def METHOD_NAME(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])))