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 that a tape with no parameters is correctly
  ignored during the gradient computation
code: def test_tape_no_parameters(self, torch_device, execute_kwargs, tol):
      """Test that a tape with no parameters is correctly
      ignored during the gradient computation"""
      dev = qml.device("default.qubit.legacy", wires=1)
      params = torch.tensor(
          [0.1, 0.2], requires_grad=True, device=torch_device
      )
      x, y = params.detach()
  
      with qml.queuing.AnnotatedQueue() as q1:
          qml.Hadamard(0)
          qml.expval(qml.PauliX(0))
  
      tape1 = qml.tape.QuantumScript.from_queue(q1)
  
      with qml.queuing.AnnotatedQueue() as q2:
          qml.RY(0.5, wires=0)
          qml.expval(qml.PauliZ(0))
  
      tape2 = qml.tape.QuantumScript.from_queue(q2)
  
      with qml.queuing.AnnotatedQueue() as q3:
          qml.RY(params[0], wires=0)
          qml.RX(params[1], wires=0)
          qml.expval(qml.PauliZ(0))
  
      tape3 = qml.tape.QuantumScript.from_queue(q3)
  
      res = sum(execute([tape1, tape2, tape3], dev, **execute_kwargs))
      expected = torch.tensor(
          1 + np.cos(0.5), dtype=res.dtype
      ) + torch.cos(x) * torch.cos(y)
      expected = expected.to(device=res.device)
  
      assert torch.allclose(res, expected, atol=tol, rtol=0)
  
      res.backward()
      grad = params.grad.detach()
      expected = torch.tensor(
          [-torch.cos(y) * torch.sin(x), -torch.cos(x) * torch.sin(y)],
          dtype=grad.dtype,
          device=grad.device,
      )
      assert torch.allclose(grad, expected, atol=tol, rtol=0)
  
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 4 for calling the TestTorchExecuteIntegration obj's underlying member method code with example usage: obj.test_tape_no_parameters(torch_device, execute_kwargs, tol) without return types