code: def test_clip_no_gradients_value(self) -> None:
      # gradients are too small to be clipped
      param_1 = Variable(torch.tensor([1.0, 2.0]), requires_grad=True)
  
      keyed_optimizer = DummyKeyedOptimizer(
          {"param_1": param_1}, {}, [{"params": [param_1]}]
      )
  
      gradient_clipping_optimizer = GradientClippingOptimizer(
          optimizer=keyed_optimizer,
          max_gradient=1.0,
          clipping=GradientClipping.VALUE,
      )
  
      gradient_clipping_optimizer.zero_grad()
      param_1.grad = torch.tensor([0.5, 0.5])
      gradient_clipping_optimizer.step()
  
      # pyre-fixme[6]: For 1st argument expected `Tensor` but got `Optional[Tensor]`.
      self.assertTrue(
          torch.equal(param_1.grad, torch.tensor([0.5, 0.5]))
      )
  
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 6 for calling the TestGradientClippingOptimizer obj's underlying member method code with example usage: obj.test_clip_no_gradients_value() without return types