class_docstr: Test for the dispatching logic of the parameter shift method
docstr: Test the case where expectation values are independent of all parameters.
docstr_tok: ["Test","the","case","where","expectation","values","are","independent","of","all","parameters","."]
code: def test_all_independent(self):
      """Test the case where expectation values are independent of all parameters."""
      dev = qml.device("default.gaussian", wires=2)
  
      with qml.queuing.AnnotatedQueue() as q:
          qml.Displacement(1, 0, wires=[1])
          qml.Displacement(1, 0, wires=[1])
          qml.expval(qml.QuadX(0))
  
      tape = qml.tape.QuantumScript.from_queue(q)
      tape.trainable_params = {0, 2}
      tapes, fn = qml.gradients.param_shift_cv(tape, dev)
      assert len(tapes) == 0
  
      grad = fn(dev.batch_execute(tapes))
      assert np.allclose(grad, [0, 0])
  
imports: import unittest.mock
  import pytest
  import pennylane
  from pennylane import numpy
  from pennylane.gradients import param_shift_cv
  from pennylane.gradients.gradient_transform import choose_trainable_params
  from pennylane.gradients.parameter_shift_cv import _grad_method_cv, _find_gradient_methods_cv, _transform_observable
label_desc: Use image node_id 13 for calling the TestParameterShiftLogic obj's underlying member method code with example usage: obj.test_all_independent() without return types