_function, distributed_type="MULTI_GPU"
          )
          torch.multiprocessing.start_processes(
              launcher,
              args=args,
              nprocs=num_processes,
              start_method="spawn",
          )
  
imports: import argparse
  import runhouse
  import torch
  from nlp_example import training_function
  from accelerate.utils import PrepareForLaunch, patch_environment
label_desc: Use image node_id 1 for calling a global function with example usage: launch_train() without return types