code: def ddp_recipes(rank, size, backend="gloo"):
      """Initialize the distributed environment."""
      os.environ["WORLD_SIZE"] = f"{size}"
      os.environ["RANK"] = f"{rank}"
      os.environ["LOCAL_RANK"] = f"{rank}"
      os.environ["MASTER_ADDR"] = "127.0.0.1"
      os.environ["MASTER_PORT"] = "29500"
  
      run_opts = dict()
      run_opts["distributed_launch"] = True
      run_opts["distributed_backend"] = backend
  
      sb.utils.distributed.ddp_init_group(run_opts)
  
      recipe(device="cpu", yaml_file="random.yaml", run_opts=run_opts)
      recipe(device="cpu", yaml_file="asc.yaml", run_opts=run_opts)
      recipe(device="cpu", yaml_file="dsc.yaml", run_opts=run_opts)
  
file_path: speechbrain/tests/integration/sampling/example_sorting.py
imports: import os
  import torch
  import pickle
  import pathlib
  import itertools
  import speechbrain
  import torch.multiprocessing
  from hyperpyyaml import load_hyperpyyaml
label_desc: Use image node_id 4 for calling a global function with example usage: ddp_recipes(rank, size, backend) without return types