code: def test_clip_no_gradients_norm_meta_device(
      self, mock_clip_grad_norm: MagicMock
  ) -> None:
      # Clip all gradients to zero
      param_1 = Variable(
          torch.tensor([1.0, 2.0], device=torch.device("meta")),
          requires_grad=True,
      )
  
      keyed_optimizer = DummyKeyedOptimizer(
          {"param_1": param_1}, {}, [{"params": [param_1]}]
      )
  
      gradient_clipping_optimizer = GradientClippingOptimizer(
          optimizer=keyed_optimizer,
          max_gradient=0.0,
          clipping=GradientClipping.NORM,
      )
  
      gradient_clipping_optimizer.zero_grad()
      gradient_clipping_optimizer.step()
  
      mock_clip_grad_norm.assert_not_called()
  
file_path: torchrec/torchrec/optim/tests/test_clipping.py
imports: import unittest
  from unittest.mock import MagicMock, patch
  import torch
  from torch.autograd import Variable
  from torchrec.optim.clipping import GradientClipping, GradientClippingOptimizer
  from torchrec.optim.test_utils import DummyKeyedOptimizer
label_desc: Use image node_id 9 for calling the TestGradientClippingOptimizer obj's underlying member method code with example usage: obj.test_clip_no_gradients_norm_meta_device(mock_clip_grad_norm) without return types