class_docstr: Test the torch interface execute function
  integrates well for both forward and backward execution
class_docstr_tok: ["Test","the","torch","interface","execute","function","integrates","well","for","both","forward","and","backward","execution"]
docstr: Test the classical processing of gate parameters within the quantum tape
code: def test_classical_processing(
      self, torch_device, execute_kwargs, tol
  ):
      """Test the classical processing of gate parameters within the quantum tape"""
      p_val = [0.1, 0.2]
      params = torch.tensor(
          p_val, requires_grad=True, device=torch_device
      )
  
      dev = qml.device("default.qubit.legacy", wires=1)
  
      with qml.queuing.AnnotatedQueue() as q:
          qml.RY(params[0] * params[1], wires=0)
          qml.RZ(0.2, wires=0)
          qml.RX(
              params[1] + params[1] ** 2 + torch.sin(params[0]), wires=0
          )
          qml.expval(qml.PauliZ(0))
  
      tape = qml.tape.QuantumScript.from_queue(q)
  
      res = execute([tape], dev, **execute_kwargs)[0]
  
      assert tape.trainable_params == [0, 2]
  
      tape_params = torch.tensor(
          [i.detach() for i in tape.get_parameters()],
          device=torch_device,
      )
      expected = torch.tensor(
          [
              p_val[0] * p_val[1],
              p_val[1] + p_val[1] ** 2 + np.sin(p_val[0]),
          ],
          dtype=tape_params.dtype,
          device=torch_device,
      )
  
      assert torch.allclose(
          tape_params,
          expected,
          atol=tol,
          rtol=0,
      )
  
      res.backward()
  
      assert isinstance(params.grad, torch.Tensor)
      assert params.shape == (2,)
  
imports: import numpy
  import pytest
  import pennylane
  from pennylane.gradients import finite_diff, param_shift
  from pennylane import execute
label_desc: Use image node_id 6 for calling the TestTorchExecuteIntegration obj's underlying member method code with example usage: obj.test_classical_processing(torch_device, execute_kwargs, tol) without return types