code: def test_unhook():
      """Test unhook that frees the tensor from CUDA memory."""
      model = Linear(
          123, 456, bias=False
      ).cuda()  # unique shape so that it can be found
      optim = AdaScale(
          SGD(model.parameters(), lr=0.1), num_gradients_to_accumulate=2
      )
  
      torch.cuda.empty_cache()
      target_shape = (456, 123)
      assert find_tensor_by_shape(
          target_shape
      ), "something wrong with gc-based method to find the tensor"
  
      optim.unhook()
      del model
      del optim
      torch.cuda.empty_cache()
      assert not find_tensor_by_shape(
          target_shape
      ), "tensor should have been released"
  
imports: import tempfile
  import numpy
  import pytest
  import torch
  from torch import Tensor
  from torch.nn import Linear, Sequential
  from torch.optim import SGD
  from torch.optim.lr_scheduler import LambdaLR
  from fairscale.fair_dev.testing.golden_testing_data import adascale_test_data
  from fairscale.fair_dev.testing.testing import make_cudnn_deterministic, skip_if_no_cuda
  from fairscale.fair_dev.testing.testing_memory import find_tensor_by_shape
  from fairscale.optim import AdaScale
label_desc: Use image node_id 11 for calling a global function with example usage: test_unhook() without return types