code: def test_clip_gradients(clip_type, accelerator, precision):
      if clip_type == "norm" and precision == "16-mixed":
          pytest.skip(
              reason="Clipping by norm with 16-mixed is numerically unstable."
          )
  
      fabric = Fabric(
          accelerator=accelerator,
          devices=2,
          precision=precision,
          strategy="ddp",
      )
      fabric.launch()
      _run_test_clip_gradients(fabric=fabric, clip_type=clip_type)
  
file_path: pytorch-lightning/tests/tests_fabric/strategies/test_ddp_integration.py
imports: from copy import deepcopy
  import pytest
  import torch
  from lightning.fabric import Fabric
  from tests_fabric.helpers.runif import RunIf
  from tests_fabric.strategies.test_single_device import _run_test_clip_gradients
label_desc: Use image node_id 3 for calling a global function with example usage: test_clip_gradients(clip_type, accelerator, precision) without return types