code: def test_unwrap():
      """Test that unwrap converts lists to lists and interface variables to numpy."""
      params = [
          [torch.tensor(2)],
          [[3, 4], torch.tensor([5, 6])],
          tf.Variable([-1.0, -2.0]),
          [jnp.array(0.5), jnp.array([6, 7])],
          torch.tensor(0.5),
      ]
  
      out = fn.unwrap(params)
  
      assert out[0] == [2]
      assert out[1][0] == [3, 4]
      assert fn.allclose(out[1][1], np.array([5, 6]))
      assert fn.get_interface(out[1][1]) == "numpy"
  
      assert fn.allclose(out[2], np.array([-1.0, -2.0]))
      assert fn.get_interface(out[2]) == "numpy"
  
      assert out[3][0] == 0.5
      assert fn.allclose(out[3][1], np.array([6, 7]))
      assert fn.get_interface(out[3][1]) == "numpy"
  
      assert out[4] == 0.5
  
imports: import autoray
  import numpy
  import pytest
  import scipy
  from autoray import numpy
  from pennylane import math
  from pennylane import numpy
  from pennylane import grad
label_desc: Use image node_id 6 for calling a global function with example usage: test_unwrap() without return types