code: def check_grad_clip_norm(rank, world_size, port):
      disable_existing_loggers()
      colossalai.launch(
          config={},
          rank=rank,
          world_size=world_size,
          host="localhost",
          port=port,
          backend="nccl",
      )
      run_test()
  
file_path: colossalai/tests/test_shardformer/test_hybrid_parallel_grad_clip_norm/test_naive_optimizer.py
imports: import pytest
  import torch
  from torch.nn.utils.clip_grad import clip_grad_norm_
  import colossalai
  from colossalai.logging import disable_existing_loggers
  from colossalai.shardformer.layer.utils import Randomizer
  from colossalai.tensor.d_tensor.api import clear_layout_converter
  from colossalai.testing import clear_cache_before_run, parameterize, rerun_if_address_is_in_use, spawn
  from tests.kit.model_zoo import model_zoo
  from tests.test_shardformer.test_model._utils import build_model_from_hybrid_plugin, check_all_grad_tensors, check_loss, check_output_hidden_state, check_weight, get_grad_tensors_for_check, run_forward_backward_with_hybrid_plugin, unwrap_model
label_desc: Use image node_id 4 for calling a global function with example usage: check_grad_clip_norm(rank, world_size, port) without return types